openai_whisper-large-v3-v20240930_547MB/TextDecoder.mlmodelc/model.mil
| 1 | program(1.0) |
| 2 | [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}})] |
| 3 | { |
| 4 | func main<ios16>(tensor<int32, [1]> cache_length, tensor<fp16, [1, 448]> decoder_key_padding_mask, tensor<fp16, [1, 1280, 1, 1500]> encoder_output_embeds, tensor<int32, [1]> input_ids, tensor<fp16, [1, 5120, 1, 448]> key_cache, tensor<fp16, [1, 448]> kv_cache_update_mask, tensor<fp16, [1, 5120, 1, 448]> value_cache) { |
| 5 | tensor<int32, []> var_24_axis_0 = const()[name = tensor<string, []>("op_24_axis_0"), val = tensor<int32, []>(0)]; |
| 6 | tensor<int32, []> var_24_batch_dims_0 = const()[name = tensor<string, []>("op_24_batch_dims_0"), val = tensor<int32, []>(0)]; |
| 7 | tensor<fp16, [51866, 1280]> embed_tokens_weight_to_fp16 = const()[name = tensor<string, []>("embed_tokens_weight_to_fp16"), val = tensor<fp16, [51866, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; |
| 8 | tensor<fp16, [1, 1280]> var_24_cast_fp16 = gather(axis = var_24_axis_0, batch_dims = var_24_batch_dims_0, indices = input_ids, x = embed_tokens_weight_to_fp16)[name = tensor<string, []>("op_24_cast_fp16")]; |
| 9 | tensor<int32, []> var_28_axis_0 = const()[name = tensor<string, []>("op_28_axis_0"), val = tensor<int32, []>(0)]; |
| 10 | tensor<int32, []> var_28_batch_dims_0 = const()[name = tensor<string, []>("op_28_batch_dims_0"), val = tensor<int32, []>(0)]; |
| 11 | tensor<fp16, [448, 1280]> embed_positions_weight_to_fp16 = const()[name = tensor<string, []>("embed_positions_weight_to_fp16"), val = tensor<fp16, [448, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132777088)))]; |
| 12 | tensor<fp16, [1, 1280]> var_28_cast_fp16 = gather(axis = var_28_axis_0, batch_dims = var_28_batch_dims_0, indices = cache_length, x = embed_positions_weight_to_fp16)[name = tensor<string, []>("op_28_cast_fp16")]; |
| 13 | tensor<fp16, [1, 1280]> hidden_states_1_cast_fp16 = add(x = var_24_cast_fp16, y = var_28_cast_fp16)[name = tensor<string, []>("hidden_states_1_cast_fp16")]; |
| 14 | tensor<int32, [1]> var_42_axes_0 = const()[name = tensor<string, []>("op_42_axes_0"), val = tensor<int32, [1]>([2])]; |
| 15 | tensor<fp16, [1, 1280, 1]> var_42_cast_fp16 = expand_dims(axes = var_42_axes_0, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("op_42_cast_fp16")]; |
| 16 | tensor<int32, [1]> inputs_1_axes_0 = const()[name = tensor<string, []>("inputs_1_axes_0"), val = tensor<int32, [1]>([3])]; |
| 17 | tensor<fp16, [1, 1280, 1, 1]> inputs_1_cast_fp16 = expand_dims(axes = inputs_1_axes_0, x = var_42_cast_fp16)[name = tensor<string, []>("inputs_1_cast_fp16")]; |
| 18 | tensor<int32, [4]> tile_0 = const()[name = tensor<string, []>("tile_0"), val = tensor<int32, [4]>([1280, 1280, 1280, 1280])]; |
| 19 | tensor<int32, []> var_47_axis_0 = const()[name = tensor<string, []>("op_47_axis_0"), val = tensor<int32, []>(1)]; |
| 20 | tensor<fp16, [1, 1280, 1, 448]> var_47_cast_fp16_0, tensor<fp16, [1, 1280, 1, 448]> var_47_cast_fp16_1, tensor<fp16, [1, 1280, 1, 448]> var_47_cast_fp16_2, tensor<fp16, [1, 1280, 1, 448]> var_47_cast_fp16_3 = split(axis = var_47_axis_0, split_sizes = tile_0, x = key_cache)[name = tensor<string, []>("op_47_cast_fp16")]; |
| 21 | tensor<int32, [4]> tile_1 = const()[name = tensor<string, []>("tile_1"), val = tensor<int32, [4]>([1280, 1280, 1280, 1280])]; |
| 22 | tensor<int32, []> var_54_axis_0 = const()[name = tensor<string, []>("op_54_axis_0"), val = tensor<int32, []>(1)]; |
| 23 | tensor<fp16, [1, 1280, 1, 448]> var_54_cast_fp16_0, tensor<fp16, [1, 1280, 1, 448]> var_54_cast_fp16_1, tensor<fp16, [1, 1280, 1, 448]> var_54_cast_fp16_2, tensor<fp16, [1, 1280, 1, 448]> var_54_cast_fp16_3 = split(axis = var_54_axis_0, split_sizes = tile_1, x = value_cache)[name = tensor<string, []>("op_54_cast_fp16")]; |
| 24 | tensor<int32, []> var_64 = const()[name = tensor<string, []>("op_64"), val = tensor<int32, []>(3)]; |
| 25 | tensor<int32, [1]> out_1_axes_0 = const()[name = tensor<string, []>("out_1_axes_0"), val = tensor<int32, [1]>([1])]; |
| 26 | tensor<fp16, []> var_90_to_fp16 = const()[name = tensor<string, []>("op_90_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 27 | tensor<fp16, [1, 1280, 1, 1]> out_1_cast_fp16 = layer_norm(axes = out_1_axes_0, epsilon = var_90_to_fp16, x = inputs_1_cast_fp16)[name = tensor<string, []>("out_1_cast_fp16")]; |
| 28 | tensor<fp16, [1280]> obj_1_mean_0_to_fp16 = const()[name = tensor<string, []>("obj_1_mean_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133924032)))]; |
| 29 | tensor<fp16, [1280]> obj_1_variance_0_to_fp16 = const()[name = tensor<string, []>("obj_1_variance_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133926656)))]; |
| 30 | tensor<fp16, [1280]> obj_1_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_1_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133929280)))]; |
| 31 | tensor<fp16, [1280]> obj_1_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_1_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133931904)))]; |
| 32 | tensor<fp16, []> obj_1_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_1_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 33 | tensor<fp16, [1, 1280, 1, 1]> obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor<string, []>("obj_1_cast_fp16")]; |
| 34 | tensor<string, []> pretrained_out_1_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| 35 | tensor<int32, [2]> pretrained_out_1_strides_0 = const()[name = tensor<string, []>("pretrained_out_1_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 36 | tensor<int32, [4]> pretrained_out_1_pad_0 = const()[name = tensor<string, []>("pretrained_out_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 37 | tensor<int32, [2]> pretrained_out_1_dilations_0 = const()[name = tensor<string, []>("pretrained_out_1_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 38 | tensor<int32, []> pretrained_out_1_groups_0 = const()[name = tensor<string, []>("pretrained_out_1_groups_0"), val = tensor<int32, []>(1)]; |
| 39 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_self_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133934528))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134753792))), name = tensor<string, []>("layers_0_self_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 40 | tensor<fp16, [1280]> layers_0_self_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134753920)))]; |
| 41 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_1_dilations_0, groups = pretrained_out_1_groups_0, pad = pretrained_out_1_pad_0, pad_type = pretrained_out_1_pad_type_0, strides = pretrained_out_1_strides_0, weight = layers_0_self_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_1_cast_fp16)[name = tensor<string, []>("pretrained_out_1_cast_fp16")]; |
| 42 | tensor<string, []> input_1_pad_type_0 = const()[name = tensor<string, []>("input_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| 43 | tensor<int32, [2]> input_1_strides_0 = const()[name = tensor<string, []>("input_1_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 44 | tensor<int32, [4]> input_1_pad_0 = const()[name = tensor<string, []>("input_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 45 | tensor<int32, [2]> input_1_dilations_0 = const()[name = tensor<string, []>("input_1_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 46 | tensor<int32, []> input_1_groups_0 = const()[name = tensor<string, []>("input_1_groups_0"), val = tensor<int32, []>(1)]; |
| 47 | tensor<fp16, [16, 1280, 1, 1]> layers_0_self_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134756544)))]; |
| 48 | tensor<fp16, [1, 16, 1, 1]> input_1_cast_fp16 = conv(dilations = input_1_dilations_0, groups = input_1_groups_0, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = input_1_strides_0, weight = layers_0_self_attn_q_proj_loraA_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")]; |
| 49 | tensor<string, []> lora_out_1_pad_type_0 = const()[name = tensor<string, []>("lora_out_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| 50 | tensor<int32, [2]> lora_out_1_strides_0 = const()[name = tensor<string, []>("lora_out_1_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 51 | tensor<int32, [4]> lora_out_1_pad_0 = const()[name = tensor<string, []>("lora_out_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 52 | tensor<int32, [2]> lora_out_1_dilations_0 = const()[name = tensor<string, []>("lora_out_1_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 53 | tensor<int32, []> lora_out_1_groups_0 = const()[name = tensor<string, []>("lora_out_1_groups_0"), val = tensor<int32, []>(1)]; |
| 54 | tensor<fp16, [1280, 16, 1, 1]> layers_0_self_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134797568)))]; |
| 55 | tensor<fp16, [1, 1280, 1, 1]> lora_out_1_cast_fp16 = conv(dilations = lora_out_1_dilations_0, groups = lora_out_1_groups_0, pad = lora_out_1_pad_0, pad_type = lora_out_1_pad_type_0, strides = lora_out_1_strides_0, weight = layers_0_self_attn_q_proj_loraB_weight_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("lora_out_1_cast_fp16")]; |
| 56 | tensor<fp16, [1, 1280, 1, 1]> query_1_cast_fp16 = add(x = pretrained_out_1_cast_fp16, y = lora_out_1_cast_fp16)[name = tensor<string, []>("query_1_cast_fp16")]; |
| 57 | tensor<string, []> pretrained_out_3_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_3_pad_type_0"), val = tensor<string, []>("valid")]; |
| 58 | tensor<int32, [2]> pretrained_out_3_strides_0 = const()[name = tensor<string, []>("pretrained_out_3_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 59 | tensor<int32, [4]> pretrained_out_3_pad_0 = const()[name = tensor<string, []>("pretrained_out_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 60 | tensor<int32, [2]> pretrained_out_3_dilations_0 = const()[name = tensor<string, []>("pretrained_out_3_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 61 | tensor<int32, []> pretrained_out_3_groups_0 = const()[name = tensor<string, []>("pretrained_out_3_groups_0"), val = tensor<int32, []>(1)]; |
| 62 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_self_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134838592))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135657856))), name = tensor<string, []>("layers_0_self_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 63 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_3_cast_fp16 = conv(dilations = pretrained_out_3_dilations_0, groups = pretrained_out_3_groups_0, pad = pretrained_out_3_pad_0, pad_type = pretrained_out_3_pad_type_0, strides = pretrained_out_3_strides_0, weight = layers_0_self_attn_k_proj_pretrained_weight_to_fp16_palettized, x = obj_1_cast_fp16)[name = tensor<string, []>("pretrained_out_3_cast_fp16")]; |
| 64 | tensor<string, []> input_3_pad_type_0 = const()[name = tensor<string, []>("input_3_pad_type_0"), val = tensor<string, []>("valid")]; |
| 65 | tensor<int32, [2]> input_3_strides_0 = const()[name = tensor<string, []>("input_3_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 66 | tensor<int32, [4]> input_3_pad_0 = const()[name = tensor<string, []>("input_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 67 | tensor<int32, [2]> input_3_dilations_0 = const()[name = tensor<string, []>("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 68 | tensor<int32, []> input_3_groups_0 = const()[name = tensor<string, []>("input_3_groups_0"), val = tensor<int32, []>(1)]; |
| 69 | tensor<fp16, [16, 1280, 1, 1]> layers_0_self_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135657984)))]; |
| 70 | tensor<fp16, [1, 16, 1, 1]> input_3_cast_fp16 = conv(dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = layers_0_self_attn_k_proj_loraA_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")]; |
| 71 | tensor<string, []> lora_out_3_pad_type_0 = const()[name = tensor<string, []>("lora_out_3_pad_type_0"), val = tensor<string, []>("valid")]; |
| 72 | tensor<int32, [2]> lora_out_3_strides_0 = const()[name = tensor<string, []>("lora_out_3_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 73 | tensor<int32, [4]> lora_out_3_pad_0 = const()[name = tensor<string, []>("lora_out_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 74 | tensor<int32, [2]> lora_out_3_dilations_0 = const()[name = tensor<string, []>("lora_out_3_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 75 | tensor<int32, []> lora_out_3_groups_0 = const()[name = tensor<string, []>("lora_out_3_groups_0"), val = tensor<int32, []>(1)]; |
| 76 | tensor<fp16, [1280, 16, 1, 1]> layers_0_self_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135699008)))]; |
| 77 | tensor<fp16, [1, 1280, 1, 1]> lora_out_3_cast_fp16 = conv(dilations = lora_out_3_dilations_0, groups = lora_out_3_groups_0, pad = lora_out_3_pad_0, pad_type = lora_out_3_pad_type_0, strides = lora_out_3_strides_0, weight = layers_0_self_attn_k_proj_loraB_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("lora_out_3_cast_fp16")]; |
| 78 | tensor<fp16, [1, 1280, 1, 1]> current_key_1_cast_fp16 = add(x = pretrained_out_3_cast_fp16, y = lora_out_3_cast_fp16)[name = tensor<string, []>("current_key_1_cast_fp16")]; |
| 79 | tensor<string, []> pretrained_out_5_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_5_pad_type_0"), val = tensor<string, []>("valid")]; |
| 80 | tensor<int32, [2]> pretrained_out_5_strides_0 = const()[name = tensor<string, []>("pretrained_out_5_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 81 | tensor<int32, [4]> pretrained_out_5_pad_0 = const()[name = tensor<string, []>("pretrained_out_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 82 | tensor<int32, [2]> pretrained_out_5_dilations_0 = const()[name = tensor<string, []>("pretrained_out_5_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 83 | tensor<int32, []> pretrained_out_5_groups_0 = const()[name = tensor<string, []>("pretrained_out_5_groups_0"), val = tensor<int32, []>(1)]; |
| 84 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_self_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135740032))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136559296))), name = tensor<string, []>("layers_0_self_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 85 | tensor<fp16, [1280]> layers_0_self_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136559424)))]; |
| 86 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_5_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_5_dilations_0, groups = pretrained_out_5_groups_0, pad = pretrained_out_5_pad_0, pad_type = pretrained_out_5_pad_type_0, strides = pretrained_out_5_strides_0, weight = layers_0_self_attn_v_proj_pretrained_weight_to_fp16_palettized, x = obj_1_cast_fp16)[name = tensor<string, []>("pretrained_out_5_cast_fp16")]; |
| 87 | tensor<string, []> input_5_pad_type_0 = const()[name = tensor<string, []>("input_5_pad_type_0"), val = tensor<string, []>("valid")]; |
| 88 | tensor<int32, [2]> input_5_strides_0 = const()[name = tensor<string, []>("input_5_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 89 | tensor<int32, [4]> input_5_pad_0 = const()[name = tensor<string, []>("input_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 90 | tensor<int32, [2]> input_5_dilations_0 = const()[name = tensor<string, []>("input_5_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 91 | tensor<int32, []> input_5_groups_0 = const()[name = tensor<string, []>("input_5_groups_0"), val = tensor<int32, []>(1)]; |
| 92 | tensor<fp16, [16, 1280, 1, 1]> layers_0_self_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136562048)))]; |
| 93 | tensor<fp16, [1, 16, 1, 1]> input_5_cast_fp16 = conv(dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = layers_0_self_attn_v_proj_loraA_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")]; |
| 94 | tensor<string, []> lora_out_5_pad_type_0 = const()[name = tensor<string, []>("lora_out_5_pad_type_0"), val = tensor<string, []>("valid")]; |
| 95 | tensor<int32, [2]> lora_out_5_strides_0 = const()[name = tensor<string, []>("lora_out_5_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 96 | tensor<int32, [4]> lora_out_5_pad_0 = const()[name = tensor<string, []>("lora_out_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 97 | tensor<int32, [2]> lora_out_5_dilations_0 = const()[name = tensor<string, []>("lora_out_5_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 98 | tensor<int32, []> lora_out_5_groups_0 = const()[name = tensor<string, []>("lora_out_5_groups_0"), val = tensor<int32, []>(1)]; |
| 99 | tensor<fp16, [1280, 16, 1, 1]> layers_0_self_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136603072)))]; |
| 100 | tensor<fp16, [1, 1280, 1, 1]> lora_out_5_cast_fp16 = conv(dilations = lora_out_5_dilations_0, groups = lora_out_5_groups_0, pad = lora_out_5_pad_0, pad_type = lora_out_5_pad_type_0, strides = lora_out_5_strides_0, weight = layers_0_self_attn_v_proj_loraB_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("lora_out_5_cast_fp16")]; |
| 101 | tensor<fp16, [1, 1280, 1, 1]> current_value_1_cast_fp16 = add(x = pretrained_out_5_cast_fp16, y = lora_out_5_cast_fp16)[name = tensor<string, []>("current_value_1_cast_fp16")]; |
| 102 | tensor<int32, [1]> var_173_axes_0 = const()[name = tensor<string, []>("op_173_axes_0"), val = tensor<int32, [1]>([1])]; |
| 103 | tensor<fp16, [1, 1, 448]> var_173_cast_fp16 = expand_dims(axes = var_173_axes_0, x = kv_cache_update_mask)[name = tensor<string, []>("op_173_cast_fp16")]; |
| 104 | tensor<int32, [1]> var_174_axes_0 = const()[name = tensor<string, []>("op_174_axes_0"), val = tensor<int32, [1]>([2])]; |
| 105 | tensor<fp16, [1, 1, 1, 448]> var_174_cast_fp16 = expand_dims(axes = var_174_axes_0, x = var_173_cast_fp16)[name = tensor<string, []>("op_174_cast_fp16")]; |
| 106 | tensor<fp16, [1, 1280, 1, 448]> var_176_cast_fp16 = mul(x = current_key_1_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_176_cast_fp16")]; |
| 107 | tensor<fp16, []> var_65_to_fp16 = const()[name = tensor<string, []>("op_65_to_fp16"), val = tensor<fp16, []>(0x1p+0)]; |
| 108 | tensor<fp16, [1, 1, 1, 448]> var_177_cast_fp16 = sub(x = var_65_to_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_177_cast_fp16")]; |
| 109 | tensor<fp16, [1, 1280, 1, 448]> var_178_cast_fp16 = mul(x = var_47_cast_fp16_0, y = var_177_cast_fp16)[name = tensor<string, []>("op_178_cast_fp16")]; |
| 110 | tensor<fp16, [1, 1280, 1, 448]> key_1_cast_fp16 = add(x = var_176_cast_fp16, y = var_178_cast_fp16)[name = tensor<string, []>("key_1_cast_fp16")]; |
| 111 | tensor<fp16, [1, 1280, 1, 448]> var_180_cast_fp16 = mul(x = current_value_1_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_180_cast_fp16")]; |
| 112 | tensor<fp16, [1, 1280, 1, 448]> var_182_cast_fp16 = mul(x = var_54_cast_fp16_0, y = var_177_cast_fp16)[name = tensor<string, []>("op_182_cast_fp16")]; |
| 113 | tensor<fp16, [1, 1280, 1, 448]> value_1_cast_fp16 = add(x = var_180_cast_fp16, y = var_182_cast_fp16)[name = tensor<string, []>("value_1_cast_fp16")]; |
| 114 | tensor<int32, [4]> var_185 = const()[name = tensor<string, []>("op_185"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 115 | tensor<fp16, [1, 20, 64, 1]> mh_q_1_cast_fp16 = reshape(shape = var_185, x = query_1_cast_fp16)[name = tensor<string, []>("mh_q_1_cast_fp16")]; |
| 116 | tensor<fp16, []> var_187_to_fp16 = const()[name = tensor<string, []>("op_187_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 117 | tensor<fp16, [1, 20, 64, 1]> var_188_cast_fp16 = mul(x = mh_q_1_cast_fp16, y = var_187_to_fp16)[name = tensor<string, []>("op_188_cast_fp16")]; |
| 118 | tensor<int32, [4]> var_189 = const()[name = tensor<string, []>("op_189"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 119 | tensor<fp16, [1, 20, 64, 448]> var_190_cast_fp16 = reshape(shape = var_189, x = key_1_cast_fp16)[name = tensor<string, []>("op_190_cast_fp16")]; |
| 120 | tensor<bool, []> mh_w_1_transpose_x_0 = const()[name = tensor<string, []>("mh_w_1_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 121 | tensor<bool, []> mh_w_1_transpose_y_0 = const()[name = tensor<string, []>("mh_w_1_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 122 | tensor<fp16, [1, 20, 1, 448]> mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_188_cast_fp16, y = var_190_cast_fp16)[name = tensor<string, []>("mh_w_1_cast_fp16")]; |
| 123 | tensor<int32, [1]> var_194_axes_0 = const()[name = tensor<string, []>("op_194_axes_0"), val = tensor<int32, [1]>([1])]; |
| 124 | tensor<fp16, [1, 1, 448]> var_194_cast_fp16 = expand_dims(axes = var_194_axes_0, x = decoder_key_padding_mask)[name = tensor<string, []>("op_194_cast_fp16")]; |
| 125 | tensor<int32, [1]> var_195_axes_0 = const()[name = tensor<string, []>("op_195_axes_0"), val = tensor<int32, [1]>([2])]; |
| 126 | tensor<fp16, [1, 1, 1, 448]> var_195_cast_fp16 = expand_dims(axes = var_195_axes_0, x = var_194_cast_fp16)[name = tensor<string, []>("op_195_cast_fp16")]; |
| 127 | tensor<fp16, [1, 20, 1, 448]> mh_w_3_cast_fp16 = add(x = mh_w_1_cast_fp16, y = var_195_cast_fp16)[name = tensor<string, []>("mh_w_3_cast_fp16")]; |
| 128 | tensor<fp16, [1, 20, 1, 448]> var_198_cast_fp16 = softmax(axis = var_64, x = mh_w_3_cast_fp16)[name = tensor<string, []>("op_198_cast_fp16")]; |
| 129 | tensor<int32, [4]> var_199 = const()[name = tensor<string, []>("op_199"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 130 | tensor<fp16, [1, 20, 64, 448]> var_200_cast_fp16 = reshape(shape = var_199, x = value_1_cast_fp16)[name = tensor<string, []>("op_200_cast_fp16")]; |
| 131 | tensor<bool, []> attn_1_transpose_x_0 = const()[name = tensor<string, []>("attn_1_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 132 | tensor<bool, []> attn_1_transpose_y_0 = const()[name = tensor<string, []>("attn_1_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 133 | tensor<fp16, [1, 20, 64, 1]> attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_200_cast_fp16, y = var_198_cast_fp16)[name = tensor<string, []>("attn_1_cast_fp16")]; |
| 134 | tensor<int32, [4]> var_203 = const()[name = tensor<string, []>("op_203"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 135 | tensor<fp16, [1, 1280, 1, 1]> input_7_cast_fp16 = reshape(shape = var_203, x = attn_1_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")]; |
| 136 | tensor<string, []> pretrained_out_7_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_7_pad_type_0"), val = tensor<string, []>("valid")]; |
| 137 | tensor<int32, [2]> pretrained_out_7_strides_0 = const()[name = tensor<string, []>("pretrained_out_7_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 138 | tensor<int32, [4]> pretrained_out_7_pad_0 = const()[name = tensor<string, []>("pretrained_out_7_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 139 | tensor<int32, [2]> pretrained_out_7_dilations_0 = const()[name = tensor<string, []>("pretrained_out_7_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 140 | tensor<int32, []> pretrained_out_7_groups_0 = const()[name = tensor<string, []>("pretrained_out_7_groups_0"), val = tensor<int32, []>(1)]; |
| 141 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_self_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136644096))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137463360))), name = tensor<string, []>("layers_0_self_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 142 | tensor<fp16, [1280]> layers_0_self_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137463488)))]; |
| 143 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_7_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_7_dilations_0, groups = pretrained_out_7_groups_0, pad = pretrained_out_7_pad_0, pad_type = pretrained_out_7_pad_type_0, strides = pretrained_out_7_strides_0, weight = layers_0_self_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_7_cast_fp16)[name = tensor<string, []>("pretrained_out_7_cast_fp16")]; |
| 144 | tensor<string, []> input_9_pad_type_0 = const()[name = tensor<string, []>("input_9_pad_type_0"), val = tensor<string, []>("valid")]; |
| 145 | tensor<int32, [2]> input_9_strides_0 = const()[name = tensor<string, []>("input_9_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 146 | tensor<int32, [4]> input_9_pad_0 = const()[name = tensor<string, []>("input_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 147 | tensor<int32, [2]> input_9_dilations_0 = const()[name = tensor<string, []>("input_9_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 148 | tensor<int32, []> input_9_groups_0 = const()[name = tensor<string, []>("input_9_groups_0"), val = tensor<int32, []>(1)]; |
| 149 | tensor<fp16, [16, 1280, 1, 1]> layers_0_self_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137466112)))]; |
| 150 | tensor<fp16, [1, 16, 1, 1]> input_9_cast_fp16 = conv(dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = layers_0_self_attn_o_proj_loraA_weight_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")]; |
| 151 | tensor<string, []> lora_out_7_pad_type_0 = const()[name = tensor<string, []>("lora_out_7_pad_type_0"), val = tensor<string, []>("valid")]; |
| 152 | tensor<int32, [2]> lora_out_7_strides_0 = const()[name = tensor<string, []>("lora_out_7_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 153 | tensor<int32, [4]> lora_out_7_pad_0 = const()[name = tensor<string, []>("lora_out_7_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 154 | tensor<int32, [2]> lora_out_7_dilations_0 = const()[name = tensor<string, []>("lora_out_7_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 155 | tensor<int32, []> lora_out_7_groups_0 = const()[name = tensor<string, []>("lora_out_7_groups_0"), val = tensor<int32, []>(1)]; |
| 156 | tensor<fp16, [1280, 16, 1, 1]> layers_0_self_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_self_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137507136)))]; |
| 157 | tensor<fp16, [1, 1280, 1, 1]> lora_out_7_cast_fp16 = conv(dilations = lora_out_7_dilations_0, groups = lora_out_7_groups_0, pad = lora_out_7_pad_0, pad_type = lora_out_7_pad_type_0, strides = lora_out_7_strides_0, weight = layers_0_self_attn_o_proj_loraB_weight_to_fp16, x = input_9_cast_fp16)[name = tensor<string, []>("lora_out_7_cast_fp16")]; |
| 158 | tensor<fp16, [1, 1280, 1, 1]> obj_7_cast_fp16 = add(x = pretrained_out_7_cast_fp16, y = lora_out_7_cast_fp16)[name = tensor<string, []>("obj_7_cast_fp16")]; |
| 159 | tensor<fp16, [1, 1280, 1, 1]> inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_7_cast_fp16)[name = tensor<string, []>("inputs_3_cast_fp16")]; |
| 160 | tensor<int32, [1]> out_3_axes_0 = const()[name = tensor<string, []>("out_3_axes_0"), val = tensor<int32, [1]>([1])]; |
| 161 | tensor<fp16, []> var_241_to_fp16 = const()[name = tensor<string, []>("op_241_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 162 | tensor<fp16, [1, 1280, 1, 1]> out_3_cast_fp16 = layer_norm(axes = out_3_axes_0, epsilon = var_241_to_fp16, x = inputs_3_cast_fp16)[name = tensor<string, []>("out_3_cast_fp16")]; |
| 163 | tensor<fp16, [1280]> obj_9_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_9_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137548160)))]; |
| 164 | tensor<fp16, [1280]> obj_9_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_9_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137550784)))]; |
| 165 | tensor<fp16, []> obj_9_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_9_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 166 | tensor<fp16, [1, 1280, 1, 1]> obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor<string, []>("obj_9_cast_fp16")]; |
| 167 | tensor<string, []> pretrained_out_9_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_9_pad_type_0"), val = tensor<string, []>("valid")]; |
| 168 | tensor<int32, [2]> pretrained_out_9_strides_0 = const()[name = tensor<string, []>("pretrained_out_9_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 169 | tensor<int32, [4]> pretrained_out_9_pad_0 = const()[name = tensor<string, []>("pretrained_out_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 170 | tensor<int32, [2]> pretrained_out_9_dilations_0 = const()[name = tensor<string, []>("pretrained_out_9_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 171 | tensor<int32, []> pretrained_out_9_groups_0 = const()[name = tensor<string, []>("pretrained_out_9_groups_0"), val = tensor<int32, []>(1)]; |
