diff --git "a/ParaformerEncoder.mlmodelc/model.mil" "b/ParaformerEncoder.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/ParaformerEncoder.mlmodelc/model.mil" @@ -0,0 +1,3682 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor speech, tensor speech_lengths) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, dict, tensor>>>>((("DefaultShapes", {{"speech", [1, 1800, 560]}}), ("EnumeratedShapes", {{"speech_1_1_1_1024_560_speech_lengths_1_1_1_1_1_", {{"speech", [1, 1024, 560]}, {"speech_lengths", [1]}}}, {"speech_1_1_1_128_560_speech_lengths_1_1_1_1_1_", {{"speech", [1, 128, 560]}, {"speech_lengths", [1]}}}, {"speech_1_1_1_1800_560_speech_lengths_1_1_1_1_1_", {{"speech", [1, 1800, 560]}, {"speech_lengths", [1]}}}, {"speech_1_1_1_256_560_speech_lengths_1_1_1_1_1_", {{"speech", [1, 256, 560]}, {"speech_lengths", [1]}}}, {"speech_1_1_1_512_560_speech_lengths_1_1_1_1_1_", {{"speech", [1, 512, 560]}, {"speech_lengths", [1]}}}})))] { + tensor var_18 = const()[name = tensor("op_18"), val = tensor(2)]; + tensor var_20 = const()[name = tensor("op_20"), val = tensor(-1)]; + tensor var_26 = const()[name = tensor("op_26"), val = tensor(0)]; + tensor var_27 = const()[name = tensor("op_27"), val = tensor(1)]; + tensor speech_to_fp16_dtype_0 = const()[name = tensor("speech_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor speech_to_fp16 = cast(dtype = speech_to_fp16_dtype_0, x = speech)[name = tensor("cast_322")]; + tensor var_31_shape_cast_fp16 = shape(x = speech_to_fp16)[name = tensor("op_31_shape_cast_fp16")]; + tensor gather_0_axis_0 = const()[name = tensor("gather_0_axis_0"), val = tensor(0)]; + tensor gather_0_batch_dims_0 = const()[name = tensor("gather_0_batch_dims_0"), val = tensor(0)]; + tensor gather_0_validate_indices_0 = const()[name = tensor("gather_0_validate_indices_0"), val = tensor(false)]; + tensor var_31_shape_cast_fp16_to_int16_dtype_0 = const()[name = tensor("op_31_shape_cast_fp16_to_int16_dtype_0"), val = tensor("int16")]; + tensor select_0_to_uint16 = const()[name = tensor("select_0_to_uint16"), val = tensor(1)]; + tensor var_31_shape_cast_fp16_to_int16 = cast(dtype = var_31_shape_cast_fp16_to_int16_dtype_0, x = var_31_shape_cast_fp16)[name = tensor("cast_321")]; + tensor gather_0_cast_uint16 = gather(axis = gather_0_axis_0, batch_dims = gather_0_batch_dims_0, indices = select_0_to_uint16, validate_indices = gather_0_validate_indices_0, x = var_31_shape_cast_fp16_to_int16)[name = tensor("gather_0_cast_uint16")]; + tensor gather_0_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_0_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; + tensor const_0 = const()[name = tensor("const_0"), val = tensor(1)]; + tensor gather_0_cast_uint16_to_int32 = cast(dtype = gather_0_cast_uint16_to_int32_dtype_0, x = gather_0_cast_uint16)[name = tensor("cast_320")]; + tensor seq_range = range_1d(end = gather_0_cast_uint16_to_int32, start = var_26, step = const_0)[name = tensor("seq_range")]; + tensor var_33_axes_0 = const()[name = tensor("op_33_axes_0"), val = tensor([0])]; + tensor var_33 = expand_dims(axes = var_33_axes_0, x = seq_range)[name = tensor("op_33")]; + tensor concat_0_axis_0 = const()[name = tensor("concat_0_axis_0"), val = tensor(0)]; + tensor concat_0_interleave_0 = const()[name = tensor("concat_0_interleave_0"), val = tensor(false)]; + tensor concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (var_27, gather_0_cast_uint16_to_int32))[name = tensor("concat_0")]; + tensor shape_1 = shape(x = var_33)[name = tensor("shape_1")]; + tensor real_div_0 = real_div(x = concat_0, y = shape_1)[name = tensor("real_div_0")]; + tensor seq_range_expand = tile(reps = real_div_0, x = var_33)[name = tensor("seq_range_expand")]; + tensor seq_length_expand = const()[name = tensor("seq_length_expand"), val = tensor([[1800]])]; + tensor var_38 = greater_equal(x = seq_range_expand, y = seq_length_expand)[name = tensor("op_38")]; + tensor var_40_axes_0 = const()[name = tensor("op_40_axes_0"), val = tensor([1])]; + tensor var_40 = expand_dims(axes = var_40_axes_0, x = var_38)[name = tensor("op_40")]; + tensor var_42 = logical_not(x = var_40)[name = tensor("op_42")]; + tensor var_44_to_fp16 = const()[name = tensor("op_44_to_fp16"), val = tensor(0x1.6ap+4)]; + tensor x_3_cast_fp16 = mul(x = speech_to_fp16, y = var_44_to_fp16)[name = tensor("x_3_cast_fp16")]; + tensor var_46_shape_cast_fp16 = shape(x = x_3_cast_fp16)[name = tensor("op_46_shape_cast_fp16")]; + tensor gather_1_axis_0 = const()[name = tensor("gather_1_axis_0"), val = tensor(0)]; + tensor gather_1_batch_dims_0 = const()[name = tensor("gather_1_batch_dims_0"), val = tensor(0)]; + tensor gather_1_validate_indices_0 = const()[name = tensor("gather_1_validate_indices_0"), val = tensor(false)]; + tensor var_46_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_46_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; + tensor select_1_to_uint16 = const()[name = tensor("select_1_to_uint16"), val = tensor(1)]; + tensor var_46_shape_cast_fp16_to_uint16 = cast(dtype = var_46_shape_cast_fp16_to_uint16_dtype_0, x = var_46_shape_cast_fp16)[name = tensor("cast_319")]; + tensor gather_1_cast_uint16 = gather(axis = gather_1_axis_0, batch_dims = gather_1_batch_dims_0, indices = select_1_to_uint16, validate_indices = gather_1_validate_indices_0, x = var_46_shape_cast_fp16_to_uint16)[name = tensor("gather_1_cast_uint16")]; + tensor gather_1_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_1_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; + tensor var_50 = const()[name = tensor("op_50"), val = tensor(1)]; + tensor gather_1_cast_uint16_to_int32 = cast(dtype = gather_1_cast_uint16_to_int32_dtype_0, x = gather_1_cast_uint16)[name = tensor("cast_318")]; + tensor var_51 = add(x = gather_1_cast_uint16_to_int32, y = var_50)[name = tensor("op_51")]; + tensor const_2 = const()[name = tensor("const_2"), val = tensor(1)]; + tensor var_53 = range_1d(end = var_51, start = var_27, step = const_2)[name = tensor("op_53")]; + tensor var_54_axes_0 = const()[name = tensor("op_54_axes_0"), val = tensor([0])]; + tensor var_54 = expand_dims(axes = var_54_axes_0, x = var_53)[name = tensor("op_54")]; + tensor var_76 = const()[name = tensor("op_76"), val = tensor([1, -1, 1])]; + tensor cast_2_to_fp16_dtype_0 = const()[name = tensor("cast_2_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor var_54_to_fp16 = cast(dtype = cast_2_to_fp16_dtype_0, x = var_54)[name = tensor("cast_317")]; + tensor var_77_cast_fp16 = reshape(shape = var_76, x = var_54_to_fp16)[name = tensor("op_77_cast_fp16")]; + tensor var_79_to_fp16 = const()[name = tensor("op_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor scaled_time_cast_fp16 = mul(x = var_77_cast_fp16, y = var_79_to_fp16)[name = tensor("scaled_time_cast_fp16")]; + tensor var_81_cast_fp16 = sin(x = scaled_time_cast_fp16)[name = tensor("op_81_cast_fp16")]; + tensor var_82_cast_fp16 = cos(x = scaled_time_cast_fp16)[name = tensor("op_82_cast_fp16")]; + tensor encoding_interleave_0 = const()[name = tensor("encoding_interleave_0"), val = tensor(false)]; + tensor encoding_cast_fp16 = concat(axis = var_18, interleave = encoding_interleave_0, values = (var_81_cast_fp16, var_82_cast_fp16))[name = tensor("encoding_cast_fp16")]; + tensor input_1_cast_fp16 = add(x = x_3_cast_fp16, y = encoding_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor x_5_axes_0 = const()[name = tensor("x_5_axes_0"), val = tensor([-1])]; + tensor e_encoders0_0_norm1_weight_to_fp16 = const()[name = tensor("e_encoders0_0_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(704)))]; + tensor e_encoders0_0_norm1_bias_to_fp16 = const()[name = tensor("e_encoders0_0_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1920)))]; + tensor var_13_to_fp16 = const()[name = tensor("op_13_to_fp16"), val = tensor(0x1p-24)]; + tensor x_5_cast_fp16 = layer_norm(axes = x_5_axes_0, beta = e_encoders0_0_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders0_0_norm1_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("x_5_cast_fp16")]; + tensor e_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3136)))]; + tensor e_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1723520)))]; + tensor linear_0_cast_fp16 = linear(bias = e_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16, x = x_5_cast_fp16)[name = tensor("linear_0_cast_fp16")]; + tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([512, 512, 512])]; + tensor var_105_axis_0 = const()[name = tensor("op_105_axis_0"), val = tensor(-1)]; + tensor var_105_cast_fp16_0, tensor var_105_cast_fp16_1, tensor var_105_cast_fp16_2 = split(axis = var_105_axis_0, split_sizes = tile_0, x = linear_0_cast_fp16)[name = tensor("op_105_cast_fp16")]; + tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([1, -1, 4, 128])]; + tensor var_110_cast_fp16 = reshape(shape = concat_1x, x = var_105_cast_fp16_0)[name = tensor("op_110_cast_fp16")]; + tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([1, -1, 4, 128])]; + tensor var_113_cast_fp16 = reshape(shape = concat_2x, x = var_105_cast_fp16_1)[name = tensor("op_113_cast_fp16")]; + tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([1, -1, 4, 128])]; + tensor var_116_cast_fp16 = reshape(shape = concat_3x, x = var_105_cast_fp16_2)[name = tensor("op_116_cast_fp16")]; + tensor value_1_perm_0 = const()[name = tensor("value_1_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_119 = const()[name = tensor("op_119"), val = tensor([1, -1, 1])]; + tensor mask_3 = reshape(shape = var_119, x = var_42)[name = tensor("mask_3")]; + tensor mask_3_promoted_to_fp16_dtype_0 = const()[name = tensor("mask_3_promoted_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor mask_3_to_fp16 = cast(dtype = mask_3_promoted_to_fp16_dtype_0, x = mask_3)[name = tensor("cast_316")]; + tensor inputs_1_cast_fp16 = mul(x = var_105_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor input_3_perm_0 = const()[name = tensor("input_3_perm_0"), val = tensor([0, 2, 1])]; + tensor input_5_pad_0 = const()[name = tensor("input_5_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_5_mode_0 = const()[name = tensor("input_5_mode_0"), val = tensor("constant")]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; + tensor input_3_cast_fp16 = transpose(perm = input_3_perm_0, x = inputs_1_cast_fp16)[name = tensor("transpose_548")]; + tensor input_5_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_5_mode_0, pad = input_5_pad_0, x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor x_7_pad_type_0 = const()[name = tensor("x_7_pad_type_0"), val = tensor("valid")]; + tensor x_7_groups_0 = const()[name = tensor("x_7_groups_0"), val = tensor(512)]; + tensor x_7_strides_0 = const()[name = tensor("x_7_strides_0"), val = tensor([1])]; + tensor x_7_pad_0 = const()[name = tensor("x_7_pad_0"), val = tensor([0, 0])]; + tensor x_7_dilations_0 = const()[name = tensor("x_7_dilations_0"), val = tensor([1])]; + tensor e_encoders0_0_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders0_0_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1726656)))]; + tensor x_7_cast_fp16 = conv(dilations = x_7_dilations_0, groups = x_7_groups_0, pad = x_7_pad_0, pad_type = x_7_pad_type_0, strides = x_7_strides_0, weight = e_encoders0_0_self_attn_fsmn_block_weight_to_fp16, x = input_5_cast_fp16)[name = tensor("x_7_cast_fp16")]; + tensor x_9_perm_0 = const()[name = tensor("x_9_perm_0"), val = tensor([0, 2, 1])]; + tensor x_9_cast_fp16 = transpose(perm = x_9_perm_0, x = x_7_cast_fp16)[name = tensor("transpose_547")]; + tensor input_7_cast_fp16 = add(x = x_9_cast_fp16, y = inputs_1_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor fsmn_memory_1_cast_fp16 = mul(x = input_7_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_1_cast_fp16")]; + tensor var_135_to_fp16 = const()[name = tensor("op_135_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_3_cast_fp16 = mul(x = var_110_cast_fp16, y = var_135_to_fp16)[name = tensor("q_h_3_cast_fp16")]; + tensor scores_1_transpose_x_0 = const()[name = tensor("scores_1_transpose_x_0"), val = tensor(false)]; + tensor scores_1_transpose_y_0 = const()[name = tensor("scores_1_transpose_y_0"), val = tensor(false)]; + tensor transpose_150_perm_0 = const()[name = tensor("transpose_150_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_151_perm_0 = const()[name = tensor("transpose_151_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_151 = transpose(perm = transpose_151_perm_0, x = var_113_cast_fp16)[name = tensor("transpose_545")]; + tensor transpose_150 = transpose(perm = transpose_150_perm_0, x = q_h_3_cast_fp16)[name = tensor("transpose_546")]; + tensor scores_1_cast_fp16 = matmul(transpose_x = scores_1_transpose_x_0, transpose_y = scores_1_transpose_y_0, x = transpose_150, y = transpose_151)[name = tensor("scores_1_cast_fp16")]; + tensor var_140_axes_0 = const()[name = tensor("op_140_axes_0"), val = tensor([1])]; + tensor var_140 = expand_dims(axes = var_140_axes_0, x = var_42)[name = tensor("op_140")]; + tensor cast_18_dtype_0 = const()[name = tensor("cast_18_dtype_0"), val = tensor("int32")]; + tensor cast_18 = cast(dtype = cast_18_dtype_0, x = var_140)[name = tensor("cast_315")]; + tensor mask_5 = equal(x = cast_18, y = var_26)[name = tensor("mask_5")]; + tensor var_11_to_fp16 = const()[name = tensor("op_11_to_fp16"), val = tensor(-0x1.388p+13)]; + tensor scores_3_cast_fp16 = select(a = var_11_to_fp16, b = scores_1_cast_fp16, cond = mask_5)[name = tensor("scores_3_cast_fp16")]; + tensor var_143_cast_fp16 = softmax(axis = var_20, x = scores_3_cast_fp16)[name = tensor("op_143_cast_fp16")]; + tensor var_6_to_fp16 = const()[name = tensor("op_6_to_fp16"), val = tensor(0x0p+0)]; + tensor input_9_cast_fp16 = select(a = var_6_to_fp16, b = var_143_cast_fp16, cond = mask_5)[name = tensor("input_9_cast_fp16")]; + tensor x_13_transpose_x_0 = const()[name = tensor("x_13_transpose_x_0"), val = tensor(false)]; + tensor x_13_transpose_y_0 = const()[name = tensor("x_13_transpose_y_0"), val = tensor(false)]; + tensor value_1_cast_fp16 = transpose(perm = value_1_perm_0, x = var_116_cast_fp16)[name = tensor("transpose_549")]; + tensor x_13_cast_fp16 = matmul(transpose_x = x_13_transpose_x_0, transpose_y = x_13_transpose_y_0, x = input_9_cast_fp16, y = value_1_cast_fp16)[name = tensor("x_13_cast_fp16")]; + tensor var_147_perm_0 = const()[name = tensor("op_147_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_149 = const()[name = tensor("op_149"), val = tensor([1, -1, 512])]; + tensor var_147_cast_fp16 = transpose(perm = var_147_perm_0, x = x_13_cast_fp16)[name = tensor("transpose_544")]; + tensor input_11_cast_fp16 = reshape(shape = var_149, x = var_147_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor e_encoders0_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders0_0_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1737984)))]; + tensor e_encoders0_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders0_0_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2262336)))]; + tensor linear_1_cast_fp16 = linear(bias = e_encoders0_0_self_attn_linear_out_bias_to_fp16, weight = e_encoders0_0_self_attn_linear_out_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("linear_1_cast_fp16")]; + tensor input_13_cast_fp16 = add(x = linear_1_cast_fp16, y = fsmn_memory_1_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor input_17_axes_0 = const()[name = tensor("input_17_axes_0"), val = tensor([-1])]; + tensor e_encoders0_0_norm2_weight_to_fp16 = const()[name = tensor("e_encoders0_0_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2263424)))]; + tensor e_encoders0_0_norm2_bias_to_fp16 = const()[name = tensor("e_encoders0_0_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2264512)))]; + tensor input_17_cast_fp16 = layer_norm(axes = input_17_axes_0, beta = e_encoders0_0_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders0_0_norm2_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor e_encoders0_0_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders0_0_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2265600)))]; + tensor e_encoders0_0_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders0_0_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4362816)))]; + tensor linear_2_cast_fp16 = linear(bias = e_encoders0_0_feed_forward_w_1_bias_to_fp16, weight = e_encoders0_0_feed_forward_w_1_weight_to_fp16, x = input_17_cast_fp16)[name = tensor("linear_2_cast_fp16")]; + tensor input_21_cast_fp16 = relu(x = linear_2_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor e_encoders0_0_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders0_0_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4366976)))]; + tensor e_encoders0_0_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders0_0_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6464192)))]; + tensor linear_3_cast_fp16 = linear(bias = e_encoders0_0_feed_forward_w_2_bias_to_fp16, weight = e_encoders0_0_feed_forward_w_2_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("linear_3_cast_fp16")]; + tensor input_27_cast_fp16 = add(x = input_13_cast_fp16, y = linear_3_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor x_15_axes_0 = const()[name = tensor("x_15_axes_0"), val = tensor([-1])]; + tensor e_encoders_0_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_0_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6465280)))]; + tensor e_encoders_0_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_0_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6466368)))]; + tensor x_15_cast_fp16 = layer_norm(axes = x_15_axes_0, beta = e_encoders_0_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_0_norm1_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("x_15_cast_fp16")]; + tensor e_encoders_0_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_0_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6467456)))]; + tensor e_encoders_0_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_0_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8040384)))]; + tensor linear_4_cast_fp16 = linear(bias = e_encoders_0_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_0_self_attn_linear_q_k_v_weight_to_fp16, x = x_15_cast_fp16)[name = tensor("linear_4_cast_fp16")]; + tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([512, 512, 512])]; + tensor var_241_axis_0 = const()[name = tensor("op_241_axis_0"), val = tensor(-1)]; + tensor var_241_cast_fp16_0, tensor var_241_cast_fp16_1, tensor var_241_cast_fp16_2 = split(axis = var_241_axis_0, split_sizes = tile_1, x = linear_4_cast_fp16)[name = tensor("op_241_cast_fp16")]; + tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([1, -1, 4, 128])]; + tensor var_246_cast_fp16 = reshape(shape = concat_4x, x = var_241_cast_fp16_0)[name = tensor("op_246_cast_fp16")]; + tensor concat_5x = const()[name = tensor("concat_5x"), val = tensor([1, -1, 4, 128])]; + tensor var_249_cast_fp16 = reshape(shape = concat_5x, x = var_241_cast_fp16_1)[name = tensor("op_249_cast_fp16")]; + tensor concat_6x = const()[name = tensor("concat_6x"), val = tensor([1, -1, 4, 128])]; + tensor var_252_cast_fp16 = reshape(shape = concat_6x, x = var_241_cast_fp16_2)[name = tensor("op_252_cast_fp16")]; + tensor value_3_perm_0 = const()[name = tensor("value_3_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_3_cast_fp16 = mul(x = var_241_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor input_29_perm_0 = const()[name = tensor("input_29_perm_0"), val = tensor([0, 2, 1])]; + tensor input_31_pad_0 = const()[name = tensor("input_31_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_31_mode_0 = const()[name = tensor("input_31_mode_0"), val = tensor("constant")]; + tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(0x0p+0)]; + tensor input_29_cast_fp16 = transpose(perm = input_29_perm_0, x = inputs_3_cast_fp16)[name = tensor("transpose_542")]; + tensor input_31_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = input_31_mode_0, pad = input_31_pad_0, x = input_29_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor x_17_pad_type_0 = const()[name = tensor("x_17_pad_type_0"), val = tensor("valid")]; + tensor x_17_groups_0 = const()[name = tensor("x_17_groups_0"), val = tensor(512)]; + tensor x_17_strides_0 = const()[name = tensor("x_17_strides_0"), val = tensor([1])]; + tensor x_17_pad_0 = const()[name = tensor("x_17_pad_0"), val = tensor([0, 0])]; + tensor x_17_dilations_0 = const()[name = tensor("x_17_dilations_0"), val = tensor([1])]; + tensor e_encoders_0_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_0_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8043520)))]; + tensor x_17_cast_fp16 = conv(dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = e_encoders_0_self_attn_fsmn_block_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("x_17_cast_fp16")]; + tensor x_19_perm_0 = const()[name = tensor("x_19_perm_0"), val = tensor([0, 2, 1])]; + tensor x_19_cast_fp16 = transpose(perm = x_19_perm_0, x = x_17_cast_fp16)[name = tensor("transpose_541")]; + tensor input_33_cast_fp16 = add(x = x_19_cast_fp16, y = inputs_3_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor fsmn_memory_3_cast_fp16 = mul(x = input_33_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_3_cast_fp16")]; + tensor var_271_to_fp16 = const()[name = tensor("op_271_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_7_cast_fp16 = mul(x = var_246_cast_fp16, y = var_271_to_fp16)[name = tensor("q_h_7_cast_fp16")]; + tensor scores_5_transpose_x_0 = const()[name = tensor("scores_5_transpose_x_0"), val = tensor(false)]; + tensor scores_5_transpose_y_0 = const()[name = tensor("scores_5_transpose_y_0"), val = tensor(false)]; + tensor transpose_152_perm_0 = const()[name = tensor("transpose_152_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_153_perm_0 = const()[name = tensor("transpose_153_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_153 = transpose(perm = transpose_153_perm_0, x = var_249_cast_fp16)[name = tensor("transpose_539")]; + tensor transpose_152 = transpose(perm = transpose_152_perm_0, x = q_h_7_cast_fp16)[name = tensor("transpose_540")]; + tensor scores_5_cast_fp16 = matmul(transpose_x = scores_5_transpose_x_0, transpose_y = scores_5_transpose_y_0, x = transpose_152, y = transpose_153)[name = tensor("scores_5_cast_fp16")]; + tensor scores_7_cast_fp16 = select(a = var_11_to_fp16, b = scores_5_cast_fp16, cond = mask_5)[name = tensor("scores_7_cast_fp16")]; + tensor var_279_cast_fp16 = softmax(axis = var_20, x = scores_7_cast_fp16)[name = tensor("op_279_cast_fp16")]; + tensor input_35_cast_fp16 = select(a = var_6_to_fp16, b = var_279_cast_fp16, cond = mask_5)[name = tensor("input_35_cast_fp16")]; + tensor x_23_transpose_x_0 = const()[name = tensor("x_23_transpose_x_0"), val = tensor(false)]; + tensor x_23_transpose_y_0 = const()[name = tensor("x_23_transpose_y_0"), val = tensor(false)]; + tensor value_3_cast_fp16 = transpose(perm = value_3_perm_0, x = var_252_cast_fp16)[name = tensor("transpose_543")]; + tensor x_23_cast_fp16 = matmul(transpose_x = x_23_transpose_x_0, transpose_y = x_23_transpose_y_0, x = input_35_cast_fp16, y = value_3_cast_fp16)[name = tensor("x_23_cast_fp16")]; + tensor var_283_perm_0 = const()[name = tensor("op_283_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_285 = const()[name = tensor("op_285"), val = tensor([1, -1, 512])]; + tensor var_283_cast_fp16 = transpose(perm = var_283_perm_0, x = x_23_cast_fp16)[name = tensor("transpose_538")]; + tensor input_37_cast_fp16 = reshape(shape = var_285, x = var_283_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor e_encoders_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_0_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8054848)))]; + tensor e_encoders_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_0_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8579200)))]; + tensor linear_5_cast_fp16 = linear(bias = e_encoders_0_self_attn_linear_out_bias_to_fp16, weight = e_encoders_0_self_attn_linear_out_weight_to_fp16, x = input_37_cast_fp16)[name = tensor("linear_5_cast_fp16")]; + tensor input_39_cast_fp16 = add(x = linear_5_cast_fp16, y = fsmn_memory_3_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor input_41_cast_fp16 = add(x = input_27_cast_fp16, y = input_39_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor input_43_axes_0 = const()[name = tensor("input_43_axes_0"), val = tensor([-1])]; + tensor e_encoders_0_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_0_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8580288)))]; + tensor e_encoders_0_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_0_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8581376)))]; + tensor input_43_cast_fp16 = layer_norm(axes = input_43_axes_0, beta = e_encoders_0_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_0_norm2_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor e_encoders_0_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_0_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8582464)))]; + tensor e_encoders_0_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_0_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10679680)))]; + tensor linear_6_cast_fp16 = linear(bias = e_encoders_0_feed_forward_w_1_bias_to_fp16, weight = e_encoders_0_feed_forward_w_1_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("linear_6_cast_fp16")]; + tensor input_47_cast_fp16 = relu(x = linear_6_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor e_encoders_0_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_0_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10683840)))]; + tensor