| 172 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137553408))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138372672))), name = tensor<string, []>("layers_0_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 173 | tensor<fp16, [1280]> layers_0_encoder_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138372800)))]; |
| 174 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_9_cast_fp16 = conv(bias = layers_0_encoder_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_9_dilations_0, groups = pretrained_out_9_groups_0, pad = pretrained_out_9_pad_0, pad_type = pretrained_out_9_pad_type_0, strides = pretrained_out_9_strides_0, weight = layers_0_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_9_cast_fp16)[name = tensor<string, []>("pretrained_out_9_cast_fp16")]; |
| 175 | tensor<string, []> input_11_pad_type_0 = const()[name = tensor<string, []>("input_11_pad_type_0"), val = tensor<string, []>("valid")]; |
| 176 | tensor<int32, [2]> input_11_strides_0 = const()[name = tensor<string, []>("input_11_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 177 | tensor<int32, [4]> input_11_pad_0 = const()[name = tensor<string, []>("input_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 178 | tensor<int32, [2]> input_11_dilations_0 = const()[name = tensor<string, []>("input_11_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 179 | tensor<int32, []> input_11_groups_0 = const()[name = tensor<string, []>("input_11_groups_0"), val = tensor<int32, []>(1)]; |
| 180 | tensor<fp16, [16, 1280, 1, 1]> layers_0_encoder_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138375424)))]; |
| 181 | tensor<fp16, [1, 16, 1, 1]> input_11_cast_fp16 = conv(dilations = input_11_dilations_0, groups = input_11_groups_0, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = input_11_strides_0, weight = layers_0_encoder_attn_q_proj_loraA_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")]; |
| 182 | tensor<string, []> lora_out_9_pad_type_0 = const()[name = tensor<string, []>("lora_out_9_pad_type_0"), val = tensor<string, []>("valid")]; |
| 183 | tensor<int32, [2]> lora_out_9_strides_0 = const()[name = tensor<string, []>("lora_out_9_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 184 | tensor<int32, [4]> lora_out_9_pad_0 = const()[name = tensor<string, []>("lora_out_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 185 | tensor<int32, [2]> lora_out_9_dilations_0 = const()[name = tensor<string, []>("lora_out_9_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 186 | tensor<int32, []> lora_out_9_groups_0 = const()[name = tensor<string, []>("lora_out_9_groups_0"), val = tensor<int32, []>(1)]; |
| 187 | tensor<fp16, [1280, 16, 1, 1]> layers_0_encoder_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138416448)))]; |
| 188 | tensor<fp16, [1, 1280, 1, 1]> lora_out_9_cast_fp16 = conv(dilations = lora_out_9_dilations_0, groups = lora_out_9_groups_0, pad = lora_out_9_pad_0, pad_type = lora_out_9_pad_type_0, strides = lora_out_9_strides_0, weight = layers_0_encoder_attn_q_proj_loraB_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("lora_out_9_cast_fp16")]; |
| 189 | tensor<fp16, [1, 1280, 1, 1]> query_3_cast_fp16 = add(x = pretrained_out_9_cast_fp16, y = lora_out_9_cast_fp16)[name = tensor<string, []>("query_3_cast_fp16")]; |
| 190 | tensor<string, []> pretrained_out_11_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_11_pad_type_0"), val = tensor<string, []>("valid")]; |
| 191 | tensor<int32, [2]> pretrained_out_11_strides_0 = const()[name = tensor<string, []>("pretrained_out_11_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 192 | tensor<int32, [4]> pretrained_out_11_pad_0 = const()[name = tensor<string, []>("pretrained_out_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 193 | tensor<int32, [2]> pretrained_out_11_dilations_0 = const()[name = tensor<string, []>("pretrained_out_11_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 194 | tensor<int32, []> pretrained_out_11_groups_0 = const()[name = tensor<string, []>("pretrained_out_11_groups_0"), val = tensor<int32, []>(1)]; |
| 195 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138457472))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139276736))), name = tensor<string, []>("layers_0_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 196 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_11_cast_fp16 = conv(dilations = pretrained_out_11_dilations_0, groups = pretrained_out_11_groups_0, pad = pretrained_out_11_pad_0, pad_type = pretrained_out_11_pad_type_0, strides = pretrained_out_11_strides_0, weight = layers_0_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_11_cast_fp16")]; |
| 197 | tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("valid")]; |
| 198 | tensor<int32, [2]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 199 | tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 200 | tensor<int32, [2]> input_13_dilations_0 = const()[name = tensor<string, []>("input_13_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 201 | tensor<int32, []> input_13_groups_0 = const()[name = tensor<string, []>("input_13_groups_0"), val = tensor<int32, []>(1)]; |
| 202 | tensor<fp16, [16, 1280, 1, 1]> layers_0_encoder_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139276864)))]; |
| 203 | tensor<fp16, [1, 16, 1, 1500]> input_13_cast_fp16 = conv(dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = layers_0_encoder_attn_k_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_13_cast_fp16")]; |
| 204 | tensor<string, []> lora_out_11_pad_type_0 = const()[name = tensor<string, []>("lora_out_11_pad_type_0"), val = tensor<string, []>("valid")]; |
| 205 | tensor<int32, [2]> lora_out_11_strides_0 = const()[name = tensor<string, []>("lora_out_11_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 206 | tensor<int32, [4]> lora_out_11_pad_0 = const()[name = tensor<string, []>("lora_out_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 207 | tensor<int32, [2]> lora_out_11_dilations_0 = const()[name = tensor<string, []>("lora_out_11_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 208 | tensor<int32, []> lora_out_11_groups_0 = const()[name = tensor<string, []>("lora_out_11_groups_0"), val = tensor<int32, []>(1)]; |
| 209 | tensor<fp16, [1280, 16, 1, 1]> layers_0_encoder_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139317888)))]; |
| 210 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_11_cast_fp16 = conv(dilations = lora_out_11_dilations_0, groups = lora_out_11_groups_0, pad = lora_out_11_pad_0, pad_type = lora_out_11_pad_type_0, strides = lora_out_11_strides_0, weight = layers_0_encoder_attn_k_proj_loraB_weight_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("lora_out_11_cast_fp16")]; |
| 211 | tensor<fp16, [1, 1280, 1, 1500]> key_3_cast_fp16 = add(x = pretrained_out_11_cast_fp16, y = lora_out_11_cast_fp16)[name = tensor<string, []>("key_3_cast_fp16")]; |
| 212 | tensor<string, []> pretrained_out_13_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_13_pad_type_0"), val = tensor<string, []>("valid")]; |
| 213 | tensor<int32, [2]> pretrained_out_13_strides_0 = const()[name = tensor<string, []>("pretrained_out_13_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 214 | tensor<int32, [4]> pretrained_out_13_pad_0 = const()[name = tensor<string, []>("pretrained_out_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 215 | tensor<int32, [2]> pretrained_out_13_dilations_0 = const()[name = tensor<string, []>("pretrained_out_13_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 216 | tensor<int32, []> pretrained_out_13_groups_0 = const()[name = tensor<string, []>("pretrained_out_13_groups_0"), val = tensor<int32, []>(1)]; |
| 217 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139358912))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(140178176))), name = tensor<string, []>("layers_0_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 218 | tensor<fp16, [1280]> layers_0_encoder_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(140178304)))]; |
| 219 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_13_cast_fp16 = conv(bias = layers_0_encoder_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_13_dilations_0, groups = pretrained_out_13_groups_0, pad = pretrained_out_13_pad_0, pad_type = pretrained_out_13_pad_type_0, strides = pretrained_out_13_strides_0, weight = layers_0_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_13_cast_fp16")]; |
| 220 | tensor<string, []> input_15_pad_type_0 = const()[name = tensor<string, []>("input_15_pad_type_0"), val = tensor<string, []>("valid")]; |
| 221 | tensor<int32, [2]> input_15_strides_0 = const()[name = tensor<string, []>("input_15_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 222 | tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 223 | tensor<int32, [2]> input_15_dilations_0 = const()[name = tensor<string, []>("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 224 | tensor<int32, []> input_15_groups_0 = const()[name = tensor<string, []>("input_15_groups_0"), val = tensor<int32, []>(1)]; |
| 225 | tensor<fp16, [16, 1280, 1, 1]> layers_0_encoder_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(140180928)))]; |
| 226 | tensor<fp16, [1, 16, 1, 1500]> input_15_cast_fp16 = conv(dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = layers_0_encoder_attn_v_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_15_cast_fp16")]; |
| 227 | tensor<string, []> lora_out_13_pad_type_0 = const()[name = tensor<string, []>("lora_out_13_pad_type_0"), val = tensor<string, []>("valid")]; |
| 228 | tensor<int32, [2]> lora_out_13_strides_0 = const()[name = tensor<string, []>("lora_out_13_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 229 | tensor<int32, [4]> lora_out_13_pad_0 = const()[name = tensor<string, []>("lora_out_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 230 | tensor<int32, [2]> lora_out_13_dilations_0 = const()[name = tensor<string, []>("lora_out_13_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 231 | tensor<int32, []> lora_out_13_groups_0 = const()[name = tensor<string, []>("lora_out_13_groups_0"), val = tensor<int32, []>(1)]; |
| 232 | tensor<fp16, [1280, 16, 1, 1]> layers_0_encoder_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(140221952)))]; |
| 233 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_13_cast_fp16 = conv(dilations = lora_out_13_dilations_0, groups = lora_out_13_groups_0, pad = lora_out_13_pad_0, pad_type = lora_out_13_pad_type_0, strides = lora_out_13_strides_0, weight = layers_0_encoder_attn_v_proj_loraB_weight_to_fp16, x = input_15_cast_fp16)[name = tensor<string, []>("lora_out_13_cast_fp16")]; |
| 234 | tensor<fp16, [1, 1280, 1, 1500]> value_3_cast_fp16 = add(x = pretrained_out_13_cast_fp16, y = lora_out_13_cast_fp16)[name = tensor<string, []>("value_3_cast_fp16")]; |
| 235 | tensor<int32, [4]> var_324 = const()[name = tensor<string, []>("op_324"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 236 | tensor<fp16, [1, 20, 64, 1]> mh_q_3_cast_fp16 = reshape(shape = var_324, x = query_3_cast_fp16)[name = tensor<string, []>("mh_q_3_cast_fp16")]; |
| 237 | tensor<fp16, []> var_326_to_fp16 = const()[name = tensor<string, []>("op_326_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 238 | tensor<fp16, [1, 20, 64, 1]> var_327_cast_fp16 = mul(x = mh_q_3_cast_fp16, y = var_326_to_fp16)[name = tensor<string, []>("op_327_cast_fp16")]; |
| 239 | tensor<int32, [4]> var_328 = const()[name = tensor<string, []>("op_328"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 240 | tensor<fp16, [1, 20, 64, 1500]> var_329_cast_fp16 = reshape(shape = var_328, x = key_3_cast_fp16)[name = tensor<string, []>("op_329_cast_fp16")]; |
| 241 | tensor<bool, []> mh_w_5_transpose_x_0 = const()[name = tensor<string, []>("mh_w_5_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 242 | tensor<bool, []> mh_w_5_transpose_y_0 = const()[name = tensor<string, []>("mh_w_5_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 243 | tensor<fp16, [1, 20, 1, 1500]> mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_327_cast_fp16, y = var_329_cast_fp16)[name = tensor<string, []>("mh_w_5_cast_fp16")]; |
| 244 | tensor<fp16, [1, 20, 1, 1500]> obj_13_cast_fp16 = softmax(axis = var_64, x = mh_w_5_cast_fp16)[name = tensor<string, []>("obj_13_cast_fp16")]; |
| 245 | tensor<int32, [4]> var_333 = const()[name = tensor<string, []>("op_333"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 246 | tensor<fp16, [1, 20, 64, 1500]> var_334_cast_fp16 = reshape(shape = var_333, x = value_3_cast_fp16)[name = tensor<string, []>("op_334_cast_fp16")]; |
| 247 | tensor<bool, []> attn_3_transpose_x_0 = const()[name = tensor<string, []>("attn_3_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 248 | tensor<bool, []> attn_3_transpose_y_0 = const()[name = tensor<string, []>("attn_3_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 249 | tensor<fp16, [1, 20, 64, 1]> attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_334_cast_fp16, y = obj_13_cast_fp16)[name = tensor<string, []>("attn_3_cast_fp16")]; |
| 250 | tensor<int32, [4]> var_337 = const()[name = tensor<string, []>("op_337"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 251 | tensor<fp16, [1, 1280, 1, 1]> input_17_cast_fp16 = reshape(shape = var_337, x = attn_3_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")]; |
| 252 | tensor<string, []> pretrained_out_15_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_15_pad_type_0"), val = tensor<string, []>("valid")]; |
| 253 | tensor<int32, [2]> pretrained_out_15_strides_0 = const()[name = tensor<string, []>("pretrained_out_15_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 254 | tensor<int32, [4]> pretrained_out_15_pad_0 = const()[name = tensor<string, []>("pretrained_out_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 255 | tensor<int32, [2]> pretrained_out_15_dilations_0 = const()[name = tensor<string, []>("pretrained_out_15_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 256 | tensor<int32, []> pretrained_out_15_groups_0 = const()[name = tensor<string, []>("pretrained_out_15_groups_0"), val = tensor<int32, []>(1)]; |
| 257 | tensor<fp16, [1280, 1280, 1, 1]> layers_0_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(140262976))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141082240))), name = tensor<string, []>("layers_0_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 258 | tensor<fp16, [1280]> layers_0_encoder_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141082368)))]; |
| 259 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_15_cast_fp16 = conv(bias = layers_0_encoder_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_15_dilations_0, groups = pretrained_out_15_groups_0, pad = pretrained_out_15_pad_0, pad_type = pretrained_out_15_pad_type_0, strides = pretrained_out_15_strides_0, weight = layers_0_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor<string, []>("pretrained_out_15_cast_fp16")]; |
| 260 | tensor<string, []> input_19_pad_type_0 = const()[name = tensor<string, []>("input_19_pad_type_0"), val = tensor<string, []>("valid")]; |
| 261 | tensor<int32, [2]> input_19_strides_0 = const()[name = tensor<string, []>("input_19_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 262 | tensor<int32, [4]> input_19_pad_0 = const()[name = tensor<string, []>("input_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 263 | tensor<int32, [2]> input_19_dilations_0 = const()[name = tensor<string, []>("input_19_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 264 | tensor<int32, []> input_19_groups_0 = const()[name = tensor<string, []>("input_19_groups_0"), val = tensor<int32, []>(1)]; |
| 265 | tensor<fp16, [16, 1280, 1, 1]> layers_0_encoder_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141084992)))]; |
| 266 | tensor<fp16, [1, 16, 1, 1]> input_19_cast_fp16 = conv(dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = layers_0_encoder_attn_o_proj_loraA_weight_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")]; |
| 267 | tensor<string, []> lora_out_15_pad_type_0 = const()[name = tensor<string, []>("lora_out_15_pad_type_0"), val = tensor<string, []>("valid")]; |
| 268 | tensor<int32, [2]> lora_out_15_strides_0 = const()[name = tensor<string, []>("lora_out_15_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 269 | tensor<int32, [4]> lora_out_15_pad_0 = const()[name = tensor<string, []>("lora_out_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 270 | tensor<int32, [2]> lora_out_15_dilations_0 = const()[name = tensor<string, []>("lora_out_15_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 271 | tensor<int32, []> lora_out_15_groups_0 = const()[name = tensor<string, []>("lora_out_15_groups_0"), val = tensor<int32, []>(1)]; |
| 272 | tensor<fp16, [1280, 16, 1, 1]> layers_0_encoder_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_encoder_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141126016)))]; |
| 273 | tensor<fp16, [1, 1280, 1, 1]> lora_out_15_cast_fp16 = conv(dilations = lora_out_15_dilations_0, groups = lora_out_15_groups_0, pad = lora_out_15_pad_0, pad_type = lora_out_15_pad_type_0, strides = lora_out_15_strides_0, weight = layers_0_encoder_attn_o_proj_loraB_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("lora_out_15_cast_fp16")]; |
| 274 | tensor<fp16, [1, 1280, 1, 1]> obj_11_cast_fp16 = add(x = pretrained_out_15_cast_fp16, y = lora_out_15_cast_fp16)[name = tensor<string, []>("obj_11_cast_fp16")]; |
| 275 | tensor<fp16, [1, 1280, 1, 1]> inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = obj_11_cast_fp16)[name = tensor<string, []>("inputs_5_cast_fp16")]; |
| 276 | tensor<int32, [1]> out_5_axes_0 = const()[name = tensor<string, []>("out_5_axes_0"), val = tensor<int32, [1]>([1])]; |
| 277 | tensor<fp16, []> var_371_to_fp16 = const()[name = tensor<string, []>("op_371_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 278 | tensor<fp16, [1, 1280, 1, 1]> out_5_cast_fp16 = layer_norm(axes = out_5_axes_0, epsilon = var_371_to_fp16, x = inputs_5_cast_fp16)[name = tensor<string, []>("out_5_cast_fp16")]; |
| 279 | tensor<fp16, [1280]> input_21_gamma_0_to_fp16 = const()[name = tensor<string, []>("input_21_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141167040)))]; |
| 280 | tensor<fp16, [1280]> input_21_beta_0_to_fp16 = const()[name = tensor<string, []>("input_21_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141169664)))]; |
| 281 | tensor<fp16, []> input_21_epsilon_0_to_fp16 = const()[name = tensor<string, []>("input_21_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 282 | tensor<fp16, [1, 1280, 1, 1]> input_21_cast_fp16 = batch_norm(beta = input_21_beta_0_to_fp16, epsilon = input_21_epsilon_0_to_fp16, gamma = input_21_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")]; |
| 283 | tensor<string, []> pretrained_out_17_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_17_pad_type_0"), val = tensor<string, []>("valid")]; |
| 284 | tensor<int32, [2]> pretrained_out_17_strides_0 = const()[name = tensor<string, []>("pretrained_out_17_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 285 | tensor<int32, [4]> pretrained_out_17_pad_0 = const()[name = tensor<string, []>("pretrained_out_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 286 | tensor<int32, [2]> pretrained_out_17_dilations_0 = const()[name = tensor<string, []>("pretrained_out_17_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 287 | tensor<int32, []> pretrained_out_17_groups_0 = const()[name = tensor<string, []>("pretrained_out_17_groups_0"), val = tensor<int32, []>(1)]; |
| 288 | tensor<fp16, [5120, 1280, 1, 1]> layers_0_fc1_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141172288))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144449152))), name = tensor<string, []>("layers_0_fc1_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([5120, 1280, 1, 1])]; |
| 289 | tensor<fp16, [5120]> layers_0_fc1_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_fc1_pretrained_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144449280)))]; |
| 290 | tensor<fp16, [1, 5120, 1, 1]> pretrained_out_17_cast_fp16 = conv(bias = layers_0_fc1_pretrained_bias_to_fp16, dilations = pretrained_out_17_dilations_0, groups = pretrained_out_17_groups_0, pad = pretrained_out_17_pad_0, pad_type = pretrained_out_17_pad_type_0, strides = pretrained_out_17_strides_0, weight = layers_0_fc1_pretrained_weight_to_fp16_palettized, x = input_21_cast_fp16)[name = tensor<string, []>("pretrained_out_17_cast_fp16")]; |
| 291 | tensor<string, []> input_23_pad_type_0 = const()[name = tensor<string, []>("input_23_pad_type_0"), val = tensor<string, []>("valid")]; |
| 292 | tensor<int32, [2]> input_23_strides_0 = const()[name = tensor<string, []>("input_23_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 293 | tensor<int32, [4]> input_23_pad_0 = const()[name = tensor<string, []>("input_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 294 | tensor<int32, [2]> input_23_dilations_0 = const()[name = tensor<string, []>("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 295 | tensor<int32, []> input_23_groups_0 = const()[name = tensor<string, []>("input_23_groups_0"), val = tensor<int32, []>(1)]; |
| 296 | tensor<fp16, [16, 1280, 1, 1]> layers_0_fc1_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_fc1_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144459584)))]; |
| 297 | tensor<fp16, [1, 16, 1, 1]> input_23_cast_fp16 = conv(dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = layers_0_fc1_loraA_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")]; |
| 298 | tensor<string, []> lora_out_17_pad_type_0 = const()[name = tensor<string, []>("lora_out_17_pad_type_0"), val = tensor<string, []>("valid")]; |
| 299 | tensor<int32, [2]> lora_out_17_strides_0 = const()[name = tensor<string, []>("lora_out_17_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 300 | tensor<int32, [4]> lora_out_17_pad_0 = const()[name = tensor<string, []>("lora_out_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 301 | tensor<int32, [2]> lora_out_17_dilations_0 = const()[name = tensor<string, []>("lora_out_17_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 302 | tensor<int32, []> lora_out_17_groups_0 = const()[name = tensor<string, []>("lora_out_17_groups_0"), val = tensor<int32, []>(1)]; |
| 303 | tensor<fp16, [5120, 16, 1, 1]> layers_0_fc1_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_fc1_loraB_weight_to_fp16"), val = tensor<fp16, [5120, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144500608)))]; |
| 304 | tensor<fp16, [1, 5120, 1, 1]> lora_out_17_cast_fp16 = conv(dilations = lora_out_17_dilations_0, groups = lora_out_17_groups_0, pad = lora_out_17_pad_0, pad_type = lora_out_17_pad_type_0, strides = lora_out_17_strides_0, weight = layers_0_fc1_loraB_weight_to_fp16, x = input_23_cast_fp16)[name = tensor<string, []>("lora_out_17_cast_fp16")]; |
| 305 | tensor<fp16, [1, 5120, 1, 1]> input_25_cast_fp16 = add(x = pretrained_out_17_cast_fp16, y = lora_out_17_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")]; |
| 306 | tensor<string, []> input_27_mode_0 = const()[name = tensor<string, []>("input_27_mode_0"), val = tensor<string, []>("EXACT")]; |
| 307 | tensor<fp16, [1, 5120, 1, 1]> input_27_cast_fp16 = gelu(mode = input_27_mode_0, x = input_25_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")]; |
| 308 | tensor<string, []> pretrained_out_19_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_19_pad_type_0"), val = tensor<string, []>("valid")]; |
| 309 | tensor<int32, [2]> pretrained_out_19_strides_0 = const()[name = tensor<string, []>("pretrained_out_19_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 310 | tensor<int32, [4]> pretrained_out_19_pad_0 = const()[name = tensor<string, []>("pretrained_out_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 311 | tensor<int32, [2]> pretrained_out_19_dilations_0 = const()[name = tensor<string, []>("pretrained_out_19_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 312 | tensor<int32, []> pretrained_out_19_groups_0 = const()[name = tensor<string, []>("pretrained_out_19_groups_0"), val = tensor<int32, []>(1)]; |
| 313 | tensor<fp16, [1280, 5120, 1, 1]> layers_0_fc2_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144664512))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147941376))), name = tensor<string, []>("layers_0_fc2_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 5120, 1, 1])]; |
| 314 | tensor<fp16, [1280]> layers_0_fc2_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_0_fc2_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147941504)))]; |
| 315 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_19_cast_fp16 = conv(bias = layers_0_fc2_pretrained_bias_to_fp16, dilations = pretrained_out_19_dilations_0, groups = pretrained_out_19_groups_0, pad = pretrained_out_19_pad_0, pad_type = pretrained_out_19_pad_type_0, strides = pretrained_out_19_strides_0, weight = layers_0_fc2_pretrained_weight_to_fp16_palettized, x = input_27_cast_fp16)[name = tensor<string, []>("pretrained_out_19_cast_fp16")]; |
| 316 | tensor<string, []> input_29_pad_type_0 = const()[name = tensor<string, []>("input_29_pad_type_0"), val = tensor<string, []>("valid")]; |
| 317 | tensor<int32, [2]> input_29_strides_0 = const()[name = tensor<string, []>("input_29_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 318 | tensor<int32, [4]> input_29_pad_0 = const()[name = tensor<string, []>("input_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 319 | tensor<int32, [2]> input_29_dilations_0 = const()[name = tensor<string, []>("input_29_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 320 | tensor<int32, []> input_29_groups_0 = const()[name = tensor<string, []>("input_29_groups_0"), val = tensor<int32, []>(1)]; |
| 321 | tensor<fp16, [16, 5120, 1, 1]> layers_0_fc2_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_fc2_loraA_weight_to_fp16"), val = tensor<fp16, [16, 5120, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147944128)))]; |
| 322 | tensor<fp16, [1, 16, 1, 1]> input_29_cast_fp16 = conv(dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = layers_0_fc2_loraA_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")]; |
| 323 | tensor<string, []> lora_out_19_pad_type_0 = const()[name = tensor<string, []>("lora_out_19_pad_type_0"), val = tensor<string, []>("valid")]; |
| 324 | tensor<int32, [2]> lora_out_19_strides_0 = const()[name = tensor<string, []>("lora_out_19_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 325 | tensor<int32, [4]> lora_out_19_pad_0 = const()[name = tensor<string, []>("lora_out_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 326 | tensor<int32, [2]> lora_out_19_dilations_0 = const()[name = tensor<string, []>("lora_out_19_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 327 | tensor<int32, []> lora_out_19_groups_0 = const()[name = tensor<string, []>("lora_out_19_groups_0"), val = tensor<int32, []>(1)]; |
| 328 | tensor<fp16, [1280, 16, 1, 1]> layers_0_fc2_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_0_fc2_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148108032)))]; |
| 329 | tensor<fp16, [1, 1280, 1, 1]> lora_out_19_cast_fp16 = conv(dilations = lora_out_19_dilations_0, groups = lora_out_19_groups_0, pad = lora_out_19_pad_0, pad_type = lora_out_19_pad_type_0, strides = lora_out_19_strides_0, weight = layers_0_fc2_loraB_weight_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("lora_out_19_cast_fp16")]; |
| 330 | tensor<fp16, [1, 1280, 1, 1]> hidden_states_3_cast_fp16 = add(x = pretrained_out_19_cast_fp16, y = lora_out_19_cast_fp16)[name = tensor<string, []>("hidden_states_3_cast_fp16")]; |
| 331 | tensor<fp16, [1, 1280, 1, 1]> inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = hidden_states_3_cast_fp16)[name = tensor<string, []>("inputs_7_cast_fp16")]; |
| 332 | tensor<int32, []> var_438 = const()[name = tensor<string, []>("op_438"), val = tensor<int32, []>(3)]; |
| 333 | tensor<int32, [1]> out_7_axes_0 = const()[name = tensor<string, []>("out_7_axes_0"), val = tensor<int32, [1]>([1])]; |
| 334 | tensor<fp16, []> var_464_to_fp16 = const()[name = tensor<string, []>("op_464_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 335 | tensor<fp16, [1, 1280, 1, 1]> out_7_cast_fp16 = layer_norm(axes = out_7_axes_0, epsilon = var_464_to_fp16, x = inputs_7_cast_fp16)[name = tensor<string, []>("out_7_cast_fp16")]; |
| 336 | tensor<fp16, [1280]> obj_15_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_15_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148149056)))]; |
| 337 | tensor<fp16, [1280]> obj_15_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_15_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148151680)))]; |
| 338 | tensor<fp16, []> obj_15_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_15_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 339 | tensor<fp16, [1, 1280, 1, 1]> obj_15_cast_fp16 = batch_norm(beta = obj_15_beta_0_to_fp16, epsilon = obj_15_epsilon_0_to_fp16, gamma = obj_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor<string, []>("obj_15_cast_fp16")]; |
| 340 | tensor<string, []> pretrained_out_21_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_21_pad_type_0"), val = tensor<string, []>("valid")]; |
| 341 | tensor<int32, [2]> pretrained_out_21_strides_0 = const()[name = tensor<string, []>("pretrained_out_21_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 342 | tensor<int32, [4]> pretrained_out_21_pad_0 = const()[name = tensor<string, []>("pretrained_out_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 343 | tensor<int32, [2]> pretrained_out_21_dilations_0 = const()[name = tensor<string, []>("pretrained_out_21_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 344 | tensor<int32, []> pretrained_out_21_groups_0 = const()[name = tensor<string, []>("pretrained_out_21_groups_0"), val = tensor<int32, []>(1)]; |
| 345 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_self_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148154304))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148973568))), name = tensor<string, []>("layers_1_self_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 346 | tensor<fp16, [1280]> layers_1_self_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148973696)))]; |
| 347 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_21_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_21_dilations_0, groups = pretrained_out_21_groups_0, pad = pretrained_out_21_pad_0, pad_type = pretrained_out_21_pad_type_0, strides = pretrained_out_21_strides_0, weight = layers_1_self_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_15_cast_fp16)[name = tensor<string, []>("pretrained_out_21_cast_fp16")]; |
| 348 | tensor<string, []> input_31_pad_type_0 = const()[name = tensor<string, []>("input_31_pad_type_0"), val = tensor<string, []>("valid")]; |
| 349 | tensor<int32, [2]> input_31_strides_0 = const()[name = tensor<string, []>("input_31_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 350 | tensor<int32, [4]> input_31_pad_0 = const()[name = tensor<string, []>("input_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 351 | tensor<int32, [2]> input_31_dilations_0 = const()[name = tensor<string, []>("input_31_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 352 | tensor<int32, []> input_31_groups_0 = const()[name = tensor<string, []>("input_31_groups_0"), val = tensor<int32, []>(1)]; |
| 353 | tensor<fp16, [16, 1280, 1, 1]> layers_1_self_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148976320)))]; |
| 354 | tensor<fp16, [1, 16, 1, 1]> input_31_cast_fp16 = conv(dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = layers_1_self_attn_q_proj_loraA_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")]; |
| 355 | tensor<string, []> lora_out_21_pad_type_0 = const()[name = tensor<string, []>("lora_out_21_pad_type_0"), val = tensor<string, []>("valid")]; |
| 356 | tensor<int32, [2]> lora_out_21_strides_0 = const()[name = tensor<string, []>("lora_out_21_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 357 | tensor<int32, [4]> lora_out_21_pad_0 = const()[name = tensor<string, []>("lora_out_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 358 | tensor<int32, [2]> lora_out_21_dilations_0 = const()[name = tensor<string, []>("lora_out_21_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 359 | tensor<int32, []> lora_out_21_groups_0 = const()[name = tensor<string, []>("lora_out_21_groups_0"), val = tensor<int32, []>(1)]; |
| 360 | tensor<fp16, [1280, 16, 1, 1]> layers_1_self_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149017344)))]; |
| 361 | tensor<fp16, [1, 1280, 1, 1]> lora_out_21_cast_fp16 = conv(dilations = lora_out_21_dilations_0, groups = lora_out_21_groups_0, pad = lora_out_21_pad_0, pad_type = lora_out_21_pad_type_0, strides = lora_out_21_strides_0, weight = layers_1_self_attn_q_proj_loraB_weight_to_fp16, x = input_31_cast_fp16)[name = tensor<string, []>("lora_out_21_cast_fp16")]; |
| 362 | tensor<fp16, [1, 1280, 1, 1]> query_5_cast_fp16 = add(x = pretrained_out_21_cast_fp16, y = lora_out_21_cast_fp16)[name = tensor<string, []>("query_5_cast_fp16")]; |
| 363 | tensor<string, []> pretrained_out_23_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_23_pad_type_0"), val = tensor<string, []>("valid")]; |
| 364 | tensor<int32, [2]> pretrained_out_23_strides_0 = const()[name = tensor<string, []>("pretrained_out_23_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 365 | tensor<int32, [4]> pretrained_out_23_pad_0 = const()[name = tensor<string, []>("pretrained_out_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 366 | tensor<int32, [2]> pretrained_out_23_dilations_0 = const()[name = tensor<string, []>("pretrained_out_23_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 367 | tensor<int32, []> pretrained_out_23_groups_0 = const()[name = tensor<string, []>("pretrained_out_23_groups_0"), val = tensor<int32, []>(1)]; |
| 368 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_self_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149058368))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149877632))), name = tensor<string, []>("layers_1_self_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 369 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_23_cast_fp16 = conv(dilations = pretrained_out_23_dilations_0, groups = pretrained_out_23_groups_0, pad = pretrained_out_23_pad_0, pad_type = pretrained_out_23_pad_type_0, strides = pretrained_out_23_strides_0, weight = layers_1_self_attn_k_proj_pretrained_weight_to_fp16_palettized, x = obj_15_cast_fp16)[name = tensor<string, []>("pretrained_out_23_cast_fp16")]; |
| 370 | tensor<string, []> input_33_pad_type_0 = const()[name = tensor<string, []>("input_33_pad_type_0"), val = tensor<string, []>("valid")]; |
| 371 | tensor<int32, [2]> input_33_strides_0 = const()[name = tensor<string, []>("input_33_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 372 | tensor<int32, [4]> input_33_pad_0 = const()[name = tensor<string, []>("input_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 373 | tensor<int32, [2]> input_33_dilations_0 = const()[name = tensor<string, []>("input_33_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 374 | tensor<int32, []> input_33_groups_0 = const()[name = tensor<string, []>("input_33_groups_0"), val = tensor<int32, []>(1)]; |
| 375 | tensor<fp16, [16, 1280, 1, 1]> layers_1_self_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149877760)))]; |
| 376 | tensor<fp16, [1, 16, 1, 1]> input_33_cast_fp16 = conv(dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = layers_1_self_attn_k_proj_loraA_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")]; |
| 377 | tensor<string, []> lora_out_23_pad_type_0 = const()[name = tensor<string, []>("lora_out_23_pad_type_0"), val = tensor<string, []>("valid")]; |
| 378 | tensor<int32, [2]> lora_out_23_strides_0 = const()[name = tensor<string, []>("lora_out_23_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 379 | tensor<int32, [4]> lora_out_23_pad_0 = const()[name = tensor<string, []>("lora_out_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 380 | tensor<int32, [2]> lora_out_23_dilations_0 = const()[name = tensor<string, []>("lora_out_23_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 381 | tensor<int32, []> lora_out_23_groups_0 = const()[name = tensor<string, []>("lora_out_23_groups_0"), val = tensor<int32, []>(1)]; |
| 382 | tensor<fp16, [1280, 16, 1, 1]> layers_1_self_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149918784)))]; |
| 383 | tensor<fp16, [1, 1280, 1, 1]> lora_out_23_cast_fp16 = conv(dilations = lora_out_23_dilations_0, groups = lora_out_23_groups_0, pad = lora_out_23_pad_0, pad_type = lora_out_23_pad_type_0, strides = lora_out_23_strides_0, weight = layers_1_self_attn_k_proj_loraB_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("lora_out_23_cast_fp16")]; |
| 384 | tensor<fp16, [1, 1280, 1, 1]> current_key_3_cast_fp16 = add(x = pretrained_out_23_cast_fp16, y = lora_out_23_cast_fp16)[name = tensor<string, []>("current_key_3_cast_fp16")]; |
| 385 | tensor<string, []> pretrained_out_25_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_25_pad_type_0"), val = tensor<string, []>("valid")]; |
| 386 | tensor<int32, [2]> pretrained_out_25_strides_0 = const()[name = tensor<string, []>("pretrained_out_25_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 387 | tensor<int32, [4]> pretrained_out_25_pad_0 = const()[name = tensor<string, []>("pretrained_out_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 388 | tensor<int32, [2]> pretrained_out_25_dilations_0 = const()[name = tensor<string, []>("pretrained_out_25_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 389 | tensor<int32, []> pretrained_out_25_groups_0 = const()[name = tensor<string, []>("pretrained_out_25_groups_0"), val = tensor<int32, []>(1)]; |
| 390 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_self_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149959808))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150779072))), name = tensor<string, []>("layers_1_self_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 391 | tensor<fp16, [1280]> layers_1_self_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150779200)))]; |
| 392 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_25_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_25_dilations_0, groups = pretrained_out_25_groups_0, pad = pretrained_out_25_pad_0, pad_type = pretrained_out_25_pad_type_0, strides = pretrained_out_25_strides_0, weight = layers_1_self_attn_v_proj_pretrained_weight_to_fp16_palettized, x = obj_15_cast_fp16)[name = tensor<string, []>("pretrained_out_25_cast_fp16")]; |
| 393 | tensor<string, []> input_35_pad_type_0 = const()[name = tensor<string, []>("input_35_pad_type_0"), val = tensor<string, []>("valid")]; |
| 394 | tensor<int32, [2]> input_35_strides_0 = const()[name = tensor<string, []>("input_35_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 395 | tensor<int32, [4]> input_35_pad_0 = const()[name = tensor<string, []>("input_35_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 396 | tensor<int32, [2]> input_35_dilations_0 = const()[name = tensor<string, []>("input_35_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 397 | tensor<int32, []> input_35_groups_0 = const()[name = tensor<string, []>("input_35_groups_0"), val = tensor<int32, []>(1)]; |
| 398 | tensor<fp16, [16, 1280, 1, 1]> layers_1_self_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150781824)))]; |
| 399 | tensor<fp16, [1, 16, 1, 1]> input_35_cast_fp16 = conv(dilations = input_35_dilations_0, groups = input_35_groups_0, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = input_35_strides_0, weight = layers_1_self_attn_v_proj_loraA_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")]; |
| 400 | tensor<string, []> lora_out_25_pad_type_0 = const()[name = tensor<string, []>("lora_out_25_pad_type_0"), val = tensor<string, []>("valid")]; |
| 401 | tensor<int32, [2]> lora_out_25_strides_0 = const()[name = tensor<string, []>("lora_out_25_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 402 | tensor<int32, [4]> lora_out_25_pad_0 = const()[name = tensor<string, []>("lora_out_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 403 | tensor<int32, [2]> lora_out_25_dilations_0 = const()[name = tensor<string, []>("lora_out_25_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 404 | tensor<int32, []> lora_out_25_groups_0 = const()[name = tensor<string, []>("lora_out_25_groups_0"), val = tensor<int32, []>(1)]; |
| 405 | tensor<fp16, [1280, 16, 1, 1]> layers_1_self_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150822848)))]; |
| 406 | tensor<fp16, [1, 1280, 1, 1]> lora_out_25_cast_fp16 = conv(dilations = lora_out_25_dilations_0, groups = lora_out_25_groups_0, pad = lora_out_25_pad_0, pad_type = lora_out_25_pad_type_0, strides = lora_out_25_strides_0, weight = layers_1_self_attn_v_proj_loraB_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("lora_out_25_cast_fp16")]; |
| 407 | tensor<fp16, [1, 1280, 1, 1]> current_value_3_cast_fp16 = add(x = pretrained_out_25_cast_fp16, y = lora_out_25_cast_fp16)[name = tensor<string, []>("current_value_3_cast_fp16")]; |
| 408 | tensor<fp16, [1, 1280, 1, 448]> var_550_cast_fp16 = mul(x = current_key_3_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_550_cast_fp16")]; |
| 409 | tensor<fp16, [1, 1280, 1, 448]> var_552_cast_fp16 = mul(x = var_47_cast_fp16_1, y = var_177_cast_fp16)[name = tensor<string, []>("op_552_cast_fp16")]; |
| 410 | tensor<fp16, [1, 1280, 1, 448]> key_5_cast_fp16 = add(x = var_550_cast_fp16, y = var_552_cast_fp16)[name = tensor<string, []>("key_5_cast_fp16")]; |
| 411 | tensor<fp16, [1, 1280, 1, 448]> var_554_cast_fp16 = mul(x = current_value_3_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_554_cast_fp16")]; |
| 412 | tensor<fp16, [1, 1280, 1, 448]> var_556_cast_fp16 = mul(x = var_54_cast_fp16_1, y = var_177_cast_fp16)[name = tensor<string, []>("op_556_cast_fp16")]; |
| 413 | tensor<fp16, [1, 1280, 1, 448]> value_5_cast_fp16 = add(x = var_554_cast_fp16, y = var_556_cast_fp16)[name = tensor<string, []>("value_5_cast_fp16")]; |
| 414 | tensor<int32, [4]> var_559 = const()[name = tensor<string, []>("op_559"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 415 | tensor<fp16, [1, 20, 64, 1]> mh_q_5_cast_fp16 = reshape(shape = var_559, x = query_5_cast_fp16)[name = tensor<string, []>("mh_q_5_cast_fp16")]; |
| 416 | tensor<fp16, []> var_561_to_fp16 = const()[name = tensor<string, []>("op_561_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 417 | tensor<fp16, [1, 20, 64, 1]> var_562_cast_fp16 = mul(x = mh_q_5_cast_fp16, y = var_561_to_fp16)[name = tensor<string, []>("op_562_cast_fp16")]; |
| 418 | tensor<int32, [4]> var_563 = const()[name = tensor<string, []>("op_563"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 419 | tensor<fp16, [1, 20, 64, 448]> var_564_cast_fp16 = reshape(shape = var_563, x = key_5_cast_fp16)[name = tensor<string, []>("op_564_cast_fp16")]; |
| 420 | tensor<bool, []> mh_w_7_transpose_x_0 = const()[name = tensor<string, []>("mh_w_7_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 421 | tensor<bool, []> mh_w_7_transpose_y_0 = const()[name = tensor<string, []>("mh_w_7_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 422 | tensor<fp16, [1, 20, 1, 448]> mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_562_cast_fp16, y = var_564_cast_fp16)[name = tensor<string, []>("mh_w_7_cast_fp16")]; |
| 423 | tensor<fp16, [1, 20, 1, 448]> mh_w_9_cast_fp16 = add(x = mh_w_7_cast_fp16, y = var_195_cast_fp16)[name = tensor<string, []>("mh_w_9_cast_fp16")]; |
| 424 | tensor<fp16, [1, 20, 1, 448]> var_572_cast_fp16 = softmax(axis = var_438, x = mh_w_9_cast_fp16)[name = tensor<string, []>("op_572_cast_fp16")]; |
| 425 | tensor<int32, [4]> var_573 = const()[name = tensor<string, []>("op_573"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 426 | tensor<fp16, [1, 20, 64, 448]> var_574_cast_fp16 = reshape(shape = var_573, x = value_5_cast_fp16)[name = tensor<string, []>("op_574_cast_fp16")]; |
| 427 | tensor<bool, []> attn_5_transpose_x_0 = const()[name = tensor<string, []>("attn_5_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 428 | tensor<bool, []> attn_5_transpose_y_0 = const()[name = tensor<string, []>("attn_5_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 429 | tensor<fp16, [1, 20, 64, 1]> attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_574_cast_fp16, y = var_572_cast_fp16)[name = tensor<string, []>("attn_5_cast_fp16")]; |
| 430 | tensor<int32, [4]> var_577 = const()[name = tensor<string, []>("op_577"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 431 | tensor<fp16, [1, 1280, 1, 1]> input_37_cast_fp16 = reshape(shape = var_577, x = attn_5_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")]; |
| 432 | tensor<string, []> pretrained_out_27_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_27_pad_type_0"), val = tensor<string, []>("valid")]; |
| 433 | tensor<int32, [2]> pretrained_out_27_strides_0 = const()[name = tensor<string, []>("pretrained_out_27_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 434 | tensor<int32, [4]> pretrained_out_27_pad_0 = const()[name = tensor<string, []>("pretrained_out_27_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 435 | tensor<int32, [2]> pretrained_out_27_dilations_0 = const()[name = tensor<string, []>("pretrained_out_27_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 436 | tensor<int32, []> pretrained_out_27_groups_0 = const()[name = tensor<string, []>("pretrained_out_27_groups_0"), val = tensor<int32, []>(1)]; |
| 437 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_self_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150863872))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151683136))), name = tensor<string, []>("layers_1_self_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 438 | tensor<fp16, [1280]> layers_1_self_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151683264)))]; |
| 439 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_27_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_27_dilations_0, groups = pretrained_out_27_groups_0, pad = pretrained_out_27_pad_0, pad_type = pretrained_out_27_pad_type_0, strides = pretrained_out_27_strides_0, weight = layers_1_self_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_37_cast_fp16)[name = tensor<string, []>("pretrained_out_27_cast_fp16")]; |
| 440 | tensor<string, []> input_39_pad_type_0 = const()[name = tensor<string, []>("input_39_pad_type_0"), val = tensor<string, []>("valid")]; |
| 441 | tensor<int32, [2]> input_39_strides_0 = const()[name = tensor<string, []>("input_39_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 442 | tensor<int32, [4]> input_39_pad_0 = const()[name = tensor<string, []>("input_39_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 443 | tensor<int32, [2]> input_39_dilations_0 = const()[name = tensor<string, []>("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 444 | tensor<int32, []> input_39_groups_0 = const()[name = tensor<string, []>("input_39_groups_0"), val = tensor<int32, []>(1)]; |
| 445 | tensor<fp16, [16, 1280, 1, 1]> layers_1_self_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151685888)))]; |
| 446 | tensor<fp16, [1, 16, 1, 1]> input_39_cast_fp16 = conv(dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = layers_1_self_attn_o_proj_loraA_weight_to_fp16, x = input_37_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")]; |
| 447 | tensor<string, []> lora_out_27_pad_type_0 = const()[name = tensor<string, []>("lora_out_27_pad_type_0"), val = tensor<string, []>("valid")]; |
| 448 | tensor<int32, [2]> lora_out_27_strides_0 = const()[name = tensor<string, []>("lora_out_27_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 449 | tensor<int32, [4]> lora_out_27_pad_0 = const()[name = tensor<string, []>("lora_out_27_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 450 | tensor<int32, [2]> lora_out_27_dilations_0 = const()[name = tensor<string, []>("lora_out_27_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 451 | tensor<int32, []> lora_out_27_groups_0 = const()[name = tensor<string, []>("lora_out_27_groups_0"), val = tensor<int32, []>(1)]; |
| 452 | tensor<fp16, [1280, 16, 1, 1]> layers_1_self_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_self_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151726912)))]; |
| 453 | tensor<fp16, [1, 1280, 1, 1]> lora_out_27_cast_fp16 = conv(dilations = lora_out_27_dilations_0, groups = lora_out_27_groups_0, pad = lora_out_27_pad_0, pad_type = lora_out_27_pad_type_0, strides = lora_out_27_strides_0, weight = layers_1_self_attn_o_proj_loraB_weight_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("lora_out_27_cast_fp16")]; |
| 454 | tensor<fp16, [1, 1280, 1, 1]> obj_21_cast_fp16 = add(x = pretrained_out_27_cast_fp16, y = lora_out_27_cast_fp16)[name = tensor<string, []>("obj_21_cast_fp16")]; |
| 455 | tensor<fp16, [1, 1280, 1, 1]> inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = obj_21_cast_fp16)[name = tensor<string, []>("inputs_9_cast_fp16")]; |
| 456 | tensor<int32, [1]> out_9_axes_0 = const()[name = tensor<string, []>("out_9_axes_0"), val = tensor<int32, [1]>([1])]; |
| 457 | tensor<fp16, []> var_615_to_fp16 = const()[name = tensor<string, []>("op_615_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 458 | tensor<fp16, [1, 1280, 1, 1]> out_9_cast_fp16 = layer_norm(axes = out_9_axes_0, epsilon = var_615_to_fp16, x = inputs_9_cast_fp16)[name = tensor<string, []>("out_9_cast_fp16")]; |
| 459 | tensor<fp16, [1280]> obj_23_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_23_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151767936)))]; |
| 460 | tensor<fp16, [1280]> obj_23_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_23_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151770560)))]; |
| 461 | tensor<fp16, []> obj_23_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_23_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 462 | tensor<fp16, [1, 1280, 1, 1]> obj_23_cast_fp16 = batch_norm(beta = obj_23_beta_0_to_fp16, epsilon = obj_23_epsilon_0_to_fp16, gamma = obj_23_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor<string, []>("obj_23_cast_fp16")]; |
| 463 | tensor<string, []> pretrained_out_29_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_29_pad_type_0"), val = tensor<string, []>("valid")]; |
| 464 | tensor<int32, [2]> pretrained_out_29_strides_0 = const()[name = tensor<string, []>("pretrained_out_29_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 465 | tensor<int32, [4]> pretrained_out_29_pad_0 = const()[name = tensor<string, []>("pretrained_out_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 466 | tensor<int32, [2]> pretrained_out_29_dilations_0 = const()[name = tensor<string, []>("pretrained_out_29_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 467 | tensor<int32, []> pretrained_out_29_groups_0 = const()[name = tensor<string, []>("pretrained_out_29_groups_0"), val = tensor<int32, []>(1)]; |
| 468 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151773184))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152592448))), name = tensor<string, []>("layers_1_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 469 | tensor<fp16, [1280]> layers_1_encoder_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152592576)))]; |
| 470 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_29_cast_fp16 = conv(bias = layers_1_encoder_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_29_dilations_0, groups = pretrained_out_29_groups_0, pad = pretrained_out_29_pad_0, pad_type = pretrained_out_29_pad_type_0, strides = pretrained_out_29_strides_0, weight = layers_1_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_23_cast_fp16)[name = tensor<string, []>("pretrained_out_29_cast_fp16")]; |
| 471 | tensor<string, []> input_41_pad_type_0 = const()[name = tensor<string, []>("input_41_pad_type_0"), val = tensor<string, []>("valid")]; |
| 472 | tensor<int32, [2]> input_41_strides_0 = const()[name = tensor<string, []>("input_41_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 473 | tensor<int32, [4]> input_41_pad_0 = const()[name = tensor<string, []>("input_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 474 | tensor<int32, [2]> input_41_dilations_0 = const()[name = tensor<string, []>("input_41_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 475 | tensor<int32, []> input_41_groups_0 = const()[name = tensor<string, []>("input_41_groups_0"), val = tensor<int32, []>(1)]; |
| 476 | tensor<fp16, [16, 1280, 1, 1]> layers_1_encoder_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152595200)))]; |
| 477 | tensor<fp16, [1, 16, 1, 1]> input_41_cast_fp16 = conv(dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = layers_1_encoder_attn_q_proj_loraA_weight_to_fp16, x = obj_23_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")]; |
| 478 | tensor<string, []> lora_out_29_pad_type_0 = const()[name = tensor<string, []>("lora_out_29_pad_type_0"), val = tensor<string, []>("valid")]; |
| 479 | tensor<int32, [2]> lora_out_29_strides_0 = const()[name = tensor<string, []>("lora_out_29_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 480 | tensor<int32, [4]> lora_out_29_pad_0 = const()[name = tensor<string, []>("lora_out_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 481 | tensor<int32, [2]> lora_out_29_dilations_0 = const()[name = tensor<string, []>("lora_out_29_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 482 | tensor<int32, []> lora_out_29_groups_0 = const()[name = tensor<string, []>("lora_out_29_groups_0"), val = tensor<int32, []>(1)]; |
| 483 | tensor<fp16, [1280, 16, 1, 1]> layers_1_encoder_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152636224)))]; |
| 484 | tensor<fp16, [1, 1280, 1, 1]> lora_out_29_cast_fp16 = conv(dilations = lora_out_29_dilations_0, groups = lora_out_29_groups_0, pad = lora_out_29_pad_0, pad_type = lora_out_29_pad_type_0, strides = lora_out_29_strides_0, weight = layers_1_encoder_attn_q_proj_loraB_weight_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("lora_out_29_cast_fp16")]; |
| 485 | tensor<fp16, [1, 1280, 1, 1]> query_7_cast_fp16 = add(x = pretrained_out_29_cast_fp16, y = lora_out_29_cast_fp16)[name = tensor<string, []>("query_7_cast_fp16")]; |
| 486 | tensor<string, []> pretrained_out_31_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_31_pad_type_0"), val = tensor<string, []>("valid")]; |
| 487 | tensor<int32, [2]> pretrained_out_31_strides_0 = const()[name = tensor<string, []>("pretrained_out_31_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 488 | tensor<int32, [4]> pretrained_out_31_pad_0 = const()[name = tensor<string, []>("pretrained_out_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 489 | tensor<int32, [2]> pretrained_out_31_dilations_0 = const()[name = tensor<string, []>("pretrained_out_31_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 490 | tensor<int32, []> pretrained_out_31_groups_0 = const()[name = tensor<string, []>("pretrained_out_31_groups_0"), val = tensor<int32, []>(1)]; |
| 491 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152677248))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153496512))), name = tensor<string, []>("layers_1_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 492 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_31_cast_fp16 = conv(dilations = pretrained_out_31_dilations_0, groups = pretrained_out_31_groups_0, pad = pretrained_out_31_pad_0, pad_type = pretrained_out_31_pad_type_0, strides = pretrained_out_31_strides_0, weight = layers_1_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_31_cast_fp16")]; |
| 493 | tensor<string, []> input_43_pad_type_0 = const()[name = tensor<string, []>("input_43_pad_type_0"), val = tensor<string, []>("valid")]; |
| 494 | tensor<int32, [2]> input_43_strides_0 = const()[name = tensor<string, []>("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 495 | tensor<int32, [4]> input_43_pad_0 = const()[name = tensor<string, []>("input_43_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 496 | tensor<int32, [2]> input_43_dilations_0 = const()[name = tensor<string, []>("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 497 | tensor<int32, []> input_43_groups_0 = const()[name = tensor<string, []>("input_43_groups_0"), val = tensor<int32, []>(1)]; |