e_encoders_0_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_0_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12781056)))]; + tensor linear_7_cast_fp16 = linear(bias = e_encoders_0_feed_forward_w_2_bias_to_fp16, weight = e_encoders_0_feed_forward_w_2_weight_to_fp16, x = input_47_cast_fp16)[name = tensor("linear_7_cast_fp16")]; + tensor input_53_cast_fp16 = add(x = input_41_cast_fp16, y = linear_7_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor x_25_axes_0 = const()[name = tensor("x_25_axes_0"), val = tensor([-1])]; + tensor e_encoders_1_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_1_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12782144)))]; + tensor e_encoders_1_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_1_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12783232)))]; + tensor x_25_cast_fp16 = layer_norm(axes = x_25_axes_0, beta = e_encoders_1_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_1_norm1_weight_to_fp16, x = input_53_cast_fp16)[name = tensor("x_25_cast_fp16")]; + tensor e_encoders_1_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_1_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12784320)))]; + tensor e_encoders_1_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_1_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14357248)))]; + tensor linear_8_cast_fp16 = linear(bias = e_encoders_1_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_1_self_attn_linear_q_k_v_weight_to_fp16, x = x_25_cast_fp16)[name = tensor("linear_8_cast_fp16")]; + tensor tile_2 = const()[name = tensor("tile_2"), val = tensor([512, 512, 512])]; + tensor var_329_axis_0 = const()[name = tensor("op_329_axis_0"), val = tensor(-1)]; + tensor var_329_cast_fp16_0, tensor var_329_cast_fp16_1, tensor var_329_cast_fp16_2 = split(axis = var_329_axis_0, split_sizes = tile_2, x = linear_8_cast_fp16)[name = tensor("op_329_cast_fp16")]; + tensor concat_7x = const()[name = tensor("concat_7x"), val = tensor([1, -1, 4, 128])]; + tensor var_334_cast_fp16 = reshape(shape = concat_7x, x = var_329_cast_fp16_0)[name = tensor("op_334_cast_fp16")]; + tensor concat_8x = const()[name = tensor("concat_8x"), val = tensor([1, -1, 4, 128])]; + tensor var_337_cast_fp16 = reshape(shape = concat_8x, x = var_329_cast_fp16_1)[name = tensor("op_337_cast_fp16")]; + tensor concat_9x = const()[name = tensor("concat_9x"), val = tensor([1, -1, 4, 128])]; + tensor var_340_cast_fp16 = reshape(shape = concat_9x, x = var_329_cast_fp16_2)[name = tensor("op_340_cast_fp16")]; + tensor value_5_perm_0 = const()[name = tensor("value_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_5_cast_fp16 = mul(x = var_329_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor input_55_perm_0 = const()[name = tensor("input_55_perm_0"), val = tensor([0, 2, 1])]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_57_mode_0 = const()[name = tensor("input_57_mode_0"), val = tensor("constant")]; + tensor const_13_to_fp16 = const()[name = tensor("const_13_to_fp16"), val = tensor(0x0p+0)]; + tensor input_55_cast_fp16 = transpose(perm = input_55_perm_0, x = inputs_5_cast_fp16)[name = tensor("transpose_536")]; + tensor input_57_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor x_27_pad_type_0 = const()[name = tensor("x_27_pad_type_0"), val = tensor("valid")]; + tensor x_27_groups_0 = const()[name = tensor("x_27_groups_0"), val = tensor(512)]; + tensor x_27_strides_0 = const()[name = tensor("x_27_strides_0"), val = tensor([1])]; + tensor x_27_pad_0 = const()[name = tensor("x_27_pad_0"), val = tensor([0, 0])]; + tensor x_27_dilations_0 = const()[name = tensor("x_27_dilations_0"), val = tensor([1])]; + tensor e_encoders_1_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_1_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14360384)))]; + tensor x_27_cast_fp16 = conv(dilations = x_27_dilations_0, groups = x_27_groups_0, pad = x_27_pad_0, pad_type = x_27_pad_type_0, strides = x_27_strides_0, weight = e_encoders_1_self_attn_fsmn_block_weight_to_fp16, x = input_57_cast_fp16)[name = tensor("x_27_cast_fp16")]; + tensor x_29_perm_0 = const()[name = tensor("x_29_perm_0"), val = tensor([0, 2, 1])]; + tensor x_29_cast_fp16 = transpose(perm = x_29_perm_0, x = x_27_cast_fp16)[name = tensor("transpose_535")]; + tensor input_59_cast_fp16 = add(x = x_29_cast_fp16, y = inputs_5_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor fsmn_memory_5_cast_fp16 = mul(x = input_59_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_5_cast_fp16")]; + tensor var_359_to_fp16 = const()[name = tensor("op_359_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_11_cast_fp16 = mul(x = var_334_cast_fp16, y = var_359_to_fp16)[name = tensor("q_h_11_cast_fp16")]; + tensor scores_9_transpose_x_0 = const()[name = tensor("scores_9_transpose_x_0"), val = tensor(false)]; + tensor scores_9_transpose_y_0 = const()[name = tensor("scores_9_transpose_y_0"), val = tensor(false)]; + tensor transpose_154_perm_0 = const()[name = tensor("transpose_154_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_155_perm_0 = const()[name = tensor("transpose_155_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_155 = transpose(perm = transpose_155_perm_0, x = var_337_cast_fp16)[name = tensor("transpose_533")]; + tensor transpose_154 = transpose(perm = transpose_154_perm_0, x = q_h_11_cast_fp16)[name = tensor("transpose_534")]; + tensor scores_9_cast_fp16 = matmul(transpose_x = scores_9_transpose_x_0, transpose_y = scores_9_transpose_y_0, x = transpose_154, y = transpose_155)[name = tensor("scores_9_cast_fp16")]; + tensor scores_11_cast_fp16 = select(a = var_11_to_fp16, b = scores_9_cast_fp16, cond = mask_5)[name = tensor("scores_11_cast_fp16")]; + tensor var_367_cast_fp16 = softmax(axis = var_20, x = scores_11_cast_fp16)[name = tensor("op_367_cast_fp16")]; + tensor input_61_cast_fp16 = select(a = var_6_to_fp16, b = var_367_cast_fp16, cond = mask_5)[name = tensor("input_61_cast_fp16")]; + tensor x_33_transpose_x_0 = const()[name = tensor("x_33_transpose_x_0"), val = tensor(false)]; + tensor x_33_transpose_y_0 = const()[name = tensor("x_33_transpose_y_0"), val = tensor(false)]; + tensor value_5_cast_fp16 = transpose(perm = value_5_perm_0, x = var_340_cast_fp16)[name = tensor("transpose_537")]; + tensor x_33_cast_fp16 = matmul(transpose_x = x_33_transpose_x_0, transpose_y = x_33_transpose_y_0, x = input_61_cast_fp16, y = value_5_cast_fp16)[name = tensor("x_33_cast_fp16")]; + tensor var_371_perm_0 = const()[name = tensor("op_371_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_373 = const()[name = tensor("op_373"), val = tensor([1, -1, 512])]; + tensor var_371_cast_fp16 = transpose(perm = var_371_perm_0, x = x_33_cast_fp16)[name = tensor("transpose_532")]; + tensor input_63_cast_fp16 = reshape(shape = var_373, x = var_371_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor e_encoders_1_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_1_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14371712)))]; + tensor e_encoders_1_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_1_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14896064)))]; + tensor linear_9_cast_fp16 = linear(bias = e_encoders_1_self_attn_linear_out_bias_to_fp16, weight = e_encoders_1_self_attn_linear_out_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("linear_9_cast_fp16")]; + tensor input_65_cast_fp16 = add(x = linear_9_cast_fp16, y = fsmn_memory_5_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor input_67_cast_fp16 = add(x = input_53_cast_fp16, y = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor input_69_axes_0 = const()[name = tensor("input_69_axes_0"), val = tensor([-1])]; + tensor e_encoders_1_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_1_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14897152)))]; + tensor e_encoders_1_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_1_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14898240)))]; + tensor input_69_cast_fp16 = layer_norm(axes = input_69_axes_0, beta = e_encoders_1_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_1_norm2_weight_to_fp16, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor e_encoders_1_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_1_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14899328)))]; + tensor e_encoders_1_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_1_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16996544)))]; + tensor linear_10_cast_fp16 = linear(bias = e_encoders_1_feed_forward_w_1_bias_to_fp16, weight = e_encoders_1_feed_forward_w_1_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("linear_10_cast_fp16")]; + tensor input_73_cast_fp16 = relu(x = linear_10_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor e_encoders_1_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_1_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17000704)))]; + tensor e_encoders_1_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_1_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19097920)))]; + tensor linear_11_cast_fp16 = linear(bias = e_encoders_1_feed_forward_w_2_bias_to_fp16, weight = e_encoders_1_feed_forward_w_2_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("linear_11_cast_fp16")]; + tensor input_79_cast_fp16 = add(x = input_67_cast_fp16, y = linear_11_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor x_35_axes_0 = const()[name = tensor("x_35_axes_0"), val = tensor([-1])]; + tensor e_encoders_2_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_2_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19099008)))]; + tensor e_encoders_2_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_2_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19100096)))]; + tensor x_35_cast_fp16 = layer_norm(axes = x_35_axes_0, beta = e_encoders_2_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_2_norm1_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("x_35_cast_fp16")]; + tensor e_encoders_2_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_2_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19101184)))]; + tensor e_encoders_2_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_2_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20674112)))]; + tensor linear_12_cast_fp16 = linear(bias = e_encoders_2_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_2_self_attn_linear_q_k_v_weight_to_fp16, x = x_35_cast_fp16)[name = tensor("linear_12_cast_fp16")]; + tensor tile_3 = const()[name = tensor("tile_3"), val = tensor([512, 512, 512])]; + tensor var_417_axis_0 = const()[name = tensor("op_417_axis_0"), val = tensor(-1)]; + tensor var_417_cast_fp16_0, tensor var_417_cast_fp16_1, tensor var_417_cast_fp16_2 = split(axis = var_417_axis_0, split_sizes = tile_3, x = linear_12_cast_fp16)[name = tensor("op_417_cast_fp16")]; + tensor concat_10x = const()[name = tensor("concat_10x"), val = tensor([1, -1, 4, 128])]; + tensor var_422_cast_fp16 = reshape(shape = concat_10x, x = var_417_cast_fp16_0)[name = tensor("op_422_cast_fp16")]; + tensor concat_11x = const()[name = tensor("concat_11x"), val = tensor([1, -1, 4, 128])]; + tensor var_425_cast_fp16 = reshape(shape = concat_11x, x = var_417_cast_fp16_1)[name = tensor("op_425_cast_fp16")]; + tensor concat_12x = const()[name = tensor("concat_12x"), val = tensor([1, -1, 4, 128])]; + tensor var_428_cast_fp16 = reshape(shape = concat_12x, x = var_417_cast_fp16_2)[name = tensor("op_428_cast_fp16")]; + tensor value_7_perm_0 = const()[name = tensor("value_7_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_7_cast_fp16 = mul(x = var_417_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor input_81_perm_0 = const()[name = tensor("input_81_perm_0"), val = tensor([0, 2, 1])]; + tensor input_83_pad_0 = const()[name = tensor("input_83_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_83_mode_0 = const()[name = tensor("input_83_mode_0"), val = tensor("constant")]; + tensor const_15_to_fp16 = const()[name = tensor("const_15_to_fp16"), val = tensor(0x0p+0)]; + tensor input_81_cast_fp16 = transpose(perm = input_81_perm_0, x = inputs_7_cast_fp16)[name = tensor("transpose_530")]; + tensor input_83_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_83_mode_0, pad = input_83_pad_0, x = input_81_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor x_37_pad_type_0 = const()[name = tensor("x_37_pad_type_0"), val = tensor("valid")]; + tensor x_37_groups_0 = const()[name = tensor("x_37_groups_0"), val = tensor(512)]; + tensor x_37_strides_0 = const()[name = tensor("x_37_strides_0"), val = tensor([1])]; + tensor x_37_pad_0 = const()[name = tensor("x_37_pad_0"), val = tensor([0, 0])]; + tensor x_37_dilations_0 = const()[name = tensor("x_37_dilations_0"), val = tensor([1])]; + tensor e_encoders_2_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_2_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20677248)))]; + tensor x_37_cast_fp16 = conv(dilations = x_37_dilations_0, groups = x_37_groups_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = e_encoders_2_self_attn_fsmn_block_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("x_37_cast_fp16")]; + tensor x_39_perm_0 = const()[name = tensor("x_39_perm_0"), val = tensor([0, 2, 1])]; + tensor x_39_cast_fp16 = transpose(perm = x_39_perm_0, x = x_37_cast_fp16)[name = tensor("transpose_529")]; + tensor input_85_cast_fp16 = add(x = x_39_cast_fp16, y = inputs_7_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor fsmn_memory_7_cast_fp16 = mul(x = input_85_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_7_cast_fp16")]; + tensor var_447_to_fp16 = const()[name = tensor("op_447_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_15_cast_fp16 = mul(x = var_422_cast_fp16, y = var_447_to_fp16)[name = tensor("q_h_15_cast_fp16")]; + tensor scores_13_transpose_x_0 = const()[name = tensor("scores_13_transpose_x_0"), val = tensor(false)]; + tensor scores_13_transpose_y_0 = const()[name = tensor("scores_13_transpose_y_0"), val = tensor(false)]; + tensor transpose_156_perm_0 = const()[name = tensor("transpose_156_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_157_perm_0 = const()[name = tensor("transpose_157_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_157 = transpose(perm = transpose_157_perm_0, x = var_425_cast_fp16)[name = tensor("transpose_527")]; + tensor transpose_156 = transpose(perm = transpose_156_perm_0, x = q_h_15_cast_fp16)[name = tensor("transpose_528")]; + tensor scores_13_cast_fp16 = matmul(transpose_x = scores_13_transpose_x_0, transpose_y = scores_13_transpose_y_0, x = transpose_156, y = transpose_157)[name = tensor("scores_13_cast_fp16")]; + tensor scores_15_cast_fp16 = select(a = var_11_to_fp16, b = scores_13_cast_fp16, cond = mask_5)[name = tensor("scores_15_cast_fp16")]; + tensor var_455_cast_fp16 = softmax(axis = var_20, x = scores_15_cast_fp16)[name = tensor("op_455_cast_fp16")]; + tensor input_87_cast_fp16 = select(a = var_6_to_fp16, b = var_455_cast_fp16, cond = mask_5)[name = tensor("input_87_cast_fp16")]; + tensor x_43_transpose_x_0 = const()[name = tensor("x_43_transpose_x_0"), val = tensor(false)]; + tensor x_43_transpose_y_0 = const()[name = tensor("x_43_transpose_y_0"), val = tensor(false)]; + tensor value_7_cast_fp16 = transpose(perm = value_7_perm_0, x = var_428_cast_fp16)[name = tensor("transpose_531")]; + tensor x_43_cast_fp16 = matmul(transpose_x = x_43_transpose_x_0, transpose_y = x_43_transpose_y_0, x = input_87_cast_fp16, y = value_7_cast_fp16)[name = tensor("x_43_cast_fp16")]; + tensor var_459_perm_0 = const()[name = tensor("op_459_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_461 = const()[name = tensor("op_461"), val = tensor([1, -1, 512])]; + tensor var_459_cast_fp16 = transpose(perm = var_459_perm_0, x = x_43_cast_fp16)[name = tensor("transpose_526")]; + tensor input_89_cast_fp16 = reshape(shape = var_461, x = var_459_cast_fp16)[name = tensor("input_89_cast_fp16")]; + tensor e_encoders_2_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_2_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20688576)))]; + tensor e_encoders_2_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_2_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21212928)))]; + tensor linear_13_cast_fp16 = linear(bias = e_encoders_2_self_attn_linear_out_bias_to_fp16, weight = e_encoders_2_self_attn_linear_out_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("linear_13_cast_fp16")]; + tensor input_91_cast_fp16 = add(x = linear_13_cast_fp16, y = fsmn_memory_7_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor input_93_cast_fp16 = add(x = input_79_cast_fp16, y = input_91_cast_fp16)[name = tensor("input_93_cast_fp16")]; + tensor input_95_axes_0 = const()[name = tensor("input_95_axes_0"), val = tensor([-1])]; + tensor e_encoders_2_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_2_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21214016)))]; + tensor e_encoders_2_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_2_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21215104)))]; + tensor input_95_cast_fp16 = layer_norm(axes = input_95_axes_0, beta = e_encoders_2_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_2_norm2_weight_to_fp16, x = input_93_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor e_encoders_2_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_2_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21216192)))]; + tensor e_encoders_2_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_2_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23313408)))]; + tensor linear_14_cast_fp16 = linear(bias = e_encoders_2_feed_forward_w_1_bias_to_fp16, weight = e_encoders_2_feed_forward_w_1_weight_to_fp16, x = input_95_cast_fp16)[name = tensor("linear_14_cast_fp16")]; + tensor input_99_cast_fp16 = relu(x = linear_14_cast_fp16)[name = tensor("input_99_cast_fp16")]; + tensor e_encoders_2_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_2_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23317568)))]; + tensor e_encoders_2_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_2_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25414784)))]; + tensor linear_15_cast_fp16 = linear(bias = e_encoders_2_feed_forward_w_2_bias_to_fp16, weight = e_encoders_2_feed_forward_w_2_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("linear_15_cast_fp16")]; + tensor input_105_cast_fp16 = add(x = input_93_cast_fp16, y = linear_15_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor x_45_axes_0 = const()[name = tensor("x_45_axes_0"), val = tensor([-1])]; + tensor e_encoders_3_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_3_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25415872)))]; + tensor e_encoders_3_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_3_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25416960)))]; + tensor x_45_cast_fp16 = layer_norm(axes = x_45_axes_0, beta = e_encoders_3_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_3_norm1_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("x_45_cast_fp16")]; + tensor