| 498 | tensor<fp16, [16, 1280, 1, 1]> layers_1_encoder_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153496640)))]; |
| 499 | tensor<fp16, [1, 16, 1, 1500]> input_43_cast_fp16 = conv(dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = layers_1_encoder_attn_k_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_43_cast_fp16")]; |
| 500 | tensor<string, []> lora_out_31_pad_type_0 = const()[name = tensor<string, []>("lora_out_31_pad_type_0"), val = tensor<string, []>("valid")]; |
| 501 | tensor<int32, [2]> lora_out_31_strides_0 = const()[name = tensor<string, []>("lora_out_31_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 502 | tensor<int32, [4]> lora_out_31_pad_0 = const()[name = tensor<string, []>("lora_out_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 503 | tensor<int32, [2]> lora_out_31_dilations_0 = const()[name = tensor<string, []>("lora_out_31_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 504 | tensor<int32, []> lora_out_31_groups_0 = const()[name = tensor<string, []>("lora_out_31_groups_0"), val = tensor<int32, []>(1)]; |
| 505 | tensor<fp16, [1280, 16, 1, 1]> layers_1_encoder_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153537664)))]; |
| 506 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_31_cast_fp16 = conv(dilations = lora_out_31_dilations_0, groups = lora_out_31_groups_0, pad = lora_out_31_pad_0, pad_type = lora_out_31_pad_type_0, strides = lora_out_31_strides_0, weight = layers_1_encoder_attn_k_proj_loraB_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("lora_out_31_cast_fp16")]; |
| 507 | tensor<fp16, [1, 1280, 1, 1500]> key_7_cast_fp16 = add(x = pretrained_out_31_cast_fp16, y = lora_out_31_cast_fp16)[name = tensor<string, []>("key_7_cast_fp16")]; |
| 508 | tensor<string, []> pretrained_out_33_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_33_pad_type_0"), val = tensor<string, []>("valid")]; |
| 509 | tensor<int32, [2]> pretrained_out_33_strides_0 = const()[name = tensor<string, []>("pretrained_out_33_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 510 | tensor<int32, [4]> pretrained_out_33_pad_0 = const()[name = tensor<string, []>("pretrained_out_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 511 | tensor<int32, [2]> pretrained_out_33_dilations_0 = const()[name = tensor<string, []>("pretrained_out_33_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 512 | tensor<int32, []> pretrained_out_33_groups_0 = const()[name = tensor<string, []>("pretrained_out_33_groups_0"), val = tensor<int32, []>(1)]; |
| 513 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153578688))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154397952))), name = tensor<string, []>("layers_1_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 514 | tensor<fp16, [1280]> layers_1_encoder_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154398080)))]; |
| 515 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_33_cast_fp16 = conv(bias = layers_1_encoder_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_33_dilations_0, groups = pretrained_out_33_groups_0, pad = pretrained_out_33_pad_0, pad_type = pretrained_out_33_pad_type_0, strides = pretrained_out_33_strides_0, weight = layers_1_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_33_cast_fp16")]; |
| 516 | tensor<string, []> input_45_pad_type_0 = const()[name = tensor<string, []>("input_45_pad_type_0"), val = tensor<string, []>("valid")]; |
| 517 | tensor<int32, [2]> input_45_strides_0 = const()[name = tensor<string, []>("input_45_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 518 | tensor<int32, [4]> input_45_pad_0 = const()[name = tensor<string, []>("input_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 519 | tensor<int32, [2]> input_45_dilations_0 = const()[name = tensor<string, []>("input_45_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 520 | tensor<int32, []> input_45_groups_0 = const()[name = tensor<string, []>("input_45_groups_0"), val = tensor<int32, []>(1)]; |
| 521 | tensor<fp16, [16, 1280, 1, 1]> layers_1_encoder_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154400704)))]; |
| 522 | tensor<fp16, [1, 16, 1, 1500]> input_45_cast_fp16 = conv(dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = layers_1_encoder_attn_v_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_45_cast_fp16")]; |
| 523 | tensor<string, []> lora_out_33_pad_type_0 = const()[name = tensor<string, []>("lora_out_33_pad_type_0"), val = tensor<string, []>("valid")]; |
| 524 | tensor<int32, [2]> lora_out_33_strides_0 = const()[name = tensor<string, []>("lora_out_33_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 525 | tensor<int32, [4]> lora_out_33_pad_0 = const()[name = tensor<string, []>("lora_out_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 526 | tensor<int32, [2]> lora_out_33_dilations_0 = const()[name = tensor<string, []>("lora_out_33_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 527 | tensor<int32, []> lora_out_33_groups_0 = const()[name = tensor<string, []>("lora_out_33_groups_0"), val = tensor<int32, []>(1)]; |
| 528 | tensor<fp16, [1280, 16, 1, 1]> layers_1_encoder_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154441728)))]; |
| 529 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_33_cast_fp16 = conv(dilations = lora_out_33_dilations_0, groups = lora_out_33_groups_0, pad = lora_out_33_pad_0, pad_type = lora_out_33_pad_type_0, strides = lora_out_33_strides_0, weight = layers_1_encoder_attn_v_proj_loraB_weight_to_fp16, x = input_45_cast_fp16)[name = tensor<string, []>("lora_out_33_cast_fp16")]; |
| 530 | tensor<fp16, [1, 1280, 1, 1500]> value_7_cast_fp16 = add(x = pretrained_out_33_cast_fp16, y = lora_out_33_cast_fp16)[name = tensor<string, []>("value_7_cast_fp16")]; |
| 531 | tensor<int32, [4]> var_698 = const()[name = tensor<string, []>("op_698"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 532 | tensor<fp16, [1, 20, 64, 1]> mh_q_7_cast_fp16 = reshape(shape = var_698, x = query_7_cast_fp16)[name = tensor<string, []>("mh_q_7_cast_fp16")]; |
| 533 | tensor<fp16, []> var_700_to_fp16 = const()[name = tensor<string, []>("op_700_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 534 | tensor<fp16, [1, 20, 64, 1]> var_701_cast_fp16 = mul(x = mh_q_7_cast_fp16, y = var_700_to_fp16)[name = tensor<string, []>("op_701_cast_fp16")]; |
| 535 | tensor<int32, [4]> var_702 = const()[name = tensor<string, []>("op_702"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 536 | tensor<fp16, [1, 20, 64, 1500]> var_703_cast_fp16 = reshape(shape = var_702, x = key_7_cast_fp16)[name = tensor<string, []>("op_703_cast_fp16")]; |
| 537 | tensor<bool, []> mh_w_11_transpose_x_0 = const()[name = tensor<string, []>("mh_w_11_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 538 | tensor<bool, []> mh_w_11_transpose_y_0 = const()[name = tensor<string, []>("mh_w_11_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 539 | tensor<fp16, [1, 20, 1, 1500]> mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_701_cast_fp16, y = var_703_cast_fp16)[name = tensor<string, []>("mh_w_11_cast_fp16")]; |
| 540 | tensor<fp16, [1, 20, 1, 1500]> obj_27_cast_fp16 = softmax(axis = var_438, x = mh_w_11_cast_fp16)[name = tensor<string, []>("obj_27_cast_fp16")]; |
| 541 | tensor<int32, [4]> var_707 = const()[name = tensor<string, []>("op_707"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 542 | tensor<fp16, [1, 20, 64, 1500]> var_708_cast_fp16 = reshape(shape = var_707, x = value_7_cast_fp16)[name = tensor<string, []>("op_708_cast_fp16")]; |
| 543 | tensor<bool, []> attn_7_transpose_x_0 = const()[name = tensor<string, []>("attn_7_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 544 | tensor<bool, []> attn_7_transpose_y_0 = const()[name = tensor<string, []>("attn_7_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 545 | tensor<fp16, [1, 20, 64, 1]> attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_708_cast_fp16, y = obj_27_cast_fp16)[name = tensor<string, []>("attn_7_cast_fp16")]; |
| 546 | tensor<int32, [4]> var_711 = const()[name = tensor<string, []>("op_711"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 547 | tensor<fp16, [1, 1280, 1, 1]> input_47_cast_fp16 = reshape(shape = var_711, x = attn_7_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")]; |
| 548 | tensor<string, []> pretrained_out_35_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_35_pad_type_0"), val = tensor<string, []>("valid")]; |
| 549 | tensor<int32, [2]> pretrained_out_35_strides_0 = const()[name = tensor<string, []>("pretrained_out_35_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 550 | tensor<int32, [4]> pretrained_out_35_pad_0 = const()[name = tensor<string, []>("pretrained_out_35_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 551 | tensor<int32, [2]> pretrained_out_35_dilations_0 = const()[name = tensor<string, []>("pretrained_out_35_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 552 | tensor<int32, []> pretrained_out_35_groups_0 = const()[name = tensor<string, []>("pretrained_out_35_groups_0"), val = tensor<int32, []>(1)]; |
| 553 | tensor<fp16, [1280, 1280, 1, 1]> layers_1_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154482752))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155302016))), name = tensor<string, []>("layers_1_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 554 | tensor<fp16, [1280]> layers_1_encoder_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155302144)))]; |
| 555 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_35_cast_fp16 = conv(bias = layers_1_encoder_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_35_dilations_0, groups = pretrained_out_35_groups_0, pad = pretrained_out_35_pad_0, pad_type = pretrained_out_35_pad_type_0, strides = pretrained_out_35_strides_0, weight = layers_1_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_47_cast_fp16)[name = tensor<string, []>("pretrained_out_35_cast_fp16")]; |
| 556 | tensor<string, []> input_49_pad_type_0 = const()[name = tensor<string, []>("input_49_pad_type_0"), val = tensor<string, []>("valid")]; |
| 557 | tensor<int32, [2]> input_49_strides_0 = const()[name = tensor<string, []>("input_49_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 558 | tensor<int32, [4]> input_49_pad_0 = const()[name = tensor<string, []>("input_49_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 559 | tensor<int32, [2]> input_49_dilations_0 = const()[name = tensor<string, []>("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 560 | tensor<int32, []> input_49_groups_0 = const()[name = tensor<string, []>("input_49_groups_0"), val = tensor<int32, []>(1)]; |
| 561 | tensor<fp16, [16, 1280, 1, 1]> layers_1_encoder_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155304768)))]; |
| 562 | tensor<fp16, [1, 16, 1, 1]> input_49_cast_fp16 = conv(dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = layers_1_encoder_attn_o_proj_loraA_weight_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")]; |
| 563 | tensor<string, []> lora_out_35_pad_type_0 = const()[name = tensor<string, []>("lora_out_35_pad_type_0"), val = tensor<string, []>("valid")]; |
| 564 | tensor<int32, [2]> lora_out_35_strides_0 = const()[name = tensor<string, []>("lora_out_35_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 565 | tensor<int32, [4]> lora_out_35_pad_0 = const()[name = tensor<string, []>("lora_out_35_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 566 | tensor<int32, [2]> lora_out_35_dilations_0 = const()[name = tensor<string, []>("lora_out_35_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 567 | tensor<int32, []> lora_out_35_groups_0 = const()[name = tensor<string, []>("lora_out_35_groups_0"), val = tensor<int32, []>(1)]; |
| 568 | tensor<fp16, [1280, 16, 1, 1]> layers_1_encoder_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_encoder_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155345792)))]; |
| 569 | tensor<fp16, [1, 1280, 1, 1]> lora_out_35_cast_fp16 = conv(dilations = lora_out_35_dilations_0, groups = lora_out_35_groups_0, pad = lora_out_35_pad_0, pad_type = lora_out_35_pad_type_0, strides = lora_out_35_strides_0, weight = layers_1_encoder_attn_o_proj_loraB_weight_to_fp16, x = input_49_cast_fp16)[name = tensor<string, []>("lora_out_35_cast_fp16")]; |
| 570 | tensor<fp16, [1, 1280, 1, 1]> obj_25_cast_fp16 = add(x = pretrained_out_35_cast_fp16, y = lora_out_35_cast_fp16)[name = tensor<string, []>("obj_25_cast_fp16")]; |
| 571 | tensor<fp16, [1, 1280, 1, 1]> inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_25_cast_fp16)[name = tensor<string, []>("inputs_11_cast_fp16")]; |
| 572 | tensor<int32, [1]> out_11_axes_0 = const()[name = tensor<string, []>("out_11_axes_0"), val = tensor<int32, [1]>([1])]; |
| 573 | tensor<fp16, []> var_745_to_fp16 = const()[name = tensor<string, []>("op_745_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 574 | tensor<fp16, [1, 1280, 1, 1]> out_11_cast_fp16 = layer_norm(axes = out_11_axes_0, epsilon = var_745_to_fp16, x = inputs_11_cast_fp16)[name = tensor<string, []>("out_11_cast_fp16")]; |
| 575 | tensor<fp16, [1280]> input_51_gamma_0_to_fp16 = const()[name = tensor<string, []>("input_51_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155386816)))]; |
| 576 | tensor<fp16, [1280]> input_51_beta_0_to_fp16 = const()[name = tensor<string, []>("input_51_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155389440)))]; |
| 577 | tensor<fp16, []> input_51_epsilon_0_to_fp16 = const()[name = tensor<string, []>("input_51_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 578 | tensor<fp16, [1, 1280, 1, 1]> input_51_cast_fp16 = batch_norm(beta = input_51_beta_0_to_fp16, epsilon = input_51_epsilon_0_to_fp16, gamma = input_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")]; |
| 579 | tensor<string, []> pretrained_out_37_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_37_pad_type_0"), val = tensor<string, []>("valid")]; |
| 580 | tensor<int32, [2]> pretrained_out_37_strides_0 = const()[name = tensor<string, []>("pretrained_out_37_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 581 | tensor<int32, [4]> pretrained_out_37_pad_0 = const()[name = tensor<string, []>("pretrained_out_37_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 582 | tensor<int32, [2]> pretrained_out_37_dilations_0 = const()[name = tensor<string, []>("pretrained_out_37_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 583 | tensor<int32, []> pretrained_out_37_groups_0 = const()[name = tensor<string, []>("pretrained_out_37_groups_0"), val = tensor<int32, []>(1)]; |
| 584 | tensor<fp16, [5120, 1280, 1, 1]> layers_1_fc1_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155392064))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158668928))), name = tensor<string, []>("layers_1_fc1_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([5120, 1280, 1, 1])]; |
| 585 | tensor<fp16, [5120]> layers_1_fc1_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_fc1_pretrained_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158669056)))]; |
| 586 | tensor<fp16, [1, 5120, 1, 1]> pretrained_out_37_cast_fp16 = conv(bias = layers_1_fc1_pretrained_bias_to_fp16, dilations = pretrained_out_37_dilations_0, groups = pretrained_out_37_groups_0, pad = pretrained_out_37_pad_0, pad_type = pretrained_out_37_pad_type_0, strides = pretrained_out_37_strides_0, weight = layers_1_fc1_pretrained_weight_to_fp16_palettized, x = input_51_cast_fp16)[name = tensor<string, []>("pretrained_out_37_cast_fp16")]; |
| 587 | tensor<string, []> input_53_pad_type_0 = const()[name = tensor<string, []>("input_53_pad_type_0"), val = tensor<string, []>("valid")]; |
| 588 | tensor<int32, [2]> input_53_strides_0 = const()[name = tensor<string, []>("input_53_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 589 | tensor<int32, [4]> input_53_pad_0 = const()[name = tensor<string, []>("input_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 590 | tensor<int32, [2]> input_53_dilations_0 = const()[name = tensor<string, []>("input_53_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 591 | tensor<int32, []> input_53_groups_0 = const()[name = tensor<string, []>("input_53_groups_0"), val = tensor<int32, []>(1)]; |
| 592 | tensor<fp16, [16, 1280, 1, 1]> layers_1_fc1_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_fc1_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158679360)))]; |
| 593 | tensor<fp16, [1, 16, 1, 1]> input_53_cast_fp16 = conv(dilations = input_53_dilations_0, groups = input_53_groups_0, pad = input_53_pad_0, pad_type = input_53_pad_type_0, strides = input_53_strides_0, weight = layers_1_fc1_loraA_weight_to_fp16, x = input_51_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")]; |
| 594 | tensor<string, []> lora_out_37_pad_type_0 = const()[name = tensor<string, []>("lora_out_37_pad_type_0"), val = tensor<string, []>("valid")]; |
| 595 | tensor<int32, [2]> lora_out_37_strides_0 = const()[name = tensor<string, []>("lora_out_37_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 596 | tensor<int32, [4]> lora_out_37_pad_0 = const()[name = tensor<string, []>("lora_out_37_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 597 | tensor<int32, [2]> lora_out_37_dilations_0 = const()[name = tensor<string, []>("lora_out_37_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 598 | tensor<int32, []> lora_out_37_groups_0 = const()[name = tensor<string, []>("lora_out_37_groups_0"), val = tensor<int32, []>(1)]; |
| 599 | tensor<fp16, [5120, 16, 1, 1]> layers_1_fc1_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_fc1_loraB_weight_to_fp16"), val = tensor<fp16, [5120, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158720384)))]; |
| 600 | tensor<fp16, [1, 5120, 1, 1]> lora_out_37_cast_fp16 = conv(dilations = lora_out_37_dilations_0, groups = lora_out_37_groups_0, pad = lora_out_37_pad_0, pad_type = lora_out_37_pad_type_0, strides = lora_out_37_strides_0, weight = layers_1_fc1_loraB_weight_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("lora_out_37_cast_fp16")]; |
| 601 | tensor<fp16, [1, 5120, 1, 1]> input_55_cast_fp16 = add(x = pretrained_out_37_cast_fp16, y = lora_out_37_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")]; |
| 602 | tensor<string, []> input_57_mode_0 = const()[name = tensor<string, []>("input_57_mode_0"), val = tensor<string, []>("EXACT")]; |
| 603 | tensor<fp16, [1, 5120, 1, 1]> input_57_cast_fp16 = gelu(mode = input_57_mode_0, x = input_55_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")]; |
| 604 | tensor<string, []> pretrained_out_39_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_39_pad_type_0"), val = tensor<string, []>("valid")]; |
| 605 | tensor<int32, [2]> pretrained_out_39_strides_0 = const()[name = tensor<string, []>("pretrained_out_39_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 606 | tensor<int32, [4]> pretrained_out_39_pad_0 = const()[name = tensor<string, []>("pretrained_out_39_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 607 | tensor<int32, [2]> pretrained_out_39_dilations_0 = const()[name = tensor<string, []>("pretrained_out_39_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 608 | tensor<int32, []> pretrained_out_39_groups_0 = const()[name = tensor<string, []>("pretrained_out_39_groups_0"), val = tensor<int32, []>(1)]; |
| 609 | tensor<fp16, [1280, 5120, 1, 1]> layers_1_fc2_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158884288))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162161152))), name = tensor<string, []>("layers_1_fc2_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 5120, 1, 1])]; |
| 610 | tensor<fp16, [1280]> layers_1_fc2_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_1_fc2_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162161280)))]; |
| 611 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_39_cast_fp16 = conv(bias = layers_1_fc2_pretrained_bias_to_fp16, dilations = pretrained_out_39_dilations_0, groups = pretrained_out_39_groups_0, pad = pretrained_out_39_pad_0, pad_type = pretrained_out_39_pad_type_0, strides = pretrained_out_39_strides_0, weight = layers_1_fc2_pretrained_weight_to_fp16_palettized, x = input_57_cast_fp16)[name = tensor<string, []>("pretrained_out_39_cast_fp16")]; |
| 612 | tensor<string, []> input_59_pad_type_0 = const()[name = tensor<string, []>("input_59_pad_type_0"), val = tensor<string, []>("valid")]; |
| 613 | tensor<int32, [2]> input_59_strides_0 = const()[name = tensor<string, []>("input_59_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 614 | tensor<int32, [4]> input_59_pad_0 = const()[name = tensor<string, []>("input_59_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 615 | tensor<int32, [2]> input_59_dilations_0 = const()[name = tensor<string, []>("input_59_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 616 | tensor<int32, []> input_59_groups_0 = const()[name = tensor<string, []>("input_59_groups_0"), val = tensor<int32, []>(1)]; |
| 617 | tensor<fp16, [16, 5120, 1, 1]> layers_1_fc2_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_fc2_loraA_weight_to_fp16"), val = tensor<fp16, [16, 5120, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162163904)))]; |
| 618 | tensor<fp16, [1, 16, 1, 1]> input_59_cast_fp16 = conv(dilations = input_59_dilations_0, groups = input_59_groups_0, pad = input_59_pad_0, pad_type = input_59_pad_type_0, strides = input_59_strides_0, weight = layers_1_fc2_loraA_weight_to_fp16, x = input_57_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")]; |
| 619 | tensor<string, []> lora_out_39_pad_type_0 = const()[name = tensor<string, []>("lora_out_39_pad_type_0"), val = tensor<string, []>("valid")]; |
| 620 | tensor<int32, [2]> lora_out_39_strides_0 = const()[name = tensor<string, []>("lora_out_39_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 621 | tensor<int32, [4]> lora_out_39_pad_0 = const()[name = tensor<string, []>("lora_out_39_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 622 | tensor<int32, [2]> lora_out_39_dilations_0 = const()[name = tensor<string, []>("lora_out_39_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 623 | tensor<int32, []> lora_out_39_groups_0 = const()[name = tensor<string, []>("lora_out_39_groups_0"), val = tensor<int32, []>(1)]; |
| 624 | tensor<fp16, [1280, 16, 1, 1]> layers_1_fc2_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_1_fc2_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162327808)))]; |
| 625 | tensor<fp16, [1, 1280, 1, 1]> lora_out_39_cast_fp16 = conv(dilations = lora_out_39_dilations_0, groups = lora_out_39_groups_0, pad = lora_out_39_pad_0, pad_type = lora_out_39_pad_type_0, strides = lora_out_39_strides_0, weight = layers_1_fc2_loraB_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("lora_out_39_cast_fp16")]; |
| 626 | tensor<fp16, [1, 1280, 1, 1]> hidden_states_5_cast_fp16 = add(x = pretrained_out_39_cast_fp16, y = lora_out_39_cast_fp16)[name = tensor<string, []>("hidden_states_5_cast_fp16")]; |
| 627 | tensor<fp16, [1, 1280, 1, 1]> inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor<string, []>("inputs_13_cast_fp16")]; |
| 628 | tensor<int32, []> var_812 = const()[name = tensor<string, []>("op_812"), val = tensor<int32, []>(3)]; |
| 629 | tensor<int32, [1]> out_13_axes_0 = const()[name = tensor<string, []>("out_13_axes_0"), val = tensor<int32, [1]>([1])]; |
| 630 | tensor<fp16, []> var_838_to_fp16 = const()[name = tensor<string, []>("op_838_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 631 | tensor<fp16, [1, 1280, 1, 1]> out_13_cast_fp16 = layer_norm(axes = out_13_axes_0, epsilon = var_838_to_fp16, x = inputs_13_cast_fp16)[name = tensor<string, []>("out_13_cast_fp16")]; |
| 632 | tensor<fp16, [1280]> obj_29_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_29_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162368832)))]; |
| 633 | tensor<fp16, [1280]> obj_29_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_29_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162371456)))]; |
| 634 | tensor<fp16, []> obj_29_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_29_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 635 | tensor<fp16, [1, 1280, 1, 1]> obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor<string, []>("obj_29_cast_fp16")]; |
| 636 | tensor<string, []> pretrained_out_41_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_41_pad_type_0"), val = tensor<string, []>("valid")]; |
| 637 | tensor<int32, [2]> pretrained_out_41_strides_0 = const()[name = tensor<string, []>("pretrained_out_41_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 638 | tensor<int32, [4]> pretrained_out_41_pad_0 = const()[name = tensor<string, []>("pretrained_out_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 639 | tensor<int32, [2]> pretrained_out_41_dilations_0 = const()[name = tensor<string, []>("pretrained_out_41_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 640 | tensor<int32, []> pretrained_out_41_groups_0 = const()[name = tensor<string, []>("pretrained_out_41_groups_0"), val = tensor<int32, []>(1)]; |
| 641 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_self_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162374080))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163193344))), name = tensor<string, []>("layers_2_self_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 642 | tensor<fp16, [1280]> layers_2_self_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163193472)))]; |
| 643 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_41_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_41_dilations_0, groups = pretrained_out_41_groups_0, pad = pretrained_out_41_pad_0, pad_type = pretrained_out_41_pad_type_0, strides = pretrained_out_41_strides_0, weight = layers_2_self_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_29_cast_fp16)[name = tensor<string, []>("pretrained_out_41_cast_fp16")]; |
| 644 | tensor<string, []> input_61_pad_type_0 = const()[name = tensor<string, []>("input_61_pad_type_0"), val = tensor<string, []>("valid")]; |
| 645 | tensor<int32, [2]> input_61_strides_0 = const()[name = tensor<string, []>("input_61_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 646 | tensor<int32, [4]> input_61_pad_0 = const()[name = tensor<string, []>("input_61_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 647 | tensor<int32, [2]> input_61_dilations_0 = const()[name = tensor<string, []>("input_61_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 648 | tensor<int32, []> input_61_groups_0 = const()[name = tensor<string, []>("input_61_groups_0"), val = tensor<int32, []>(1)]; |
| 649 | tensor<fp16, [16, 1280, 1, 1]> layers_2_self_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163196096)))]; |
| 650 | tensor<fp16, [1, 16, 1, 1]> input_61_cast_fp16 = conv(dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = layers_2_self_attn_q_proj_loraA_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")]; |
| 651 | tensor<string, []> lora_out_41_pad_type_0 = const()[name = tensor<string, []>("lora_out_41_pad_type_0"), val = tensor<string, []>("valid")]; |
| 652 | tensor<int32, [2]> lora_out_41_strides_0 = const()[name = tensor<string, []>("lora_out_41_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 653 | tensor<int32, [4]> lora_out_41_pad_0 = const()[name = tensor<string, []>("lora_out_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 654 | tensor<int32, [2]> lora_out_41_dilations_0 = const()[name = tensor<string, []>("lora_out_41_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 655 | tensor<int32, []> lora_out_41_groups_0 = const()[name = tensor<string, []>("lora_out_41_groups_0"), val = tensor<int32, []>(1)]; |
| 656 | tensor<fp16, [1280, 16, 1, 1]> layers_2_self_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163237120)))]; |
| 657 | tensor<fp16, [1, 1280, 1, 1]> lora_out_41_cast_fp16 = conv(dilations = lora_out_41_dilations_0, groups = lora_out_41_groups_0, pad = lora_out_41_pad_0, pad_type = lora_out_41_pad_type_0, strides = lora_out_41_strides_0, weight = layers_2_self_attn_q_proj_loraB_weight_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("lora_out_41_cast_fp16")]; |
| 658 | tensor<fp16, [1, 1280, 1, 1]> query_9_cast_fp16 = add(x = pretrained_out_41_cast_fp16, y = lora_out_41_cast_fp16)[name = tensor<string, []>("query_9_cast_fp16")]; |
| 659 | tensor<string, []> pretrained_out_43_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_43_pad_type_0"), val = tensor<string, []>("valid")]; |
| 660 | tensor<int32, [2]> pretrained_out_43_strides_0 = const()[name = tensor<string, []>("pretrained_out_43_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 661 | tensor<int32, [4]> pretrained_out_43_pad_0 = const()[name = tensor<string, []>("pretrained_out_43_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 662 | tensor<int32, [2]> pretrained_out_43_dilations_0 = const()[name = tensor<string, []>("pretrained_out_43_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 663 | tensor<int32, []> pretrained_out_43_groups_0 = const()[name = tensor<string, []>("pretrained_out_43_groups_0"), val = tensor<int32, []>(1)]; |
| 664 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_self_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163278144))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164097408))), name = tensor<string, []>("layers_2_self_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 665 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_43_cast_fp16 = conv(dilations = pretrained_out_43_dilations_0, groups = pretrained_out_43_groups_0, pad = pretrained_out_43_pad_0, pad_type = pretrained_out_43_pad_type_0, strides = pretrained_out_43_strides_0, weight = layers_2_self_attn_k_proj_pretrained_weight_to_fp16_palettized, x = obj_29_cast_fp16)[name = tensor<string, []>("pretrained_out_43_cast_fp16")]; |
| 666 | tensor<string, []> input_63_pad_type_0 = const()[name = tensor<string, []>("input_63_pad_type_0"), val = tensor<string, []>("valid")]; |
| 667 | tensor<int32, [2]> input_63_strides_0 = const()[name = tensor<string, []>("input_63_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 668 | tensor<int32, [4]> input_63_pad_0 = const()[name = tensor<string, []>("input_63_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 669 | tensor<int32, [2]> input_63_dilations_0 = const()[name = tensor<string, []>("input_63_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 670 | tensor<int32, []> input_63_groups_0 = const()[name = tensor<string, []>("input_63_groups_0"), val = tensor<int32, []>(1)]; |
| 671 | tensor<fp16, [16, 1280, 1, 1]> layers_2_self_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164097536)))]; |
| 672 | tensor<fp16, [1, 16, 1, 1]> input_63_cast_fp16 = conv(dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = layers_2_self_attn_k_proj_loraA_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")]; |
| 673 | tensor<string, []> lora_out_43_pad_type_0 = const()[name = tensor<string, []>("lora_out_43_pad_type_0"), val = tensor<string, []>("valid")]; |
| 674 | tensor<int32, [2]> lora_out_43_strides_0 = const()[name = tensor<string, []>("lora_out_43_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 675 | tensor<int32, [4]> lora_out_43_pad_0 = const()[name = tensor<string, []>("lora_out_43_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 676 | tensor<int32, [2]> lora_out_43_dilations_0 = const()[name = tensor<string, []>("lora_out_43_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 677 | tensor<int32, []> lora_out_43_groups_0 = const()[name = tensor<string, []>("lora_out_43_groups_0"), val = tensor<int32, []>(1)]; |
| 678 | tensor<fp16, [1280, 16, 1, 1]> layers_2_self_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164138560)))]; |
| 679 | tensor<fp16, [1, 1280, 1, 1]> lora_out_43_cast_fp16 = conv(dilations = lora_out_43_dilations_0, groups = lora_out_43_groups_0, pad = lora_out_43_pad_0, pad_type = lora_out_43_pad_type_0, strides = lora_out_43_strides_0, weight = layers_2_self_attn_k_proj_loraB_weight_to_fp16, x = input_63_cast_fp16)[name = tensor<string, []>("lora_out_43_cast_fp16")]; |
| 680 | tensor<fp16, [1, 1280, 1, 1]> current_key_5_cast_fp16 = add(x = pretrained_out_43_cast_fp16, y = lora_out_43_cast_fp16)[name = tensor<string, []>("current_key_5_cast_fp16")]; |
| 681 | tensor<string, []> pretrained_out_45_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_45_pad_type_0"), val = tensor<string, []>("valid")]; |
| 682 | tensor<int32, [2]> pretrained_out_45_strides_0 = const()[name = tensor<string, []>("pretrained_out_45_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 683 | tensor<int32, [4]> pretrained_out_45_pad_0 = const()[name = tensor<string, []>("pretrained_out_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 684 | tensor<int32, [2]> pretrained_out_45_dilations_0 = const()[name = tensor<string, []>("pretrained_out_45_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 685 | tensor<int32, []> pretrained_out_45_groups_0 = const()[name = tensor<string, []>("pretrained_out_45_groups_0"), val = tensor<int32, []>(1)]; |
| 686 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_self_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164179584))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164998848))), name = tensor<string, []>("layers_2_self_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 687 | tensor<fp16, [1280]> layers_2_self_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164998976)))]; |
| 688 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_45_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_45_dilations_0, groups = pretrained_out_45_groups_0, pad = pretrained_out_45_pad_0, pad_type = pretrained_out_45_pad_type_0, strides = pretrained_out_45_strides_0, weight = layers_2_self_attn_v_proj_pretrained_weight_to_fp16_palettized, x = obj_29_cast_fp16)[name = tensor<string, []>("pretrained_out_45_cast_fp16")]; |
| 689 | tensor<string, []> input_65_pad_type_0 = const()[name = tensor<string, []>("input_65_pad_type_0"), val = tensor<string, []>("valid")]; |
| 690 | tensor<int32, [2]> input_65_strides_0 = const()[name = tensor<string, []>("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 691 | tensor<int32, [4]> input_65_pad_0 = const()[name = tensor<string, []>("input_65_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 692 | tensor<int32, [2]> input_65_dilations_0 = const()[name = tensor<string, []>("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 693 | tensor<int32, []> input_65_groups_0 = const()[name = tensor<string, []>("input_65_groups_0"), val = tensor<int32, []>(1)]; |
| 694 | tensor<fp16, [16, 1280, 1, 1]> layers_2_self_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165001600)))]; |
| 695 | tensor<fp16, [1, 16, 1, 1]> input_65_cast_fp16 = conv(dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = layers_2_self_attn_v_proj_loraA_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")]; |
| 696 | tensor<string, []> lora_out_45_pad_type_0 = const()[name = tensor<string, []>("lora_out_45_pad_type_0"), val = tensor<string, []>("valid")]; |
| 697 | tensor<int32, [2]> lora_out_45_strides_0 = const()[name = tensor<string, []>("lora_out_45_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 698 | tensor<int32, [4]> lora_out_45_pad_0 = const()[name = tensor<string, []>("lora_out_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 699 | tensor<int32, [2]> lora_out_45_dilations_0 = const()[name = tensor<string, []>("lora_out_45_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 700 | tensor<int32, []> lora_out_45_groups_0 = const()[name = tensor<string, []>("lora_out_45_groups_0"), val = tensor<int32, []>(1)]; |
| 701 | tensor<fp16, [1280, 16, 1, 1]> layers_2_self_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165042624)))]; |
| 702 | tensor<fp16, [1, 1280, 1, 1]> lora_out_45_cast_fp16 = conv(dilations = lora_out_45_dilations_0, groups = lora_out_45_groups_0, pad = lora_out_45_pad_0, pad_type = lora_out_45_pad_type_0, strides = lora_out_45_strides_0, weight = layers_2_self_attn_v_proj_loraB_weight_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("lora_out_45_cast_fp16")]; |
| 703 | tensor<fp16, [1, 1280, 1, 1]> current_value_5_cast_fp16 = add(x = pretrained_out_45_cast_fp16, y = lora_out_45_cast_fp16)[name = tensor<string, []>("current_value_5_cast_fp16")]; |
| 704 | tensor<fp16, [1, 1280, 1, 448]> var_924_cast_fp16 = mul(x = current_key_5_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_924_cast_fp16")]; |
| 705 | tensor<fp16, [1, 1280, 1, 448]> var_926_cast_fp16 = mul(x = var_47_cast_fp16_2, y = var_177_cast_fp16)[name = tensor<string, []>("op_926_cast_fp16")]; |
| 706 | tensor<fp16, [1, 1280, 1, 448]> key_9_cast_fp16 = add(x = var_924_cast_fp16, y = var_926_cast_fp16)[name = tensor<string, []>("key_9_cast_fp16")]; |
| 707 | tensor<fp16, [1, 1280, 1, 448]> var_928_cast_fp16 = mul(x = current_value_5_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_928_cast_fp16")]; |
| 708 | tensor<fp16, [1, 1280, 1, 448]> var_930_cast_fp16 = mul(x = var_54_cast_fp16_2, y = var_177_cast_fp16)[name = tensor<string, []>("op_930_cast_fp16")]; |
| 709 | tensor<fp16, [1, 1280, 1, 448]> value_9_cast_fp16 = add(x = var_928_cast_fp16, y = var_930_cast_fp16)[name = tensor<string, []>("value_9_cast_fp16")]; |
| 710 | tensor<int32, [4]> var_933 = const()[name = tensor<string, []>("op_933"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 711 | tensor<fp16, [1, 20, 64, 1]> mh_q_9_cast_fp16 = reshape(shape = var_933, x = query_9_cast_fp16)[name = tensor<string, []>("mh_q_9_cast_fp16")]; |
| 712 | tensor<fp16, []> var_935_to_fp16 = const()[name = tensor<string, []>("op_935_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 713 | tensor<fp16, [1, 20, 64, 1]> var_936_cast_fp16 = mul(x = mh_q_9_cast_fp16, y = var_935_to_fp16)[name = tensor<string, []>("op_936_cast_fp16")]; |
| 714 | tensor<int32, [4]> var_937 = const()[name = tensor<string, []>("op_937"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 715 | tensor<fp16, [1, 20, 64, 448]> var_938_cast_fp16 = reshape(shape = var_937, x = key_9_cast_fp16)[name = tensor<string, []>("op_938_cast_fp16")]; |
| 716 | tensor<bool, []> mh_w_13_transpose_x_0 = const()[name = tensor<string, []>("mh_w_13_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 717 | tensor<bool, []> mh_w_13_transpose_y_0 = const()[name = tensor<string, []>("mh_w_13_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 718 | tensor<fp16, [1, 20, 1, 448]> mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_936_cast_fp16, y = var_938_cast_fp16)[name = tensor<string, []>("mh_w_13_cast_fp16")]; |
| 719 | tensor<fp16, [1, 20, 1, 448]> mh_w_15_cast_fp16 = add(x = mh_w_13_cast_fp16, y = var_195_cast_fp16)[name = tensor<string, []>("mh_w_15_cast_fp16")]; |
| 720 | tensor<fp16, [1, 20, 1, 448]> var_946_cast_fp16 = softmax(axis = var_812, x = mh_w_15_cast_fp16)[name = tensor<string, []>("op_946_cast_fp16")]; |
| 721 | tensor<int32, [4]> var_947 = const()[name = tensor<string, []>("op_947"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 722 | tensor<fp16, [1, 20, 64, 448]> var_948_cast_fp16 = reshape(shape = var_947, x = value_9_cast_fp16)[name = tensor<string, []>("op_948_cast_fp16")]; |
| 723 | tensor<bool, []> attn_9_transpose_x_0 = const()[name = tensor<string, []>("attn_9_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 724 | tensor<bool, []> attn_9_transpose_y_0 = const()[name = tensor<string, []>("attn_9_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 725 | tensor<fp16, [1, 20, 64, 1]> attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_948_cast_fp16, y = var_946_cast_fp16)[name = tensor<string, []>("attn_9_cast_fp16")]; |
| 726 | tensor<int32, [4]> var_951 = const()[name = tensor<string, []>("op_951"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 727 | tensor<fp16, [1, 1280, 1, 1]> input_67_cast_fp16 = reshape(shape = var_951, x = attn_9_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")]; |
| 728 | tensor<string, []> pretrained_out_47_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_47_pad_type_0"), val = tensor<string, []>("valid")]; |
| 729 | tensor<int32, [2]> pretrained_out_47_strides_0 = const()[name = tensor<string, []>("pretrained_out_47_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 730 | tensor<int32, [4]> pretrained_out_47_pad_0 = const()[name = tensor<string, []>("pretrained_out_47_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 731 | tensor<int32, [2]> pretrained_out_47_dilations_0 = const()[name = tensor<string, []>("pretrained_out_47_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 732 | tensor<int32, []> pretrained_out_47_groups_0 = const()[name = tensor<string, []>("pretrained_out_47_groups_0"), val = tensor<int32, []>(1)]; |
| 733 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_self_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165083648))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165902912))), name = tensor<string, []>("layers_2_self_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 734 | tensor<fp16, [1280]> layers_2_self_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165903040)))]; |
| 735 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_47_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_47_dilations_0, groups = pretrained_out_47_groups_0, pad = pretrained_out_47_pad_0, pad_type = pretrained_out_47_pad_type_0, strides = pretrained_out_47_strides_0, weight = layers_2_self_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_67_cast_fp16)[name = tensor<string, []>("pretrained_out_47_cast_fp16")]; |
| 736 | tensor<string, []> input_69_pad_type_0 = const()[name = tensor<string, []>("input_69_pad_type_0"), val = tensor<string, []>("valid")]; |
| 737 | tensor<int32, [2]> input_69_strides_0 = const()[name = tensor<string, []>("input_69_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 738 | tensor<int32, [4]> input_69_pad_0 = const()[name = tensor<string, []>("input_69_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 739 | tensor<int32, [2]> input_69_dilations_0 = const()[name = tensor<string, []>("input_69_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 740 | tensor<int32, []> input_69_groups_0 = const()[name = tensor<string, []>("input_69_groups_0"), val = tensor<int32, []>(1)]; |
| 741 | tensor<fp16, [16, 1280, 1, 1]> layers_2_self_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165905664)))]; |
| 742 | tensor<fp16, [1, 16, 1, 1]> input_69_cast_fp16 = conv(dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = layers_2_self_attn_o_proj_loraA_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")]; |
| 743 | tensor<string, []> lora_out_47_pad_type_0 = const()[name = tensor<string, []>("lora_out_47_pad_type_0"), val = tensor<string, []>("valid")]; |
| 744 | tensor<int32, [2]> lora_out_47_strides_0 = const()[name = tensor<string, []>("lora_out_47_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 745 | tensor<int32, [4]> lora_out_47_pad_0 = const()[name = tensor<string, []>("lora_out_47_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 746 | tensor<int32, [2]> lora_out_47_dilations_0 = const()[name = tensor<string, []>("lora_out_47_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 747 | tensor<int32, []> lora_out_47_groups_0 = const()[name = tensor<string, []>("lora_out_47_groups_0"), val = tensor<int32, []>(1)]; |
| 748 | tensor<fp16, [1280, 16, 1, 1]> layers_2_self_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_self_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165946688)))]; |
| 749 | tensor<fp16, [1, 1280, 1, 1]> lora_out_47_cast_fp16 = conv(dilations = lora_out_47_dilations_0, groups = lora_out_47_groups_0, pad = lora_out_47_pad_0, pad_type = lora_out_47_pad_type_0, strides = lora_out_47_strides_0, weight = layers_2_self_attn_o_proj_loraB_weight_to_fp16, x = input_69_cast_fp16)[name = tensor<string, []>("lora_out_47_cast_fp16")]; |
| 750 | tensor<fp16, [1, 1280, 1, 1]> obj_35_cast_fp16 = add(x = pretrained_out_47_cast_fp16, y = lora_out_47_cast_fp16)[name = tensor<string, []>("obj_35_cast_fp16")]; |
| 751 | tensor<fp16, [1, 1280, 1, 1]> inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_35_cast_fp16)[name = tensor<string, []>("inputs_15_cast_fp16")]; |
| 752 | tensor<int32, [1]> out_15_axes_0 = const()[name = tensor<string, []>("out_15_axes_0"), val = tensor<int32, [1]>([1])]; |
| 753 | tensor<fp16, []> var_989_to_fp16 = const()[name = tensor<string, []>("op_989_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 754 | tensor<fp16, [1, 1280, 1, 1]> out_15_cast_fp16 = layer_norm(axes = out_15_axes_0, epsilon = var_989_to_fp16, x = inputs_15_cast_fp16)[name = tensor<string, []>("out_15_cast_fp16")]; |
| 755 | tensor<fp16, [1280]> obj_37_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_37_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165987712)))]; |
| 756 | tensor<fp16, [1280]> obj_37_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_37_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165990336)))]; |
| 757 | tensor<fp16, []> obj_37_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_37_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 758 | tensor<fp16, [1, 1280, 1, 1]> obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor<string, []>("obj_37_cast_fp16")]; |
| 759 | tensor<string, []> pretrained_out_49_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_49_pad_type_0"), val = tensor<string, []>("valid")]; |
| 760 | tensor<int32, [2]> pretrained_out_49_strides_0 = const()[name = tensor<string, []>("pretrained_out_49_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 761 | tensor<int32, [4]> pretrained_out_49_pad_0 = const()[name = tensor<string, []>("pretrained_out_49_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 762 | tensor<int32, [2]> pretrained_out_49_dilations_0 = const()[name = tensor<string, []>("pretrained_out_49_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 763 | tensor<int32, []> pretrained_out_49_groups_0 = const()[name = tensor<string, []>("pretrained_out_49_groups_0"), val = tensor<int32, []>(1)]; |
| 764 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165992960))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166812224))), name = tensor<string, []>("layers_2_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 765 | tensor<fp16, [1280]> layers_2_encoder_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166812352)))]; |
| 766 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_49_cast_fp16 = conv(bias = layers_2_encoder_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_49_dilations_0, groups = pretrained_out_49_groups_0, pad = pretrained_out_49_pad_0, pad_type = pretrained_out_49_pad_type_0, strides = pretrained_out_49_strides_0, weight = layers_2_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_37_cast_fp16)[name = tensor<string, []>("pretrained_out_49_cast_fp16")]; |
| 767 | tensor<string, []> input_71_pad_type_0 = const()[name = tensor<string, []>("input_71_pad_type_0"), val = tensor<string, []>("valid")]; |
| 768 | tensor<int32, [2]> input_71_strides_0 = const()[name = tensor<string, []>("input_71_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 769 | tensor<int32, [4]> input_71_pad_0 = const()[name = tensor<string, []>("input_71_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 770 | tensor<int32, [2]> input_71_dilations_0 = const()[name = tensor<string, []>("input_71_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 771 | tensor<int32, []> input_71_groups_0 = const()[name = tensor<string, []>("input_71_groups_0"), val = tensor<int32, []>(1)]; |
| 772 | tensor<fp16, [16, 1280, 1, 1]> layers_2_encoder_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166814976)))]; |
| 773 | tensor<fp16, [1, 16, 1, 1]> input_71_cast_fp16 = conv(dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = layers_2_encoder_attn_q_proj_loraA_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")]; |
| 774 | tensor<string, []> lora_out_49_pad_type_0 = const()[name = tensor<string, []>("lora_out_49_pad_type_0"), val = tensor<string, []>("valid")]; |
| 775 | tensor<int32, [2]> lora_out_49_strides_0 = const()[name = tensor<string, []>("lora_out_49_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 776 | tensor<int32, [4]> lora_out_49_pad_0 = const()[name = tensor<string, []>("lora_out_49_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 777 | tensor<int32, [2]> lora_out_49_dilations_0 = const()[name = tensor<string, []>("lora_out_49_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 778 | tensor<int32, []> lora_out_49_groups_0 = const()[name = tensor<string, []>("lora_out_49_groups_0"), val = tensor<int32, []>(1)]; |
| 779 | tensor<fp16, [1280, 16, 1, 1]> layers_2_encoder_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166856000)))]; |
| 780 | tensor<fp16, [1, 1280, 1, 1]> lora_out_49_cast_fp16 = conv(dilations = lora_out_49_dilations_0, groups = lora_out_49_groups_0, pad = lora_out_49_pad_0, pad_type = lora_out_49_pad_type_0, strides = lora_out_49_strides_0, weight = layers_2_encoder_attn_q_proj_loraB_weight_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("lora_out_49_cast_fp16")]; |
| 781 | tensor<fp16, [1, 1280, 1, 1]> query_11_cast_fp16 = add(x = pretrained_out_49_cast_fp16, y = lora_out_49_cast_fp16)[name = tensor<string, []>("query_11_cast_fp16")]; |
| 782 | tensor<string, []> pretrained_out_51_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_51_pad_type_0"), val = tensor<string, []>("valid")]; |
| 783 | tensor<int32, [2]> pretrained_out_51_strides_0 = const()[name = tensor<string, []>("pretrained_out_51_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 784 | tensor<int32, [4]> pretrained_out_51_pad_0 = const()[name = tensor<string, []>("pretrained_out_51_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 785 | tensor<int32, [2]> pretrained_out_51_dilations_0 = const()[name = tensor<string, []>("pretrained_out_51_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 786 | tensor<int32, []> pretrained_out_51_groups_0 = const()[name = tensor<string, []>("pretrained_out_51_groups_0"), val = tensor<int32, []>(1)]; |
| 787 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166897024))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167716288))), name = tensor<string, []>("layers_2_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 788 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_51_cast_fp16 = conv(dilations = pretrained_out_51_dilations_0, groups = pretrained_out_51_groups_0, pad = pretrained_out_51_pad_0, pad_type = pretrained_out_51_pad_type_0, strides = pretrained_out_51_strides_0, weight = layers_2_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_51_cast_fp16")]; |
| 789 | tensor<string, []> input_73_pad_type_0 = const()[name = tensor<string, []>("input_73_pad_type_0"), val = tensor<string, []>("valid")]; |
| 790 | tensor<int32, [2]> input_73_strides_0 = const()[name = tensor<string, []>("input_73_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 791 | tensor<int32, [4]> input_73_pad_0 = const()[name = tensor<string, []>("input_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 792 | tensor<int32, [2]> input_73_dilations_0 = const()[name = tensor<string, []>("input_73_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 793 | tensor<int32, []> input_73_groups_0 = const()[name = tensor<string, []>("input_73_groups_0"), val = tensor<int32, []>(1)]; |
| 794 | tensor<fp16, [16, 1280, 1, 1]> layers_2_encoder_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167716416)))]; |
| 795 | tensor<fp16, [1, 16, 1, 1500]> input_73_cast_fp16 = conv(dilations = input_73_dilations_0, groups = input_73_groups_0, pad = input_73_pad_0, pad_type = input_73_pad_type_0, strides = input_73_strides_0, weight = layers_2_encoder_attn_k_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_73_cast_fp16")]; |
| 796 | tensor<string, []> lora_out_51_pad_type_0 = const()[name = tensor<string, []>("lora_out_51_pad_type_0"), val = tensor<string, []>("valid")]; |
| 797 | tensor<int32, [2]> lora_out_51_strides_0 = const()[name = tensor<string, []>("lora_out_51_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 798 | tensor<int32, [4]> lora_out_51_pad_0 = const()[name = tensor<string, []>("lora_out_51_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 799 | tensor<int32, [2]> lora_out_51_dilations_0 = const()[name = tensor<string, []>("lora_out_51_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 800 | tensor<int32, []> lora_out_51_groups_0 = const()[name = tensor<string, []>("lora_out_51_groups_0"), val = tensor<int32, []>(1)]; |
| 801 | tensor<fp16, [1280, 16, 1, 1]> layers_2_encoder_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167757440)))]; |
| 802 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_51_cast_fp16 = conv(dilations = lora_out_51_dilations_0, groups = lora_out_51_groups_0, pad = lora_out_51_pad_0, pad_type = lora_out_51_pad_type_0, strides = lora_out_51_strides_0, weight = layers_2_encoder_attn_k_proj_loraB_weight_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("lora_out_51_cast_fp16")]; |
| 803 | tensor<fp16, [1, 1280, 1, 1500]> key_11_cast_fp16 = add(x = pretrained_out_51_cast_fp16, y = lora_out_51_cast_fp16)[name = tensor<string, []>("key_11_cast_fp16")]; |
| 804 | tensor<string, []> pretrained_out_53_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_53_pad_type_0"), val = tensor<string, []>("valid")]; |
| 805 | tensor<int32, [2]> pretrained_out_53_strides_0 = const()[name = tensor<string, []>("pretrained_out_53_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 806 | tensor<int32, [4]> pretrained_out_53_pad_0 = const()[name = tensor<string, []>("pretrained_out_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 807 | tensor<int32, [2]> pretrained_out_53_dilations_0 = const()[name = tensor<string, []>("pretrained_out_53_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 808 | tensor<int32, []> pretrained_out_53_groups_0 = const()[name = tensor<string, []>("pretrained_out_53_groups_0"), val = tensor<int32, []>(1)]; |
| 809 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167798464))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168617728))), name = tensor<string, []>("layers_2_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 810 | tensor<fp16, [1280]> layers_2_encoder_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168617856)))]; |
| 811 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_53_cast_fp16 = conv(bias = layers_2_encoder_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_53_dilations_0, groups = pretrained_out_53_groups_0, pad = pretrained_out_53_pad_0, pad_type = pretrained_out_53_pad_type_0, strides = pretrained_out_53_strides_0, weight = layers_2_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_53_cast_fp16")]; |
| 812 | tensor<string, []> input_75_pad_type_0 = const()[name = tensor<string, []>("input_75_pad_type_0"), val = tensor<string, []>("valid")]; |
| 813 | tensor<int32, [2]> input_75_strides_0 = const()[name = tensor<string, []>("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 814 | tensor<int32, [4]> input_75_pad_0 = const()[name = tensor<string, []>("input_75_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 815 | tensor<int32, [2]> input_75_dilations_0 = const()[name = tensor<string, []>("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 816 | tensor<int32, []> input_75_groups_0 = const()[name = tensor<string, []>("input_75_groups_0"), val = tensor<int32, []>(1)]; |
| 817 | tensor<fp16, [16, 1280, 1, 1]> layers_2_encoder_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168620480)))]; |
| 818 | tensor<fp16, [1, 16, 1, 1500]> input_75_cast_fp16 = conv(dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = layers_2_encoder_attn_v_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_75_cast_fp16")]; |
| 819 | tensor<string, []> lora_out_53_pad_type_0 = const()[name = tensor<string, []>("lora_out_53_pad_type_0"), val = tensor<string, []>("valid")]; |
| 820 | tensor<int32, [2]> lora_out_53_strides_0 = const()[name = tensor<string, []>("lora_out_53_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 821 | tensor<int32, [4]> lora_out_53_pad_0 = const()[name = tensor<string, []>("lora_out_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 822 | tensor<int32, [2]> lora_out_53_dilations_0 = const()[name = tensor<string, []>("lora_out_53_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 823 | tensor<int32, []> lora_out_53_groups_0 = const()[name = tensor<string, []>("lora_out_53_groups_0"), val = tensor<int32, []>(1)]; |
| 824 | tensor<fp16, [1280, 16, 1, 1]> layers_2_encoder_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168661504)))]; |
| 825 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_53_cast_fp16 = conv(dilations = lora_out_53_dilations_0, groups = lora_out_53_groups_0, pad = lora_out_53_pad_0, pad_type = lora_out_53_pad_type_0, strides = lora_out_53_strides_0, weight = layers_2_encoder_attn_v_proj_loraB_weight_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("lora_out_53_cast_fp16")]; |
| 826 | tensor<fp16, [1, 1280, 1, 1500]> value_11_cast_fp16 = add(x = pretrained_out_53_cast_fp16, y = lora_out_53_cast_fp16)[name = tensor<string, []>("value_11_cast_fp16")]; |
| 827 | tensor<int32, [4]> var_1072 = const()[name = tensor<string, []>("op_1072"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 828 | tensor<fp16, [1, 20, 64, 1]> mh_q_11_cast_fp16 = reshape(shape = var_1072, x = query_11_cast_fp16)[name = tensor<string, []>("mh_q_11_cast_fp16")]; |
| 829 | tensor<fp16, []> var_1074_to_fp16 = const()[name = tensor<string, []>("op_1074_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 830 | tensor<fp16, [1, 20, 64, 1]> var_1075_cast_fp16 = mul(x = mh_q_11_cast_fp16, y = var_1074_to_fp16)[name = tensor<string, []>("op_1075_cast_fp16")]; |
| 831 | tensor<int32, [4]> var_1076 = const()[name = tensor<string, []>("op_1076"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 832 | tensor<fp16, [1, 20, 64, 1500]> var_1077_cast_fp16 = reshape(shape = var_1076, x = key_11_cast_fp16)[name = tensor<string, []>("op_1077_cast_fp16")]; |
| 833 | tensor<bool, []> mh_w_17_transpose_x_0 = const()[name = tensor<string, []>("mh_w_17_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 834 | tensor<bool, []> mh_w_17_transpose_y_0 = const()[name = tensor<string, []>("mh_w_17_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 835 | tensor<fp16, [1, 20, 1, 1500]> mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_1075_cast_fp16, y = var_1077_cast_fp16)[name = tensor<string, []>("mh_w_17_cast_fp16")]; |
| 836 | tensor<fp16, [1, 20, 1, 1500]> obj_41_cast_fp16 = softmax(axis = var_812, x = mh_w_17_cast_fp16)[name = tensor<string, []>("obj_41_cast_fp16")]; |
| 837 | tensor<int32, [4]> var_1081 = const()[name = tensor<string, []>("op_1081"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 838 | tensor<fp16, [1, 20, 64, 1500]> var_1082_cast_fp16 = reshape(shape = var_1081, x = value_11_cast_fp16)[name = tensor<string, []>("op_1082_cast_fp16")]; |
| 839 | tensor<bool, []> attn_11_transpose_x_0 = const()[name = tensor<string, []>("attn_11_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 840 | tensor<bool, []> attn_11_transpose_y_0 = const()[name = tensor<string, []>("attn_11_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 841 | tensor<fp16, [1, 20, 64, 1]> attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_1082_cast_fp16, y = obj_41_cast_fp16)[name = tensor<string, []>("attn_11_cast_fp16")]; |
| 842 | tensor<int32, [4]> var_1085 = const()[name = tensor<string, []>("op_1085"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 843 | tensor<fp16, [1, 1280, 1, 1]> input_77_cast_fp16 = reshape(shape = var_1085, x = attn_11_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")]; |
| 844 | tensor<string, []> pretrained_out_55_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_55_pad_type_0"), val = tensor<string, []>("valid")]; |
| 845 | tensor<int32, [2]> pretrained_out_55_strides_0 = const()[name = tensor<string, []>("pretrained_out_55_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 846 | tensor<int32, [4]> pretrained_out_55_pad_0 = const()[name = tensor<string, []>("pretrained_out_55_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 847 | tensor<int32, [2]> pretrained_out_55_dilations_0 = const()[name = tensor<string, []>("pretrained_out_55_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 848 | tensor<int32, []> pretrained_out_55_groups_0 = const()[name = tensor<string, []>("pretrained_out_55_groups_0"), val = tensor<int32, []>(1)]; |
| 849 | tensor<fp16, [1280, 1280, 1, 1]> layers_2_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168702528))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169521792))), name = tensor<string, []>("layers_2_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 850 | tensor<fp16, [1280]> layers_2_encoder_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169521920)))]; |
| 851 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_55_cast_fp16 = conv(bias = layers_2_encoder_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_55_dilations_0, groups = pretrained_out_55_groups_0, pad = pretrained_out_55_pad_0, pad_type = pretrained_out_55_pad_type_0, strides = pretrained_out_55_strides_0, weight = layers_2_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_77_cast_fp16)[name = tensor<string, []>("pretrained_out_55_cast_fp16")]; |
| 852 | tensor<string, []> input_79_pad_type_0 = const()[name = tensor<string, []>("input_79_pad_type_0"), val = tensor<string, []>("valid")]; |
| 853 | tensor<int32, [2]> input_79_strides_0 = const()[name = tensor<string, []>("input_79_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 854 | tensor<int32, [4]> input_79_pad_0 = const()[name = tensor<string, []>("input_79_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 855 | tensor<int32, [2]> input_79_dilations_0 = const()[name = tensor<string, []>("input_79_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 856 | tensor<int32, []> input_79_groups_0 = const()[name = tensor<string, []>("input_79_groups_0"), val = tensor<int32, []>(1)]; |
| 857 | tensor<fp16, [16, 1280, 1, 1]> layers_2_encoder_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169524544)))]; |
| 858 | tensor<fp16, [1, 16, 1, 1]> input_79_cast_fp16 = conv(dilations = input_79_dilations_0, groups = input_79_groups_0, pad = input_79_pad_0, pad_type = input_79_pad_type_0, strides = input_79_strides_0, weight = layers_2_encoder_attn_o_proj_loraA_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")]; |
| 859 | tensor<string, []> lora_out_55_pad_type_0 = const()[name = tensor<string, []>("lora_out_55_pad_type_0"), val = tensor<string, []>("valid")]; |
| 860 | tensor<int32, [2]> lora_out_55_strides_0 = const()[name = tensor<string, []>("lora_out_55_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 861 | tensor<int32, [4]> lora_out_55_pad_0 = const()[name = tensor<string, []>("lora_out_55_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 862 | tensor<int32, [2]> lora_out_55_dilations_0 = const()[name = tensor<string, []>("lora_out_55_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 863 | tensor<int32, []> lora_out_55_groups_0 = const()[name = tensor<string, []>("lora_out_55_groups_0"), val = tensor<int32, []>(1)]; |
| 864 | tensor<fp16, [1280, 16, 1, 1]> layers_2_encoder_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_encoder_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169565568)))]; |
| 865 | tensor<fp16, [1, 1280, 1, 1]> lora_out_55_cast_fp16 = conv(dilations = lora_out_55_dilations_0, groups = lora_out_55_groups_0, pad = lora_out_55_pad_0, pad_type = lora_out_55_pad_type_0, strides = lora_out_55_strides_0, weight = layers_2_encoder_attn_o_proj_loraB_weight_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("lora_out_55_cast_fp16")]; |
| 866 | tensor<fp16, [1, 1280, 1, 1]> obj_39_cast_fp16 = add(x = pretrained_out_55_cast_fp16, y = lora_out_55_cast_fp16)[name = tensor<string, []>("obj_39_cast_fp16")]; |
| 867 | tensor<fp16, [1, 1280, 1, 1]> inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = obj_39_cast_fp16)[name = tensor<string, []>("inputs_17_cast_fp16")]; |
| 868 | tensor<int32, [1]> out_17_axes_0 = const()[name = tensor<string, []>("out_17_axes_0"), val = tensor<int32, [1]>([1])]; |
| 869 | tensor<fp16, []> var_1122_to_fp16 = const()[name = tensor<string, []>("op_1122_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 870 | tensor<fp16, [1, 1280, 1, 1]> out_17_cast_fp16 = layer_norm(axes = out_17_axes_0, epsilon = var_1122_to_fp16, x = inputs_17_cast_fp16)[name = tensor<string, []>("out_17_cast_fp16")]; |
| 871 | tensor<fp16, [1280]> input_81_gamma_0_to_fp16 = const()[name = tensor<string, []>("input_81_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169606592)))]; |
| 872 | tensor<fp16, [1280]> input_81_beta_0_to_fp16 = const()[name = tensor<string, []>("input_81_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169609216)))]; |
| 873 | tensor<fp16, []> input_81_epsilon_0_to_fp16 = const()[name = tensor<string, []>("input_81_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 874 | tensor<fp16, [1, 1280, 1, 1]> input_81_cast_fp16 = batch_norm(beta = input_81_beta_0_to_fp16, epsilon = input_81_epsilon_0_to_fp16, gamma = input_81_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")]; |
| 875 | tensor<string, []> pretrained_out_57_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_57_pad_type_0"), val = tensor<string, []>("valid")]; |
| 876 | tensor<int32, [2]> pretrained_out_57_strides_0 = const()[name = tensor<string, []>("pretrained_out_57_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 877 | tensor<int32, [4]> pretrained_out_57_pad_0 = const()[name = tensor<string, []>("pretrained_out_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 878 | tensor<int32, [2]> pretrained_out_57_dilations_0 = const()[name = tensor<string, []>("pretrained_out_57_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 879 | tensor<int32, []> pretrained_out_57_groups_0 = const()[name = tensor<string, []>("pretrained_out_57_groups_0"), val = tensor<int32, []>(1)]; |
| 880 | tensor<fp16, [5120, 1280, 1, 1]> layers_2_fc1_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169611840))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172888704))), name = tensor<string, []>("layers_2_fc1_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([5120, 1280, 1, 1])]; |
| 881 | tensor<fp16, [5120]> layers_2_fc1_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_fc1_pretrained_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172888832)))]; |
| 882 | tensor<fp16, [1, 5120, 1, 1]> pretrained_out_57_cast_fp16 = conv(bias = layers_2_fc1_pretrained_bias_to_fp16, dilations = pretrained_out_57_dilations_0, groups = pretrained_out_57_groups_0, pad = pretrained_out_57_pad_0, pad_type = pretrained_out_57_pad_type_0, strides = pretrained_out_57_strides_0, weight = layers_2_fc1_pretrained_weight_to_fp16_palettized, x = input_81_cast_fp16)[name = tensor<string, []>("pretrained_out_57_cast_fp16")]; |
| 883 | tensor<string, []> input_83_pad_type_0 = const()[name = tensor<string, []>("input_83_pad_type_0"), val = tensor<string, []>("valid")]; |
| 884 | tensor<int32, [2]> input_83_strides_0 = const()[name = tensor<string, []>("input_83_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 885 | tensor<int32, [4]> input_83_pad_0 = const()[name = tensor<string, []>("input_83_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 886 | tensor<int32, [2]> input_83_dilations_0 = const()[name = tensor<string, []>("input_83_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 887 | tensor<int32, []> input_83_groups_0 = const()[name = tensor<string, []>("input_83_groups_0"), val = tensor<int32, []>(1)]; |
| 888 | tensor<fp16, [16, 1280, 1, 1]> layers_2_fc1_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_fc1_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172899136)))]; |
| 889 | tensor<fp16, [1, 16, 1, 1]> input_83_cast_fp16 = conv(dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = layers_2_fc1_loraA_weight_to_fp16, x = input_81_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")]; |
| 890 | tensor<string, []> lora_out_57_pad_type_0 = const()[name = tensor<string, []>("lora_out_57_pad_type_0"), val = tensor<string, []>("valid")]; |
| 891 | tensor<int32, [2]> lora_out_57_strides_0 = const()[name = tensor<string, []>("lora_out_57_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 892 | tensor<int32, [4]> lora_out_57_pad_0 = const()[name = tensor<string, []>("lora_out_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 893 | tensor<int32, [2]> lora_out_57_dilations_0 = const()[name = tensor<string, []>("lora_out_57_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 894 | tensor<int32, []> lora_out_57_groups_0 = const()[name = tensor<string, []>("lora_out_57_groups_0"), val = tensor<int32, []>(1)]; |
| 895 | tensor<fp16, [5120, 16, 1, 1]> layers_2_fc1_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_fc1_loraB_weight_to_fp16"), val = tensor<fp16, [5120, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172940160)))]; |
| 896 | tensor<fp16, [1, 5120, 1, 1]> lora_out_57_cast_fp16 = conv(dilations = lora_out_57_dilations_0, groups = lora_out_57_groups_0, pad = lora_out_57_pad_0, pad_type = lora_out_57_pad_type_0, strides = lora_out_57_strides_0, weight = layers_2_fc1_loraB_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("lora_out_57_cast_fp16")]; |
| 897 | tensor<fp16, [1, 5120, 1, 1]> input_85_cast_fp16 = add(x = pretrained_out_57_cast_fp16, y = lora_out_57_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")]; |
| 898 | tensor<string, []> input_87_mode_0 = const()[name = tensor<string, []>("input_87_mode_0"), val = tensor<string, []>("EXACT")]; |
| 899 | tensor<fp16, [1, 5120, 1, 1]> input_87_cast_fp16 = gelu(mode = input_87_mode_0, x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")]; |
| 900 | tensor<string, []> pretrained_out_59_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_59_pad_type_0"), val = tensor<string, []>("valid")]; |
| 901 | tensor<int32, [2]> pretrained_out_59_strides_0 = const()[name = tensor<string, []>("pretrained_out_59_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 902 | tensor<int32, [4]> pretrained_out_59_pad_0 = const()[name = tensor<string, []>("pretrained_out_59_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 903 | tensor<int32, [2]> pretrained_out_59_dilations_0 = const()[name = tensor<string, []>("pretrained_out_59_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 904 | tensor<int32, []> pretrained_out_59_groups_0 = const()[name = tensor<string, []>("pretrained_out_59_groups_0"), val = tensor<int32, []>(1)]; |
| 905 | tensor<fp16, [1280, 5120, 1, 1]> layers_2_fc2_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173104064))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176380928))), name = tensor<string, []>("layers_2_fc2_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 5120, 1, 1])]; |
| 906 | tensor<fp16, [1280]> layers_2_fc2_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_2_fc2_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176381056)))]; |
| 907 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_59_cast_fp16 = conv(bias = layers_2_fc2_pretrained_bias_to_fp16, dilations = pretrained_out_59_dilations_0, groups = pretrained_out_59_groups_0, pad = pretrained_out_59_pad_0, pad_type = pretrained_out_59_pad_type_0, strides = pretrained_out_59_strides_0, weight = layers_2_fc2_pretrained_weight_to_fp16_palettized, x = input_87_cast_fp16)[name = tensor<string, []>("pretrained_out_59_cast_fp16")]; |
| 908 | tensor<string, []> input_89_pad_type_0 = const()[name = tensor<string, []>("input_89_pad_type_0"), val = tensor<string, []>("valid")]; |
| 909 | tensor<int32, [2]> input_89_strides_0 = const()[name = tensor<string, []>("input_89_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 910 | tensor<int32, [4]> input_89_pad_0 = const()[name = tensor<string, []>("input_89_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 911 | tensor<int32, [2]> input_89_dilations_0 = const()[name = tensor<string, []>("input_89_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 912 | tensor<int32, []> input_89_groups_0 = const()[name = tensor<string, []>("input_89_groups_0"), val = tensor<int32, []>(1)]; |
| 913 | tensor<fp16, [16, 5120, 1, 1]> layers_2_fc2_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_fc2_loraA_weight_to_fp16"), val = tensor<fp16, [16, 5120, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176383680)))]; |
| 914 | tensor<fp16, [1, 16, 1, 1]> input_89_cast_fp16 = conv(dilations = input_89_dilations_0, groups = input_89_groups_0, pad = input_89_pad_0, pad_type = input_89_pad_type_0, strides = input_89_strides_0, weight = layers_2_fc2_loraA_weight_to_fp16, x = input_87_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")]; |
| 915 | tensor<string, []> lora_out_59_pad_type_0 = const()[name = tensor<string, []>("lora_out_59_pad_type_0"), val = tensor<string, []>("valid")]; |
| 916 | tensor<int32, [2]> lora_out_59_strides_0 = const()[name = tensor<string, []>("lora_out_59_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 917 | tensor<int32, [4]> lora_out_59_pad_0 = const()[name = tensor<string, []>("lora_out_59_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 918 | tensor<int32, [2]> lora_out_59_dilations_0 = const()[name = tensor<string, []>("lora_out_59_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 919 | tensor<int32, []> lora_out_59_groups_0 = const()[name = tensor<string, []>("lora_out_59_groups_0"), val = tensor<int32, []>(1)]; |
| 920 | tensor<fp16, [1280, 16, 1, 1]> layers_2_fc2_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_2_fc2_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176547584)))]; |
| 921 | tensor<fp16, [1, 1280, 1, 1]> lora_out_59_cast_fp16 = conv(dilations = lora_out_59_dilations_0, groups = lora_out_59_groups_0, pad = lora_out_59_pad_0, pad_type = lora_out_59_pad_type_0, strides = lora_out_59_strides_0, weight = layers_2_fc2_loraB_weight_to_fp16, x = input_89_cast_fp16)[name = tensor<string, []>("lora_out_59_cast_fp16")]; |
| 922 | tensor<fp16, [1, 1280, 1, 1]> hidden_states_7_cast_fp16 = add(x = pretrained_out_59_cast_fp16, y = lora_out_59_cast_fp16)[name = tensor<string, []>("hidden_states_7_cast_fp16")]; |
| 923 | tensor<fp16, [1, 1280, 1, 1]> inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor<string, []>("inputs_19_cast_fp16")]; |
| 924 | tensor<int32, []> var_1190 = const()[name = tensor<string, []>("op_1190"), val = tensor<int32, []>(3)]; |
| 925 | tensor<int32, [1]> out_19_axes_0 = const()[name = tensor<string, []>("out_19_axes_0"), val = tensor<int32, [1]>([1])]; |
| 926 | tensor<fp16, []> var_1216_to_fp16 = const()[name = tensor<string, []>("op_1216_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 927 | tensor<fp16, [1, 1280, 1, 1]> out_19_cast_fp16 = layer_norm(axes = out_19_axes_0, epsilon = var_1216_to_fp16, x = inputs_19_cast_fp16)[name = tensor<string, []>("out_19_cast_fp16")]; |
| 928 | tensor<fp16, [1280]> obj_43_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_43_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176588608)))]; |
| 929 | tensor<fp16, [1280]> obj_43_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_43_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176591232)))]; |
| 930 | tensor<fp16, []> obj_43_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_43_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 931 | tensor<fp16, [1, 1280, 1, 1]> obj_43_cast_fp16 = batch_norm(beta = obj_43_beta_0_to_fp16, epsilon = obj_43_epsilon_0_to_fp16, gamma = obj_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor<string, []>("obj_43_cast_fp16")]; |
| 932 | tensor<string, []> pretrained_out_61_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_61_pad_type_0"), val = tensor<string, []>("valid")]; |
| 933 | tensor<int32, [2]> pretrained_out_61_strides_0 = const()[name = tensor<string, []>("pretrained_out_61_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 934 | tensor<int32, [4]> pretrained_out_61_pad_0 = const()[name = tensor<string, []>("pretrained_out_61_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 935 | tensor<int32, [2]> pretrained_out_61_dilations_0 = const()[name = tensor<string, []>("pretrained_out_61_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 936 | tensor<int32, []> pretrained_out_61_groups_0 = const()[name = tensor<string, []>("pretrained_out_61_groups_0"), val = tensor<int32, []>(1)]; |
| 937 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_self_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176593856))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177413120))), name = tensor<string, []>("layers_3_self_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 938 | tensor<fp16, [1280]> layers_3_self_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177413248)))]; |
| 939 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_61_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_61_dilations_0, groups = pretrained_out_61_groups_0, pad = pretrained_out_61_pad_0, pad_type = pretrained_out_61_pad_type_0, strides = pretrained_out_61_strides_0, weight = layers_3_self_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_43_cast_fp16)[name = tensor<string, []>("pretrained_out_61_cast_fp16")]; |
| 940 | tensor<string, []> input_91_pad_type_0 = const()[name = tensor<string, []>("input_91_pad_type_0"), val = tensor<string, []>("valid")]; |
| 941 | tensor<int32, [2]> input_91_strides_0 = const()[name = tensor<string, []>("input_91_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 942 | tensor<int32, [4]> input_91_pad_0 = const()[name = tensor<string, []>("input_91_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 943 | tensor<int32, [2]> input_91_dilations_0 = const()[name = tensor<string, []>("input_91_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 944 | tensor<int32, []> input_91_groups_0 = const()[name = tensor<string, []>("input_91_groups_0"), val = tensor<int32, []>(1)]; |
| 945 | tensor<fp16, [16, 1280, 1, 1]> layers_3_self_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177415872)))]; |
| 946 | tensor<fp16, [1, 16, 1, 1]> input_91_cast_fp16 = conv(dilations = input_91_dilations_0, groups = input_91_groups_0, pad = input_91_pad_0, pad_type = input_91_pad_type_0, strides = input_91_strides_0, weight = layers_3_self_attn_q_proj_loraA_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")]; |
| 947 | tensor<string, []> lora_out_61_pad_type_0 = const()[name = tensor<string, []>("lora_out_61_pad_type_0"), val = tensor<string, []>("valid")]; |
| 948 | tensor<int32, [2]> lora_out_61_strides_0 = const()[name = tensor<string, []>("lora_out_61_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 949 | tensor<int32, [4]> lora_out_61_pad_0 = const()[name = tensor<string, []>("lora_out_61_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 950 | tensor<int32, [2]> lora_out_61_dilations_0 = const()[name = tensor<string, []>("lora_out_61_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 951 | tensor<int32, []> lora_out_61_groups_0 = const()[name = tensor<string, []>("lora_out_61_groups_0"), val = tensor<int32, []>(1)]; |
| 952 | tensor<fp16, [1280, 16, 1, 1]> layers_3_self_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177456896)))]; |
| 953 | tensor<fp16, [1, 1280, 1, 1]> lora_out_61_cast_fp16 = conv(dilations = lora_out_61_dilations_0, groups = lora_out_61_groups_0, pad = lora_out_61_pad_0, pad_type = lora_out_61_pad_type_0, strides = lora_out_61_strides_0, weight = layers_3_self_attn_q_proj_loraB_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("lora_out_61_cast_fp16")]; |
| 954 | tensor<fp16, [1, 1280, 1, 1]> query_13_cast_fp16 = add(x = pretrained_out_61_cast_fp16, y = lora_out_61_cast_fp16)[name = tensor<string, []>("query_13_cast_fp16")]; |
| 955 | tensor<string, []> pretrained_out_63_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_63_pad_type_0"), val = tensor<string, []>("valid")]; |
| 956 | tensor<int32, [2]> pretrained_out_63_strides_0 = const()[name = tensor<string, []>("pretrained_out_63_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 957 | tensor<int32, [4]> pretrained_out_63_pad_0 = const()[name = tensor<string, []>("pretrained_out_63_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 958 | tensor<int32, [2]> pretrained_out_63_dilations_0 = const()[name = tensor<string, []>("pretrained_out_63_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 959 | tensor<int32, []> pretrained_out_63_groups_0 = const()[name = tensor<string, []>("pretrained_out_63_groups_0"), val = tensor<int32, []>(1)]; |
| 960 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_self_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177497920))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178317184))), name = tensor<string, []>("layers_3_self_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 961 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_63_cast_fp16 = conv(dilations = pretrained_out_63_dilations_0, groups = pretrained_out_63_groups_0, pad = pretrained_out_63_pad_0, pad_type = pretrained_out_63_pad_type_0, strides = pretrained_out_63_strides_0, weight = layers_3_self_attn_k_proj_pretrained_weight_to_fp16_palettized, x = obj_43_cast_fp16)[name = tensor<string, []>("pretrained_out_63_cast_fp16")]; |
| 962 | tensor<string, []> input_93_pad_type_0 = const()[name = tensor<string, []>("input_93_pad_type_0"), val = tensor<string, []>("valid")]; |
| 963 | tensor<int32, [2]> input_93_strides_0 = const()[name = tensor<string, []>("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 964 | tensor<int32, [4]> input_93_pad_0 = const()[name = tensor<string, []>("input_93_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 965 | tensor<int32, [2]> input_93_dilations_0 = const()[name = tensor<string, []>("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 966 | tensor<int32, []> input_93_groups_0 = const()[name = tensor<string, []>("input_93_groups_0"), val = tensor<int32, []>(1)]; |
| 967 | tensor<fp16, [16, 1280, 1, 1]> layers_3_self_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178317312)))]; |
| 968 | tensor<fp16, [1, 16, 1, 1]> input_93_cast_fp16 = conv(dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = layers_3_self_attn_k_proj_loraA_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")]; |
| 969 | tensor<string, []> lora_out_63_pad_type_0 = const()[name = tensor<string, []>("lora_out_63_pad_type_0"), val = tensor<string, []>("valid")]; |
| 970 | tensor<int32, [2]> lora_out_63_strides_0 = const()[name = tensor<string, []>("lora_out_63_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 971 | tensor<int32, [4]> lora_out_63_pad_0 = const()[name = tensor<string, []>("lora_out_63_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 972 | tensor<int32, [2]> lora_out_63_dilations_0 = const()[name = tensor<string, []>("lora_out_63_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 973 | tensor<int32, []> lora_out_63_groups_0 = const()[name = tensor<string, []>("lora_out_63_groups_0"), val = tensor<int32, []>(1)]; |
| 974 | tensor<fp16, [1280, 16, 1, 1]> layers_3_self_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178358336)))]; |
| 975 | tensor<fp16, [1, 1280, 1, 1]> lora_out_63_cast_fp16 = conv(dilations = lora_out_63_dilations_0, groups = lora_out_63_groups_0, pad = lora_out_63_pad_0, pad_type = lora_out_63_pad_type_0, strides = lora_out_63_strides_0, weight = layers_3_self_attn_k_proj_loraB_weight_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("lora_out_63_cast_fp16")]; |
| 976 | tensor<fp16, [1, 1280, 1, 1]> current_key_cast_fp16 = add(x = pretrained_out_63_cast_fp16, y = lora_out_63_cast_fp16)[name = tensor<string, []>("current_key_cast_fp16")]; |
| 977 | tensor<string, []> pretrained_out_65_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_65_pad_type_0"), val = tensor<string, []>("valid")]; |
| 978 | tensor<int32, [2]> pretrained_out_65_strides_0 = const()[name = tensor<string, []>("pretrained_out_65_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 979 | tensor<int32, [4]> pretrained_out_65_pad_0 = const()[name = tensor<string, []>("pretrained_out_65_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 980 | tensor<int32, [2]> pretrained_out_65_dilations_0 = const()[name = tensor<string, []>("pretrained_out_65_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 981 | tensor<int32, []> pretrained_out_65_groups_0 = const()[name = tensor<string, []>("pretrained_out_65_groups_0"), val = tensor<int32, []>(1)]; |
| 982 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_self_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178399360))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179218624))), name = tensor<string, []>("layers_3_self_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 983 | tensor<fp16, [1280]> layers_3_self_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179218752)))]; |
| 984 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_65_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_65_dilations_0, groups = pretrained_out_65_groups_0, pad = pretrained_out_65_pad_0, pad_type = pretrained_out_65_pad_type_0, strides = pretrained_out_65_strides_0, weight = layers_3_self_attn_v_proj_pretrained_weight_to_fp16_palettized, x = obj_43_cast_fp16)[name = tensor<string, []>("pretrained_out_65_cast_fp16")]; |
| 985 | tensor<string, []> input_95_pad_type_0 = const()[name = tensor<string, []>("input_95_pad_type_0"), val = tensor<string, []>("valid")]; |
| 986 | tensor<int32, [2]> input_95_strides_0 = const()[name = tensor<string, []>("input_95_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 987 | tensor<int32, [4]> input_95_pad_0 = const()[name = tensor<string, []>("input_95_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 988 | tensor<int32, [2]> input_95_dilations_0 = const()[name = tensor<string, []>("input_95_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 989 | tensor<int32, []> input_95_groups_0 = const()[name = tensor<string, []>("input_95_groups_0"), val = tensor<int32, []>(1)]; |
| 990 | tensor<fp16, [16, 1280, 1, 1]> layers_3_self_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179221376)))]; |
| 991 | tensor<fp16, [1, 16, 1, 1]> input_95_cast_fp16 = conv(dilations = input_95_dilations_0, groups = input_95_groups_0, pad = input_95_pad_0, pad_type = input_95_pad_type_0, strides = input_95_strides_0, weight = layers_3_self_attn_v_proj_loraA_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")]; |
| 992 | tensor<string, []> lora_out_65_pad_type_0 = const()[name = tensor<string, []>("lora_out_65_pad_type_0"), val = tensor<string, []>("valid")]; |
| 993 | tensor<int32, [2]> lora_out_65_strides_0 = const()[name = tensor<string, []>("lora_out_65_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 994 | tensor<int32, [4]> lora_out_65_pad_0 = const()[name = tensor<string, []>("lora_out_65_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 995 | tensor<int32, [2]> lora_out_65_dilations_0 = const()[name = tensor<string, []>("lora_out_65_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 996 | tensor<int32, []> lora_out_65_groups_0 = const()[name = tensor<string, []>("lora_out_65_groups_0"), val = tensor<int32, []>(1)]; |
| 997 | tensor<fp16, [1280, 16, 1, 1]> layers_3_self_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179262400)))]; |
| 998 | tensor<fp16, [1, 1280, 1, 1]> lora_out_65_cast_fp16 = conv(dilations = lora_out_65_dilations_0, groups = lora_out_65_groups_0, pad = lora_out_65_pad_0, pad_type = lora_out_65_pad_type_0, strides = lora_out_65_strides_0, weight = layers_3_self_attn_v_proj_loraB_weight_to_fp16, x = input_95_cast_fp16)[name = tensor<string, []>("lora_out_65_cast_fp16")]; |
| 999 | tensor<fp16, [1, 1280, 1, 1]> current_value_cast_fp16 = add(x = pretrained_out_65_cast_fp16, y = lora_out_65_cast_fp16)[name = tensor<string, []>("current_value_cast_fp16")]; |
| 1000 | tensor<fp16, [1, 1280, 1, 448]> var_1302_cast_fp16 = mul(x = current_key_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_1302_cast_fp16")]; |
| 1001 | tensor<fp16, [1, 1280, 1, 448]> var_1304_cast_fp16 = mul(x = var_47_cast_fp16_3, y = var_177_cast_fp16)[name = tensor<string, []>("op_1304_cast_fp16")]; |
| 1002 | tensor<fp16, [1, 1280, 1, 448]> key_13_cast_fp16 = add(x = var_1302_cast_fp16, y = var_1304_cast_fp16)[name = tensor<string, []>("key_13_cast_fp16")]; |
| 1003 | tensor<fp16, [1, 1280, 1, 448]> var_1306_cast_fp16 = mul(x = current_value_cast_fp16, y = var_174_cast_fp16)[name = tensor<string, []>("op_1306_cast_fp16")]; |
| 1004 | tensor<fp16, [1, 1280, 1, 448]> var_1308_cast_fp16 = mul(x = var_54_cast_fp16_3, y = var_177_cast_fp16)[name = tensor<string, []>("op_1308_cast_fp16")]; |
| 1005 | tensor<fp16, [1, 1280, 1, 448]> value_13_cast_fp16 = add(x = var_1306_cast_fp16, y = var_1308_cast_fp16)[name = tensor<string, []>("value_13_cast_fp16")]; |
| 1006 | tensor<int32, [4]> var_1311 = const()[name = tensor<string, []>("op_1311"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1007 | tensor<fp16, [1, 20, 64, 1]> mh_q_13_cast_fp16 = reshape(shape = var_1311, x = query_13_cast_fp16)[name = tensor<string, []>("mh_q_13_cast_fp16")]; |
| 1008 | tensor<fp16, []> var_1313_to_fp16 = const()[name = tensor<string, []>("op_1313_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 1009 | tensor<fp16, [1, 20, 64, 1]> var_1314_cast_fp16 = mul(x = mh_q_13_cast_fp16, y = var_1313_to_fp16)[name = tensor<string, []>("op_1314_cast_fp16")]; |
| 1010 | tensor<int32, [4]> var_1315 = const()[name = tensor<string, []>("op_1315"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1011 | tensor<fp16, [1, 20, 64, 448]> var_1316_cast_fp16 = reshape(shape = var_1315, x = key_13_cast_fp16)[name = tensor<string, []>("op_1316_cast_fp16")]; |
| 1012 | tensor<bool, []> mh_w_19_transpose_x_0 = const()[name = tensor<string, []>("mh_w_19_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 1013 | tensor<bool, []> mh_w_19_transpose_y_0 = const()[name = tensor<string, []>("mh_w_19_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 1014 | tensor<fp16, [1, 20, 1, 448]> mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_1314_cast_fp16, y = var_1316_cast_fp16)[name = tensor<string, []>("mh_w_19_cast_fp16")]; |
| 1015 | tensor<fp16, [1, 20, 1, 448]> mh_w_21_cast_fp16 = add(x = mh_w_19_cast_fp16, y = var_195_cast_fp16)[name = tensor<string, []>("mh_w_21_cast_fp16")]; |
| 1016 | tensor<fp16, [1, 20, 1, 448]> var_1324_cast_fp16 = softmax(axis = var_1190, x = mh_w_21_cast_fp16)[name = tensor<string, []>("op_1324_cast_fp16")]; |
| 1017 | tensor<int32, [4]> var_1325 = const()[name = tensor<string, []>("op_1325"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1018 | tensor<fp16, [1, 20, 64, 448]> var_1326_cast_fp16 = reshape(shape = var_1325, x = value_13_cast_fp16)[name = tensor<string, []>("op_1326_cast_fp16")]; |
| 1019 | tensor<bool, []> attn_13_transpose_x_0 = const()[name = tensor<string, []>("attn_13_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 1020 | tensor<bool, []> attn_13_transpose_y_0 = const()[name = tensor<string, []>("attn_13_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 1021 | tensor<fp16, [1, 20, 64, 1]> attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_1326_cast_fp16, y = var_1324_cast_fp16)[name = tensor<string, []>("attn_13_cast_fp16")]; |
| 1022 | tensor<int32, [4]> var_1329 = const()[name = tensor<string, []>("op_1329"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 1023 | tensor<fp16, [1, 1280, 1, 1]> input_97_cast_fp16 = reshape(shape = var_1329, x = attn_13_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")]; |
| 1024 | tensor<string, []> pretrained_out_67_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_67_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1025 | tensor<int32, [2]> pretrained_out_67_strides_0 = const()[name = tensor<string, []>("pretrained_out_67_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1026 | tensor<int32, [4]> pretrained_out_67_pad_0 = const()[name = tensor<string, []>("pretrained_out_67_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1027 | tensor<int32, [2]> pretrained_out_67_dilations_0 = const()[name = tensor<string, []>("pretrained_out_67_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1028 | tensor<int32, []> pretrained_out_67_groups_0 = const()[name = tensor<string, []>("pretrained_out_67_groups_0"), val = tensor<int32, []>(1)]; |
| 1029 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_self_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179303424))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180122688))), name = tensor<string, []>("layers_3_self_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 1030 | tensor<fp16, [1280]> layers_3_self_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180122816)))]; |
| 1031 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_67_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_67_dilations_0, groups = pretrained_out_67_groups_0, pad = pretrained_out_67_pad_0, pad_type = pretrained_out_67_pad_type_0, strides = pretrained_out_67_strides_0, weight = layers_3_self_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_97_cast_fp16)[name = tensor<string, []>("pretrained_out_67_cast_fp16")]; |
| 1032 | tensor<string, []> input_99_pad_type_0 = const()[name = tensor<string, []>("input_99_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1033 | tensor<int32, [2]> input_99_strides_0 = const()[name = tensor<string, []>("input_99_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1034 | tensor<int32, [4]> input_99_pad_0 = const()[name = tensor<string, []>("input_99_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1035 | tensor<int32, [2]> input_99_dilations_0 = const()[name = tensor<string, []>("input_99_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1036 | tensor<int32, []> input_99_groups_0 = const()[name = tensor<string, []>("input_99_groups_0"), val = tensor<int32, []>(1)]; |
| 1037 | tensor<fp16, [16, 1280, 1, 1]> layers_3_self_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180125440)))]; |
| 1038 | tensor<fp16, [1, 16, 1, 1]> input_99_cast_fp16 = conv(dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = layers_3_self_attn_o_proj_loraA_weight_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")]; |
| 1039 | tensor<string, []> lora_out_67_pad_type_0 = const()[name = tensor<string, []>("lora_out_67_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1040 | tensor<int32, [2]> lora_out_67_strides_0 = const()[name = tensor<string, []>("lora_out_67_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1041 | tensor<int32, [4]> lora_out_67_pad_0 = const()[name = tensor<string, []>("lora_out_67_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1042 | tensor<int32, [2]> lora_out_67_dilations_0 = const()[name = tensor<string, []>("lora_out_67_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1043 | tensor<int32, []> lora_out_67_groups_0 = const()[name = tensor<string, []>("lora_out_67_groups_0"), val = tensor<int32, []>(1)]; |
| 1044 | tensor<fp16, [1280, 16, 1, 1]> layers_3_self_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_self_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180166464)))]; |
| 1045 | tensor<fp16, [1, 1280, 1, 1]> lora_out_67_cast_fp16 = conv(dilations = lora_out_67_dilations_0, groups = lora_out_67_groups_0, pad = lora_out_67_pad_0, pad_type = lora_out_67_pad_type_0, strides = lora_out_67_strides_0, weight = layers_3_self_attn_o_proj_loraB_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("lora_out_67_cast_fp16")]; |
| 1046 | tensor<fp16, [1, 1280, 1, 1]> obj_49_cast_fp16 = add(x = pretrained_out_67_cast_fp16, y = lora_out_67_cast_fp16)[name = tensor<string, []>("obj_49_cast_fp16")]; |
| 1047 | tensor<fp16, [1, 1280, 1, 1]> inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = obj_49_cast_fp16)[name = tensor<string, []>("inputs_21_cast_fp16")]; |
| 1048 | tensor<int32, [1]> out_21_axes_0 = const()[name = tensor<string, []>("out_21_axes_0"), val = tensor<int32, [1]>([1])]; |
| 1049 | tensor<fp16, []> var_1367_to_fp16 = const()[name = tensor<string, []>("op_1367_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1050 | tensor<fp16, [1, 1280, 1, 1]> out_21_cast_fp16 = layer_norm(axes = out_21_axes_0, epsilon = var_1367_to_fp16, x = inputs_21_cast_fp16)[name = tensor<string, []>("out_21_cast_fp16")]; |
| 1051 | tensor<fp16, [1280]> obj_51_gamma_0_to_fp16 = const()[name = tensor<string, []>("obj_51_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180207488)))]; |
| 1052 | tensor<fp16, [1280]> obj_51_beta_0_to_fp16 = const()[name = tensor<string, []>("obj_51_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180210112)))]; |
| 1053 | tensor<fp16, []> obj_51_epsilon_0_to_fp16 = const()[name = tensor<string, []>("obj_51_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1054 | tensor<fp16, [1, 1280, 1, 1]> obj_51_cast_fp16 = batch_norm(beta = obj_51_beta_0_to_fp16, epsilon = obj_51_epsilon_0_to_fp16, gamma = obj_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor<string, []>("obj_51_cast_fp16")]; |
| 1055 | tensor<string, []> pretrained_out_69_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_69_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1056 | tensor<int32, [2]> pretrained_out_69_strides_0 = const()[name = tensor<string, []>("pretrained_out_69_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1057 | tensor<int32, [4]> pretrained_out_69_pad_0 = const()[name = tensor<string, []>("pretrained_out_69_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1058 | tensor<int32, [2]> pretrained_out_69_dilations_0 = const()[name = tensor<string, []>("pretrained_out_69_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1059 | tensor<int32, []> pretrained_out_69_groups_0 = const()[name = tensor<string, []>("pretrained_out_69_groups_0"), val = tensor<int32, []>(1)]; |
| 1060 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180212736))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181032000))), name = tensor<string, []>("layers_3_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 1061 | tensor<fp16, [1280]> layers_3_encoder_attn_q_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_q_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181032128)))]; |
| 1062 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_69_cast_fp16 = conv(bias = layers_3_encoder_attn_q_proj_pretrained_bias_to_fp16, dilations = pretrained_out_69_dilations_0, groups = pretrained_out_69_groups_0, pad = pretrained_out_69_pad_0, pad_type = pretrained_out_69_pad_type_0, strides = pretrained_out_69_strides_0, weight = layers_3_encoder_attn_q_proj_pretrained_weight_to_fp16_palettized, x = obj_51_cast_fp16)[name = tensor<string, []>("pretrained_out_69_cast_fp16")]; |
| 1063 | tensor<string, []> input_101_pad_type_0 = const()[name = tensor<string, []>("input_101_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1064 | tensor<int32, [2]> input_101_strides_0 = const()[name = tensor<string, []>("input_101_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1065 | tensor<int32, [4]> input_101_pad_0 = const()[name = tensor<string, []>("input_101_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1066 | tensor<int32, [2]> input_101_dilations_0 = const()[name = tensor<string, []>("input_101_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1067 | tensor<int32, []> input_101_groups_0 = const()[name = tensor<string, []>("input_101_groups_0"), val = tensor<int32, []>(1)]; |
| 1068 | tensor<fp16, [16, 1280, 1, 1]> layers_3_encoder_attn_q_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_q_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181034752)))]; |
| 1069 | tensor<fp16, [1, 16, 1, 1]> input_101_cast_fp16 = conv(dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = layers_3_encoder_attn_q_proj_loraA_weight_to_fp16, x = obj_51_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")]; |
| 1070 | tensor<string, []> lora_out_69_pad_type_0 = const()[name = tensor<string, []>("lora_out_69_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1071 | tensor<int32, [2]> lora_out_69_strides_0 = const()[name = tensor<string, []>("lora_out_69_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1072 | tensor<int32, [4]> lora_out_69_pad_0 = const()[name = tensor<string, []>("lora_out_69_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1073 | tensor<int32, [2]> lora_out_69_dilations_0 = const()[name = tensor<string, []>("lora_out_69_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1074 | tensor<int32, []> lora_out_69_groups_0 = const()[name = tensor<string, []>("lora_out_69_groups_0"), val = tensor<int32, []>(1)]; |
| 1075 | tensor<fp16, [1280, 16, 1, 1]> layers_3_encoder_attn_q_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_q_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181075776)))]; |
| 1076 | tensor<fp16, [1, 1280, 1, 1]> lora_out_69_cast_fp16 = conv(dilations = lora_out_69_dilations_0, groups = lora_out_69_groups_0, pad = lora_out_69_pad_0, pad_type = lora_out_69_pad_type_0, strides = lora_out_69_strides_0, weight = layers_3_encoder_attn_q_proj_loraB_weight_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("lora_out_69_cast_fp16")]; |
| 1077 | tensor<fp16, [1, 1280, 1, 1]> query_cast_fp16 = add(x = pretrained_out_69_cast_fp16, y = lora_out_69_cast_fp16)[name = tensor<string, []>("query_cast_fp16")]; |
| 1078 | tensor<string, []> pretrained_out_71_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_71_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1079 | tensor<int32, [2]> pretrained_out_71_strides_0 = const()[name = tensor<string, []>("pretrained_out_71_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1080 | tensor<int32, [4]> pretrained_out_71_pad_0 = const()[name = tensor<string, []>("pretrained_out_71_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1081 | tensor<int32, [2]> pretrained_out_71_dilations_0 = const()[name = tensor<string, []>("pretrained_out_71_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1082 | tensor<int32, []> pretrained_out_71_groups_0 = const()[name = tensor<string, []>("pretrained_out_71_groups_0"), val = tensor<int32, []>(1)]; |
| 1083 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181116800))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181936064))), name = tensor<string, []>("layers_3_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 1084 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_71_cast_fp16 = conv(dilations = pretrained_out_71_dilations_0, groups = pretrained_out_71_groups_0, pad = pretrained_out_71_pad_0, pad_type = pretrained_out_71_pad_type_0, strides = pretrained_out_71_strides_0, weight = layers_3_encoder_attn_k_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_71_cast_fp16")]; |
| 1085 | tensor<string, []> input_103_pad_type_0 = const()[name = tensor<string, []>("input_103_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1086 | tensor<int32, [2]> input_103_strides_0 = const()[name = tensor<string, []>("input_103_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1087 | tensor<int32, [4]> input_103_pad_0 = const()[name = tensor<string, []>("input_103_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1088 | tensor<int32, [2]> input_103_dilations_0 = const()[name = tensor<string, []>("input_103_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1089 | tensor<int32, []> input_103_groups_0 = const()[name = tensor<string, []>("input_103_groups_0"), val = tensor<int32, []>(1)]; |
| 1090 | tensor<fp16, [16, 1280, 1, 1]> layers_3_encoder_attn_k_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_k_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181936192)))]; |
| 1091 | tensor<fp16, [1, 16, 1, 1500]> input_103_cast_fp16 = conv(dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = layers_3_encoder_attn_k_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_103_cast_fp16")]; |
| 1092 | tensor<string, []> lora_out_71_pad_type_0 = const()[name = tensor<string, []>("lora_out_71_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1093 | tensor<int32, [2]> lora_out_71_strides_0 = const()[name = tensor<string, []>("lora_out_71_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1094 | tensor<int32, [4]> lora_out_71_pad_0 = const()[name = tensor<string, []>("lora_out_71_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1095 | tensor<int32, [2]> lora_out_71_dilations_0 = const()[name = tensor<string, []>("lora_out_71_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1096 | tensor<int32, []> lora_out_71_groups_0 = const()[name = tensor<string, []>("lora_out_71_groups_0"), val = tensor<int32, []>(1)]; |
| 1097 | tensor<fp16, [1280, 16, 1, 1]> layers_3_encoder_attn_k_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_k_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181977216)))]; |
| 1098 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_71_cast_fp16 = conv(dilations = lora_out_71_dilations_0, groups = lora_out_71_groups_0, pad = lora_out_71_pad_0, pad_type = lora_out_71_pad_type_0, strides = lora_out_71_strides_0, weight = layers_3_encoder_attn_k_proj_loraB_weight_to_fp16, x = input_103_cast_fp16)[name = tensor<string, []>("lora_out_71_cast_fp16")]; |
| 1099 | tensor<fp16, [1, 1280, 1, 1500]> key_cast_fp16 = add(x = pretrained_out_71_cast_fp16, y = lora_out_71_cast_fp16)[name = tensor<string, []>("key_cast_fp16")]; |
| 1100 | tensor<string, []> pretrained_out_73_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_73_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1101 | tensor<int32, [2]> pretrained_out_73_strides_0 = const()[name = tensor<string, []>("pretrained_out_73_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1102 | tensor<int32, [4]> pretrained_out_73_pad_0 = const()[name = tensor<string, []>("pretrained_out_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1103 | tensor<int32, [2]> pretrained_out_73_dilations_0 = const()[name = tensor<string, []>("pretrained_out_73_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1104 | tensor<int32, []> pretrained_out_73_groups_0 = const()[name = tensor<string, []>("pretrained_out_73_groups_0"), val = tensor<int32, []>(1)]; |
| 1105 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182018240))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182837504))), name = tensor<string, []>("layers_3_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 1106 | tensor<fp16, [1280]> layers_3_encoder_attn_v_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_v_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182837632)))]; |
| 1107 | tensor<fp16, [1, 1280, 1, 1500]> pretrained_out_73_cast_fp16 = conv(bias = layers_3_encoder_attn_v_proj_pretrained_bias_to_fp16, dilations = pretrained_out_73_dilations_0, groups = pretrained_out_73_groups_0, pad = pretrained_out_73_pad_0, pad_type = pretrained_out_73_pad_type_0, strides = pretrained_out_73_strides_0, weight = layers_3_encoder_attn_v_proj_pretrained_weight_to_fp16_palettized, x = encoder_output_embeds)[name = tensor<string, []>("pretrained_out_73_cast_fp16")]; |
| 1108 | tensor<string, []> input_105_pad_type_0 = const()[name = tensor<string, []>("input_105_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1109 | tensor<int32, [2]> input_105_strides_0 = const()[name = tensor<string, []>("input_105_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1110 | tensor<int32, [4]> input_105_pad_0 = const()[name = tensor<string, []>("input_105_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1111 | tensor<int32, [2]> input_105_dilations_0 = const()[name = tensor<string, []>("input_105_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1112 | tensor<int32, []> input_105_groups_0 = const()[name = tensor<string, []>("input_105_groups_0"), val = tensor<int32, []>(1)]; |
| 1113 | tensor<fp16, [16, 1280, 1, 1]> layers_3_encoder_attn_v_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_v_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182840256)))]; |
| 1114 | tensor<fp16, [1, 16, 1, 1500]> input_105_cast_fp16 = conv(dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = layers_3_encoder_attn_v_proj_loraA_weight_to_fp16, x = encoder_output_embeds)[name = tensor<string, []>("input_105_cast_fp16")]; |
| 1115 | tensor<string, []> lora_out_73_pad_type_0 = const()[name = tensor<string, []>("lora_out_73_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1116 | tensor<int32, [2]> lora_out_73_strides_0 = const()[name = tensor<string, []>("lora_out_73_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1117 | tensor<int32, [4]> lora_out_73_pad_0 = const()[name = tensor<string, []>("lora_out_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1118 | tensor<int32, [2]> lora_out_73_dilations_0 = const()[name = tensor<string, []>("lora_out_73_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1119 | tensor<int32, []> lora_out_73_groups_0 = const()[name = tensor<string, []>("lora_out_73_groups_0"), val = tensor<int32, []>(1)]; |
| 1120 | tensor<fp16, [1280, 16, 1, 1]> layers_3_encoder_attn_v_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_v_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182881280)))]; |
| 1121 | tensor<fp16, [1, 1280, 1, 1500]> lora_out_73_cast_fp16 = conv(dilations = lora_out_73_dilations_0, groups = lora_out_73_groups_0, pad = lora_out_73_pad_0, pad_type = lora_out_73_pad_type_0, strides = lora_out_73_strides_0, weight = layers_3_encoder_attn_v_proj_loraB_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("lora_out_73_cast_fp16")]; |
| 1122 | tensor<fp16, [1, 1280, 1, 1500]> value_cast_fp16 = add(x = pretrained_out_73_cast_fp16, y = lora_out_73_cast_fp16)[name = tensor<string, []>("value_cast_fp16")]; |
| 1123 | tensor<int32, [4]> var_1450 = const()[name = tensor<string, []>("op_1450"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1124 | tensor<fp16, [1, 20, 64, 1]> mh_q_cast_fp16 = reshape(shape = var_1450, x = query_cast_fp16)[name = tensor<string, []>("mh_q_cast_fp16")]; |
| 1125 | tensor<fp16, []> var_1452_to_fp16 = const()[name = tensor<string, []>("op_1452_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| 1126 | tensor<fp16, [1, 20, 64, 1]> var_1453_cast_fp16 = mul(x = mh_q_cast_fp16, y = var_1452_to_fp16)[name = tensor<string, []>("op_1453_cast_fp16")]; |
| 1127 | tensor<int32, [4]> var_1454 = const()[name = tensor<string, []>("op_1454"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1128 | tensor<fp16, [1, 20, 64, 1500]> var_1455_cast_fp16 = reshape(shape = var_1454, x = key_cast_fp16)[name = tensor<string, []>("op_1455_cast_fp16")]; |
| 1129 | tensor<bool, []> mh_w_transpose_x_0 = const()[name = tensor<string, []>("mh_w_transpose_x_0"), val = tensor<bool, []>(true)]; |
| 1130 | tensor<bool, []> mh_w_transpose_y_0 = const()[name = tensor<string, []>("mh_w_transpose_y_0"), val = tensor<bool, []>(false)]; |
| 1131 | tensor<fp16, [1, 20, 1, 1500]> mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_1453_cast_fp16, y = var_1455_cast_fp16)[name = tensor<string, []>("mh_w_cast_fp16")]; |
| 1132 | tensor<fp16, [1, 20, 1, 1500]> obj_55_cast_fp16 = softmax(axis = var_1190, x = mh_w_cast_fp16)[name = tensor<string, []>("obj_55_cast_fp16")]; |
| 1133 | tensor<int32, [4]> var_1459 = const()[name = tensor<string, []>("op_1459"), val = tensor<int32, [4]>([1, 20, 64, -1])]; |
| 1134 | tensor<fp16, [1, 20, 64, 1500]> var_1460_cast_fp16 = reshape(shape = var_1459, x = value_cast_fp16)[name = tensor<string, []>("op_1460_cast_fp16")]; |
| 1135 | tensor<bool, []> attn_transpose_x_0 = const()[name = tensor<string, []>("attn_transpose_x_0"), val = tensor<bool, []>(false)]; |
| 1136 | tensor<bool, []> attn_transpose_y_0 = const()[name = tensor<string, []>("attn_transpose_y_0"), val = tensor<bool, []>(true)]; |
| 1137 | tensor<fp16, [1, 20, 64, 1]> attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_1460_cast_fp16, y = obj_55_cast_fp16)[name = tensor<string, []>("attn_cast_fp16")]; |
| 1138 | tensor<int32, [4]> var_1463 = const()[name = tensor<string, []>("op_1463"), val = tensor<int32, [4]>([1, 1280, 1, -1])]; |
| 1139 | tensor<fp16, [1, 1280, 1, 1]> input_107_cast_fp16 = reshape(shape = var_1463, x = attn_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")]; |
| 1140 | tensor<string, []> pretrained_out_75_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_75_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1141 | tensor<int32, [2]> pretrained_out_75_strides_0 = const()[name = tensor<string, []>("pretrained_out_75_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1142 | tensor<int32, [4]> pretrained_out_75_pad_0 = const()[name = tensor<string, []>("pretrained_out_75_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1143 | tensor<int32, [2]> pretrained_out_75_dilations_0 = const()[name = tensor<string, []>("pretrained_out_75_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1144 | tensor<int32, []> pretrained_out_75_groups_0 = const()[name = tensor<string, []>("pretrained_out_75_groups_0"), val = tensor<int32, []>(1)]; |
| 1145 | tensor<fp16, [1280, 1280, 1, 1]> layers_3_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [819200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182922304))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183741568))), name = tensor<string, []>("layers_3_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 1280, 1, 1])]; |
| 1146 | tensor<fp16, [1280]> layers_3_encoder_attn_o_proj_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_o_proj_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183741696)))]; |
| 1147 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_75_cast_fp16 = conv(bias = layers_3_encoder_attn_o_proj_pretrained_bias_to_fp16, dilations = pretrained_out_75_dilations_0, groups = pretrained_out_75_groups_0, pad = pretrained_out_75_pad_0, pad_type = pretrained_out_75_pad_type_0, strides = pretrained_out_75_strides_0, weight = layers_3_encoder_attn_o_proj_pretrained_weight_to_fp16_palettized, x = input_107_cast_fp16)[name = tensor<string, []>("pretrained_out_75_cast_fp16")]; |
| 1148 | tensor<string, []> input_109_pad_type_0 = const()[name = tensor<string, []>("input_109_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1149 | tensor<int32, [2]> input_109_strides_0 = const()[name = tensor<string, []>("input_109_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1150 | tensor<int32, [4]> input_109_pad_0 = const()[name = tensor<string, []>("input_109_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1151 | tensor<int32, [2]> input_109_dilations_0 = const()[name = tensor<string, []>("input_109_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1152 | tensor<int32, []> input_109_groups_0 = const()[name = tensor<string, []>("input_109_groups_0"), val = tensor<int32, []>(1)]; |
| 1153 | tensor<fp16, [16, 1280, 1, 1]> layers_3_encoder_attn_o_proj_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_o_proj_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183744320)))]; |
| 1154 | tensor<fp16, [1, 16, 1, 1]> input_109_cast_fp16 = conv(dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = layers_3_encoder_attn_o_proj_loraA_weight_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")]; |
| 1155 | tensor<string, []> lora_out_75_pad_type_0 = const()[name = tensor<string, []>("lora_out_75_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1156 | tensor<int32, [2]> lora_out_75_strides_0 = const()[name = tensor<string, []>("lora_out_75_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1157 | tensor<int32, [4]> lora_out_75_pad_0 = const()[name = tensor<string, []>("lora_out_75_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1158 | tensor<int32, [2]> lora_out_75_dilations_0 = const()[name = tensor<string, []>("lora_out_75_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1159 | tensor<int32, []> lora_out_75_groups_0 = const()[name = tensor<string, []>("lora_out_75_groups_0"), val = tensor<int32, []>(1)]; |
| 1160 | tensor<fp16, [1280, 16, 1, 1]> layers_3_encoder_attn_o_proj_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_encoder_attn_o_proj_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183785344)))]; |
| 1161 | tensor<fp16, [1, 1280, 1, 1]> lora_out_75_cast_fp16 = conv(dilations = lora_out_75_dilations_0, groups = lora_out_75_groups_0, pad = lora_out_75_pad_0, pad_type = lora_out_75_pad_type_0, strides = lora_out_75_strides_0, weight = layers_3_encoder_attn_o_proj_loraB_weight_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("lora_out_75_cast_fp16")]; |
| 1162 | tensor<fp16, [1, 1280, 1, 1]> obj_53_cast_fp16 = add(x = pretrained_out_75_cast_fp16, y = lora_out_75_cast_fp16)[name = tensor<string, []>("obj_53_cast_fp16")]; |
| 1163 | tensor<fp16, [1, 1280, 1, 1]> inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_53_cast_fp16)[name = tensor<string, []>("inputs_23_cast_fp16")]; |
| 1164 | tensor<int32, [1]> out_23_axes_0 = const()[name = tensor<string, []>("out_23_axes_0"), val = tensor<int32, [1]>([1])]; |
| 1165 | tensor<fp16, []> var_1500_to_fp16 = const()[name = tensor<string, []>("op_1500_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1166 | tensor<fp16, [1, 1280, 1, 1]> out_23_cast_fp16 = layer_norm(axes = out_23_axes_0, epsilon = var_1500_to_fp16, x = inputs_23_cast_fp16)[name = tensor<string, []>("out_23_cast_fp16")]; |
| 1167 | tensor<fp16, [1280]> input_111_gamma_0_to_fp16 = const()[name = tensor<string, []>("input_111_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183826368)))]; |
| 1168 | tensor<fp16, [1280]> input_111_beta_0_to_fp16 = const()[name = tensor<string, []>("input_111_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183828992)))]; |
| 1169 | tensor<fp16, []> input_111_epsilon_0_to_fp16 = const()[name = tensor<string, []>("input_111_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1170 | tensor<fp16, [1, 1280, 1, 1]> input_111_cast_fp16 = batch_norm(beta = input_111_beta_0_to_fp16, epsilon = input_111_epsilon_0_to_fp16, gamma = input_111_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")]; |
| 1171 | tensor<string, []> pretrained_out_77_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_77_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1172 | tensor<int32, [2]> pretrained_out_77_strides_0 = const()[name = tensor<string, []>("pretrained_out_77_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1173 | tensor<int32, [4]> pretrained_out_77_pad_0 = const()[name = tensor<string, []>("pretrained_out_77_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1174 | tensor<int32, [2]> pretrained_out_77_dilations_0 = const()[name = tensor<string, []>("pretrained_out_77_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1175 | tensor<int32, []> pretrained_out_77_groups_0 = const()[name = tensor<string, []>("pretrained_out_77_groups_0"), val = tensor<int32, []>(1)]; |
| 1176 | tensor<fp16, [5120, 1280, 1, 1]> layers_3_fc1_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3276800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183831616))), lut = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(187108480))), name = tensor<string, []>("layers_3_fc1_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([5120, 1280, 1, 1])]; |
| 1177 | tensor<fp16, [5120]> layers_3_fc1_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_fc1_pretrained_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(187108608)))]; |
| 1178 | tensor<fp16, [1, 5120, 1, 1]> pretrained_out_77_cast_fp16 = conv(bias = layers_3_fc1_pretrained_bias_to_fp16, dilations = pretrained_out_77_dilations_0, groups = pretrained_out_77_groups_0, pad = pretrained_out_77_pad_0, pad_type = pretrained_out_77_pad_type_0, strides = pretrained_out_77_strides_0, weight = layers_3_fc1_pretrained_weight_to_fp16_palettized, x = input_111_cast_fp16)[name = tensor<string, []>("pretrained_out_77_cast_fp16")]; |
| 1179 | tensor<string, []> input_113_pad_type_0 = const()[name = tensor<string, []>("input_113_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1180 | tensor<int32, [2]> input_113_strides_0 = const()[name = tensor<string, []>("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1181 | tensor<int32, [4]> input_113_pad_0 = const()[name = tensor<string, []>("input_113_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1182 | tensor<int32, [2]> input_113_dilations_0 = const()[name = tensor<string, []>("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1183 | tensor<int32, []> input_113_groups_0 = const()[name = tensor<string, []>("input_113_groups_0"), val = tensor<int32, []>(1)]; |
| 1184 | tensor<fp16, [16, 1280, 1, 1]> layers_3_fc1_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_fc1_loraA_weight_to_fp16"), val = tensor<fp16, [16, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(187118912)))]; |
| 1185 | tensor<fp16, [1, 16, 1, 1]> input_113_cast_fp16 = conv(dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = layers_3_fc1_loraA_weight_to_fp16, x = input_111_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")]; |
| 1186 | tensor<string, []> lora_out_77_pad_type_0 = const()[name = tensor<string, []>("lora_out_77_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1187 | tensor<int32, [2]> lora_out_77_strides_0 = const()[name = tensor<string, []>("lora_out_77_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1188 | tensor<int32, [4]> lora_out_77_pad_0 = const()[name = tensor<string, []>("lora_out_77_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1189 | tensor<int32, [2]> lora_out_77_dilations_0 = const()[name = tensor<string, []>("lora_out_77_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1190 | tensor<int32, []> lora_out_77_groups_0 = const()[name = tensor<string, []>("lora_out_77_groups_0"), val = tensor<int32, []>(1)]; |
| 1191 | tensor<fp16, [5120, 16, 1, 1]> layers_3_fc1_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_fc1_loraB_weight_to_fp16"), val = tensor<fp16, [5120, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(187159936)))]; |
| 1192 | tensor<fp16, [1, 5120, 1, 1]> lora_out_77_cast_fp16 = conv(dilations = lora_out_77_dilations_0, groups = lora_out_77_groups_0, pad = lora_out_77_pad_0, pad_type = lora_out_77_pad_type_0, strides = lora_out_77_strides_0, weight = layers_3_fc1_loraB_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("lora_out_77_cast_fp16")]; |
| 1193 | tensor<fp16, [1, 5120, 1, 1]> input_115_cast_fp16 = add(x = pretrained_out_77_cast_fp16, y = lora_out_77_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")]; |
| 1194 | tensor<string, []> input_117_mode_0 = const()[name = tensor<string, []>("input_117_mode_0"), val = tensor<string, []>("EXACT")]; |
| 1195 | tensor<fp16, [1, 5120, 1, 1]> input_117_cast_fp16 = gelu(mode = input_117_mode_0, x = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")]; |
| 1196 | tensor<string, []> pretrained_out_pad_type_0 = const()[name = tensor<string, []>("pretrained_out_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1197 | tensor<int32, [2]> pretrained_out_strides_0 = const()[name = tensor<string, []>("pretrained_out_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1198 | tensor<int32, [4]> pretrained_out_pad_0 = const()[name = tensor<string, []>("pretrained_out_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1199 | tensor<int32, [2]> pretrained_out_dilations_0 = const()[name = tensor<string, []>("pretrained_out_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1200 | tensor<int32, []> pretrained_out_groups_0 = const()[name = tensor<string, []>("pretrained_out_groups_0"), val = tensor<int32, []>(1)]; |
| 1201 | tensor<fp16, [1280, 5120, 1, 1]> layers_3_fc2_pretrained_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(187323840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192239104))), name = tensor<string, []>("layers_3_fc2_pretrained_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1280, 5120, 1, 1])]; |
| 1202 | tensor<fp16, [1280]> layers_3_fc2_pretrained_bias_to_fp16 = const()[name = tensor<string, []>("layers_3_fc2_pretrained_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192239296)))]; |
| 1203 | tensor<fp16, [1, 1280, 1, 1]> pretrained_out_cast_fp16 = conv(bias = layers_3_fc2_pretrained_bias_to_fp16, dilations = pretrained_out_dilations_0, groups = pretrained_out_groups_0, pad = pretrained_out_pad_0, pad_type = pretrained_out_pad_type_0, strides = pretrained_out_strides_0, weight = layers_3_fc2_pretrained_weight_to_fp16_palettized, x = input_117_cast_fp16)[name = tensor<string, []>("pretrained_out_cast_fp16")]; |
| 1204 | tensor<string, []> input_pad_type_0 = const()[name = tensor<string, []>("input_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1205 | tensor<int32, [2]> input_strides_0 = const()[name = tensor<string, []>("input_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1206 | tensor<int32, [4]> input_pad_0 = const()[name = tensor<string, []>("input_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1207 | tensor<int32, [2]> input_dilations_0 = const()[name = tensor<string, []>("input_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1208 | tensor<int32, []> input_groups_0 = const()[name = tensor<string, []>("input_groups_0"), val = tensor<int32, []>(1)]; |
| 1209 | tensor<fp16, [16, 5120, 1, 1]> layers_3_fc2_loraA_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_fc2_loraA_weight_to_fp16"), val = tensor<fp16, [16, 5120, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192241920)))]; |
| 1210 | tensor<fp16, [1, 16, 1, 1]> input_cast_fp16 = conv(dilations = input_dilations_0, groups = input_groups_0, pad = input_pad_0, pad_type = input_pad_type_0, strides = input_strides_0, weight = layers_3_fc2_loraA_weight_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("input_cast_fp16")]; |
| 1211 | tensor<string, []> lora_out_pad_type_0 = const()[name = tensor<string, []>("lora_out_pad_type_0"), val = tensor<string, []>("valid")]; |
| 1212 | tensor<int32, [2]> lora_out_strides_0 = const()[name = tensor<string, []>("lora_out_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1213 | tensor<int32, [4]> lora_out_pad_0 = const()[name = tensor<string, []>("lora_out_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1214 | tensor<int32, [2]> lora_out_dilations_0 = const()[name = tensor<string, []>("lora_out_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| 1215 | tensor<int32, []> lora_out_groups_0 = const()[name = tensor<string, []>("lora_out_groups_0"), val = tensor<int32, []>(1)]; |
| 1216 | tensor<fp16, [1280, 16, 1, 1]> layers_3_fc2_loraB_weight_to_fp16 = const()[name = tensor<string, []>("layers_3_fc2_loraB_weight_to_fp16"), val = tensor<fp16, [1280, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192405824)))]; |
| 1217 | tensor<fp16, [1, 1280, 1, 1]> lora_out_cast_fp16 = conv(dilations = lora_out_dilations_0, groups = lora_out_groups_0, pad = lora_out_pad_0, pad_type = lora_out_pad_type_0, strides = lora_out_strides_0, weight = layers_3_fc2_loraB_weight_to_fp16, x = input_cast_fp16)[name = tensor<string, []>("lora_out_cast_fp16")]; |
| 1218 | tensor<fp16, [1, 1280, 1, 1]> hidden_states_9_cast_fp16 = add(x = pretrained_out_cast_fp16, y = lora_out_cast_fp16)[name = tensor<string, []>("hidden_states_9_cast_fp16")]; |
| 1219 | tensor<fp16, [1, 1280, 1, 1]> inputs_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor<string, []>("inputs_cast_fp16")]; |
| 1220 | tensor<int32, [1]> out_axes_0 = const()[name = tensor<string, []>("out_axes_0"), val = tensor<int32, [1]>([1])]; |
| 1221 | tensor<fp16, []> var_1575_to_fp16 = const()[name = tensor<string, []>("op_1575_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1222 | tensor<fp16, [1, 1280, 1, 1]> out_cast_fp16 = layer_norm(axes = out_axes_0, epsilon = var_1575_to_fp16, x = inputs_cast_fp16)[name = tensor<string, []>("out_cast_fp16")]; |
| 1223 | tensor<fp16, [1280]> hidden_states_gamma_0_to_fp16 = const()[name = tensor<string, []>("hidden_states_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192446848)))]; |
| 1224 | tensor<fp16, [1280]> hidden_states_beta_0_to_fp16 = const()[name = tensor<string, []>("hidden_states_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192449472)))]; |
| 1225 | tensor<fp16, []> hidden_states_epsilon_0_to_fp16 = const()[name = tensor<string, []>("hidden_states_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)]; |
| 1226 | tensor<fp16, [1, 1280, 1, 1]> hidden_states_cast_fp16 = batch_norm(beta = hidden_states_beta_0_to_fp16, epsilon = hidden_states_epsilon_0_to_fp16, gamma = hidden_states_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor<string, []>("hidden_states_cast_fp16")]; |
| 1227 | tensor<int32, [1]> var_1586_axes_0 = const()[name = tensor<string, []>("op_1586_axes_0"), val = tensor<int32, [1]>([2])]; |
| 1228 | tensor<fp16, [1, 1280, 1]> var_1586_cast_fp16 = squeeze(axes = var_1586_axes_0, x = hidden_states_cast_fp16)[name = tensor<string, []>("op_1586_cast_fp16")]; |
| 1229 | tensor<int32, [3]> var_1589_perm_0 = const()[name = tensor<string, []>("op_1589_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| 1230 | tensor<fp16, [51866]> linear_0_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_0_bias_0_to_fp16"), val = tensor<fp16, [51866]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192452096)))]; |
| 1231 | tensor<fp16, [1, 1, 1280]> var_1589_cast_fp16 = transpose(perm = var_1589_perm_0, x = var_1586_cast_fp16)[name = tensor<string, []>("transpose_0")]; |
| 1232 | tensor<fp16, [1, 1, 51866]> logits = linear(bias = linear_0_bias_0_to_fp16, weight = embed_tokens_weight_to_fp16, x = var_1589_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")]; |
| 1233 | tensor<int32, []> var_1593 = const()[name = tensor<string, []>("op_1593"), val = tensor<int32, []>(1)]; |
| 1234 | tensor<bool, []> obj_59_interleave_0 = const()[name = tensor<string, []>("obj_59_interleave_0"), val = tensor<bool, []>(false)]; |
| 1235 | tensor<fp16, [1, 5120, 1, 1]> key_cache_updates = concat(axis = var_1593, interleave = obj_59_interleave_0, values = (current_key_1_cast_fp16, current_key_3_cast_fp16, current_key_5_cast_fp16, current_key_cast_fp16))[name = tensor<string, []>("obj_59_cast_fp16")]; |
| 1236 | tensor<int32, []> var_1596 = const()[name = tensor<string, []>("op_1596"), val = tensor<int32, []>(1)]; |
| 1237 | tensor<bool, []> obj_61_interleave_0 = const()[name = tensor<string, []>("obj_61_interleave_0"), val = tensor<bool, []>(false)]; |
| 1238 | tensor<fp16, [1, 5120, 1, 1]> value_cache_updates = concat(axis = var_1596, interleave = obj_61_interleave_0, values = (current_value_1_cast_fp16, current_value_3_cast_fp16, current_value_5_cast_fp16, current_value_cast_fp16))[name = tensor<string, []>("obj_61_cast_fp16")]; |
| 1239 | tensor<int32, [4]> var_1607_begin_0 = const()[name = tensor<string, []>("op_1607_begin_0"), val = tensor<int32, [4]>([0, 4, 0, 0])]; |
| 1240 | tensor<int32, [4]> var_1607_end_0 = const()[name = tensor<string, []>("op_1607_end_0"), val = tensor<int32, [4]>([1, 5, 1, 1500])]; |
| 1241 | tensor<bool, [4]> var_1607_end_mask_0 = const()[name = tensor<string, []>("op_1607_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1242 | tensor<fp16, [1, 1, 1, 1500]> var_1607_cast_fp16 = slice_by_index(begin = var_1607_begin_0, end = var_1607_end_0, end_mask = var_1607_end_mask_0, x = obj_41_cast_fp16)[name = tensor<string, []>("op_1607_cast_fp16")]; |
| 1243 | tensor<int32, [4]> var_1610_begin_0 = const()[name = tensor<string, []>("op_1610_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1244 | tensor<int32, [4]> var_1610_end_0 = const()[name = tensor<string, []>("op_1610_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1245 | tensor<bool, [4]> var_1610_end_mask_0 = const()[name = tensor<string, []>("op_1610_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1246 | tensor<bool, [4]> var_1610_squeeze_mask_0 = const()[name = tensor<string, []>("op_1610_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1247 | tensor<fp16, [1, 1, 1500]> var_1610_cast_fp16 = slice_by_index(begin = var_1610_begin_0, end = var_1610_end_0, end_mask = var_1610_end_mask_0, squeeze_mask = var_1610_squeeze_mask_0, x = var_1607_cast_fp16)[name = tensor<string, []>("op_1610_cast_fp16")]; |
| 1248 | tensor<int32, [4]> var_1625_begin_0 = const()[name = tensor<string, []>("op_1625_begin_0"), val = tensor<int32, [4]>([0, 11, 0, 0])]; |
| 1249 | tensor<int32, [4]> var_1625_end_0 = const()[name = tensor<string, []>("op_1625_end_0"), val = tensor<int32, [4]>([1, 12, 1, 1500])]; |
| 1250 | tensor<bool, [4]> var_1625_end_mask_0 = const()[name = tensor<string, []>("op_1625_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1251 | tensor<fp16, [1, 1, 1, 1500]> var_1625_cast_fp16 = slice_by_index(begin = var_1625_begin_0, end = var_1625_end_0, end_mask = var_1625_end_mask_0, x = obj_41_cast_fp16)[name = tensor<string, []>("op_1625_cast_fp16")]; |
| 1252 | tensor<int32, [4]> var_1628_begin_0 = const()[name = tensor<string, []>("op_1628_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1253 | tensor<int32, [4]> var_1628_end_0 = const()[name = tensor<string, []>("op_1628_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1254 | tensor<bool, [4]> var_1628_end_mask_0 = const()[name = tensor<string, []>("op_1628_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1255 | tensor<bool, [4]> var_1628_squeeze_mask_0 = const()[name = tensor<string, []>("op_1628_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1256 | tensor<fp16, [1, 1, 1500]> var_1628_cast_fp16 = slice_by_index(begin = var_1628_begin_0, end = var_1628_end_0, end_mask = var_1628_end_mask_0, squeeze_mask = var_1628_squeeze_mask_0, x = var_1625_cast_fp16)[name = tensor<string, []>("op_1628_cast_fp16")]; |
| 1257 | tensor<int32, [4]> var_1643_begin_0 = const()[name = tensor<string, []>("op_1643_begin_0"), val = tensor<int32, [4]>([0, 3, 0, 0])]; |
| 1258 | tensor<int32, [4]> var_1643_end_0 = const()[name = tensor<string, []>("op_1643_end_0"), val = tensor<int32, [4]>([1, 4, 1, 1500])]; |
| 1259 | tensor<bool, [4]> var_1643_end_mask_0 = const()[name = tensor<string, []>("op_1643_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1260 | tensor<fp16, [1, 1, 1, 1500]> var_1643_cast_fp16 = slice_by_index(begin = var_1643_begin_0, end = var_1643_end_0, end_mask = var_1643_end_mask_0, x = obj_55_cast_fp16)[name = tensor<string, []>("op_1643_cast_fp16")]; |
| 1261 | tensor<int32, [4]> var_1646_begin_0 = const()[name = tensor<string, []>("op_1646_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1262 | tensor<int32, [4]> var_1646_end_0 = const()[name = tensor<string, []>("op_1646_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1263 | tensor<bool, [4]> var_1646_end_mask_0 = const()[name = tensor<string, []>("op_1646_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1264 | tensor<bool, [4]> var_1646_squeeze_mask_0 = const()[name = tensor<string, []>("op_1646_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1265 | tensor<fp16, [1, 1, 1500]> var_1646_cast_fp16 = slice_by_index(begin = var_1646_begin_0, end = var_1646_end_0, end_mask = var_1646_end_mask_0, squeeze_mask = var_1646_squeeze_mask_0, x = var_1643_cast_fp16)[name = tensor<string, []>("op_1646_cast_fp16")]; |
| 1266 | tensor<int32, [4]> var_1661_begin_0 = const()[name = tensor<string, []>("op_1661_begin_0"), val = tensor<int32, [4]>([0, 6, 0, 0])]; |
| 1267 | tensor<int32, [4]> var_1661_end_0 = const()[name = tensor<string, []>("op_1661_end_0"), val = tensor<int32, [4]>([1, 7, 1, 1500])]; |
| 1268 | tensor<bool, [4]> var_1661_end_mask_0 = const()[name = tensor<string, []>("op_1661_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1269 | tensor<fp16, [1, 1, 1, 1500]> var_1661_cast_fp16 = slice_by_index(begin = var_1661_begin_0, end = var_1661_end_0, end_mask = var_1661_end_mask_0, x = obj_55_cast_fp16)[name = tensor<string, []>("op_1661_cast_fp16")]; |
| 1270 | tensor<int32, [4]> var_1664_begin_0 = const()[name = tensor<string, []>("op_1664_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1271 | tensor<int32, [4]> var_1664_end_0 = const()[name = tensor<string, []>("op_1664_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1272 | tensor<bool, [4]> var_1664_end_mask_0 = const()[name = tensor<string, []>("op_1664_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1273 | tensor<bool, [4]> var_1664_squeeze_mask_0 = const()[name = tensor<string, []>("op_1664_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1274 | tensor<fp16, [1, 1, 1500]> var_1664_cast_fp16 = slice_by_index(begin = var_1664_begin_0, end = var_1664_end_0, end_mask = var_1664_end_mask_0, squeeze_mask = var_1664_squeeze_mask_0, x = var_1661_cast_fp16)[name = tensor<string, []>("op_1664_cast_fp16")]; |
| 1275 | tensor<int32, [4]> var_1679_begin_0 = const()[name = tensor<string, []>("op_1679_begin_0"), val = tensor<int32, [4]>([0, 11, 0, 0])]; |
| 1276 | tensor<int32, [4]> var_1679_end_0 = const()[name = tensor<string, []>("op_1679_end_0"), val = tensor<int32, [4]>([1, 12, 1, 1500])]; |
| 1277 | tensor<bool, [4]> var_1679_end_mask_0 = const()[name = tensor<string, []>("op_1679_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1278 | tensor<fp16, [1, 1, 1, 1500]> var_1679_cast_fp16 = slice_by_index(begin = var_1679_begin_0, end = var_1679_end_0, end_mask = var_1679_end_mask_0, x = obj_55_cast_fp16)[name = tensor<string, []>("op_1679_cast_fp16")]; |
| 1279 | tensor<int32, [4]> var_1682_begin_0 = const()[name = tensor<string, []>("op_1682_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1280 | tensor<int32, [4]> var_1682_end_0 = const()[name = tensor<string, []>("op_1682_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1281 | tensor<bool, [4]> var_1682_end_mask_0 = const()[name = tensor<string, []>("op_1682_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1282 | tensor<bool, [4]> var_1682_squeeze_mask_0 = const()[name = tensor<string, []>("op_1682_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1283 | tensor<fp16, [1, 1, 1500]> var_1682_cast_fp16 = slice_by_index(begin = var_1682_begin_0, end = var_1682_end_0, end_mask = var_1682_end_mask_0, squeeze_mask = var_1682_squeeze_mask_0, x = var_1679_cast_fp16)[name = tensor<string, []>("op_1682_cast_fp16")]; |
| 1284 | tensor<int32, [4]> var_1697_begin_0 = const()[name = tensor<string, []>("op_1697_begin_0"), val = tensor<int32, [4]>([0, 14, 0, 0])]; |
| 1285 | tensor<int32, [4]> var_1697_end_0 = const()[name = tensor<string, []>("op_1697_end_0"), val = tensor<int32, [4]>([1, 15, 1, 1500])]; |
| 1286 | tensor<bool, [4]> var_1697_end_mask_0 = const()[name = tensor<string, []>("op_1697_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])]; |
| 1287 | tensor<fp16, [1, 1, 1, 1500]> var_1697_cast_fp16 = slice_by_index(begin = var_1697_begin_0, end = var_1697_end_0, end_mask = var_1697_end_mask_0, x = obj_55_cast_fp16)[name = tensor<string, []>("op_1697_cast_fp16")]; |
| 1288 | tensor<int32, [4]> var_1700_begin_0 = const()[name = tensor<string, []>("op_1700_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| 1289 | tensor<int32, [4]> var_1700_end_0 = const()[name = tensor<string, []>("op_1700_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1500])]; |
| 1290 | tensor<bool, [4]> var_1700_end_mask_0 = const()[name = tensor<string, []>("op_1700_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])]; |
| 1291 | tensor<bool, [4]> var_1700_squeeze_mask_0 = const()[name = tensor<string, []>("op_1700_squeeze_mask_0"), val = tensor<bool, [4]>([false, false, true, false])]; |
| 1292 | tensor<fp16, [1, 1, 1500]> var_1700_cast_fp16 = slice_by_index(begin = var_1700_begin_0, end = var_1700_end_0, end_mask = var_1700_end_mask_0, squeeze_mask = var_1700_squeeze_mask_0, x = var_1697_cast_fp16)[name = tensor<string, []>("op_1700_cast_fp16")]; |
| 1293 | tensor<int32, []> var_1707 = const()[name = tensor<string, []>("op_1707"), val = tensor<int32, []>(1)]; |
| 1294 | tensor<bool, []> var_1708_interleave_0 = const()[name = tensor<string, []>("op_1708_interleave_0"), val = tensor<bool, []>(false)]; |
| 1295 | tensor<fp16, [1, 6, 1500]> var_1708_cast_fp16 = concat(axis = var_1707, interleave = var_1708_interleave_0, values = (var_1610_cast_fp16, var_1628_cast_fp16, var_1646_cast_fp16, var_1664_cast_fp16, var_1682_cast_fp16, var_1700_cast_fp16))[name = tensor<string, []>("op_1708_cast_fp16")]; |
| 1296 | tensor<bool, []> var_1711 = const()[name = tensor<string, []>("op_1711"), val = tensor<bool, []>(false)]; |
| 1297 | tensor<int32, [1]> obj_axes_0 = const()[name = tensor<string, []>("obj_axes_0"), val = tensor<int32, [1]>([1])]; |
| 1298 | tensor<fp16, [1, 1500]> alignment_heads_weights = reduce_mean(axes = obj_axes_0, keep_dims = var_1711, x = var_1708_cast_fp16)[name = tensor<string, []>("obj_cast_fp16")]; |
| 1299 | } -> (logits, key_cache_updates, value_cache_updates, alignment_heads_weights); |
| 1300 | } |