e_encoders_3_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_3_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25418048)))]; + tensor e_encoders_3_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_3_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26990976)))]; + tensor linear_16_cast_fp16 = linear(bias = e_encoders_3_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_3_self_attn_linear_q_k_v_weight_to_fp16, x = x_45_cast_fp16)[name = tensor("linear_16_cast_fp16")]; + tensor tile_4 = const()[name = tensor("tile_4"), val = tensor([512, 512, 512])]; + tensor var_505_axis_0 = const()[name = tensor("op_505_axis_0"), val = tensor(-1)]; + tensor var_505_cast_fp16_0, tensor var_505_cast_fp16_1, tensor var_505_cast_fp16_2 = split(axis = var_505_axis_0, split_sizes = tile_4, x = linear_16_cast_fp16)[name = tensor("op_505_cast_fp16")]; + tensor concat_13x = const()[name = tensor("concat_13x"), val = tensor([1, -1, 4, 128])]; + tensor var_510_cast_fp16 = reshape(shape = concat_13x, x = var_505_cast_fp16_0)[name = tensor("op_510_cast_fp16")]; + tensor concat_14x = const()[name = tensor("concat_14x"), val = tensor([1, -1, 4, 128])]; + tensor var_513_cast_fp16 = reshape(shape = concat_14x, x = var_505_cast_fp16_1)[name = tensor("op_513_cast_fp16")]; + tensor concat_15x = const()[name = tensor("concat_15x"), val = tensor([1, -1, 4, 128])]; + tensor var_516_cast_fp16 = reshape(shape = concat_15x, x = var_505_cast_fp16_2)[name = tensor("op_516_cast_fp16")]; + tensor value_9_perm_0 = const()[name = tensor("value_9_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_9_cast_fp16 = mul(x = var_505_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor input_107_perm_0 = const()[name = tensor("input_107_perm_0"), val = tensor([0, 2, 1])]; + tensor input_109_pad_0 = const()[name = tensor("input_109_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_109_mode_0 = const()[name = tensor("input_109_mode_0"), val = tensor("constant")]; + tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(0x0p+0)]; + tensor input_107_cast_fp16 = transpose(perm = input_107_perm_0, x = inputs_9_cast_fp16)[name = tensor("transpose_524")]; + tensor input_109_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_109_mode_0, pad = input_109_pad_0, x = input_107_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor x_47_pad_type_0 = const()[name = tensor("x_47_pad_type_0"), val = tensor("valid")]; + tensor x_47_groups_0 = const()[name = tensor("x_47_groups_0"), val = tensor(512)]; + tensor x_47_strides_0 = const()[name = tensor("x_47_strides_0"), val = tensor([1])]; + tensor x_47_pad_0 = const()[name = tensor("x_47_pad_0"), val = tensor([0, 0])]; + tensor x_47_dilations_0 = const()[name = tensor("x_47_dilations_0"), val = tensor([1])]; + tensor e_encoders_3_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_3_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26994112)))]; + tensor x_47_cast_fp16 = conv(dilations = x_47_dilations_0, groups = x_47_groups_0, pad = x_47_pad_0, pad_type = x_47_pad_type_0, strides = x_47_strides_0, weight = e_encoders_3_self_attn_fsmn_block_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("x_47_cast_fp16")]; + tensor x_49_perm_0 = const()[name = tensor("x_49_perm_0"), val = tensor([0, 2, 1])]; + tensor x_49_cast_fp16 = transpose(perm = x_49_perm_0, x = x_47_cast_fp16)[name = tensor("transpose_523")]; + tensor input_111_cast_fp16 = add(x = x_49_cast_fp16, y = inputs_9_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor fsmn_memory_9_cast_fp16 = mul(x = input_111_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_9_cast_fp16")]; + tensor var_535_to_fp16 = const()[name = tensor("op_535_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_19_cast_fp16 = mul(x = var_510_cast_fp16, y = var_535_to_fp16)[name = tensor("q_h_19_cast_fp16")]; + tensor scores_17_transpose_x_0 = const()[name = tensor("scores_17_transpose_x_0"), val = tensor(false)]; + tensor scores_17_transpose_y_0 = const()[name = tensor("scores_17_transpose_y_0"), val = tensor(false)]; + tensor transpose_158_perm_0 = const()[name = tensor("transpose_158_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_159_perm_0 = const()[name = tensor("transpose_159_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_159 = transpose(perm = transpose_159_perm_0, x = var_513_cast_fp16)[name = tensor("transpose_521")]; + tensor transpose_158 = transpose(perm = transpose_158_perm_0, x = q_h_19_cast_fp16)[name = tensor("transpose_522")]; + tensor scores_17_cast_fp16 = matmul(transpose_x = scores_17_transpose_x_0, transpose_y = scores_17_transpose_y_0, x = transpose_158, y = transpose_159)[name = tensor("scores_17_cast_fp16")]; + tensor scores_19_cast_fp16 = select(a = var_11_to_fp16, b = scores_17_cast_fp16, cond = mask_5)[name = tensor("scores_19_cast_fp16")]; + tensor var_543_cast_fp16 = softmax(axis = var_20, x = scores_19_cast_fp16)[name = tensor("op_543_cast_fp16")]; + tensor input_113_cast_fp16 = select(a = var_6_to_fp16, b = var_543_cast_fp16, cond = mask_5)[name = tensor("input_113_cast_fp16")]; + tensor x_53_transpose_x_0 = const()[name = tensor("x_53_transpose_x_0"), val = tensor(false)]; + tensor x_53_transpose_y_0 = const()[name = tensor("x_53_transpose_y_0"), val = tensor(false)]; + tensor value_9_cast_fp16 = transpose(perm = value_9_perm_0, x = var_516_cast_fp16)[name = tensor("transpose_525")]; + tensor x_53_cast_fp16 = matmul(transpose_x = x_53_transpose_x_0, transpose_y = x_53_transpose_y_0, x = input_113_cast_fp16, y = value_9_cast_fp16)[name = tensor("x_53_cast_fp16")]; + tensor var_547_perm_0 = const()[name = tensor("op_547_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_549 = const()[name = tensor("op_549"), val = tensor([1, -1, 512])]; + tensor var_547_cast_fp16 = transpose(perm = var_547_perm_0, x = x_53_cast_fp16)[name = tensor("transpose_520")]; + tensor input_115_cast_fp16 = reshape(shape = var_549, x = var_547_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor e_encoders_3_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_3_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27005440)))]; + tensor e_encoders_3_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_3_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27529792)))]; + tensor linear_17_cast_fp16 = linear(bias = e_encoders_3_self_attn_linear_out_bias_to_fp16, weight = e_encoders_3_self_attn_linear_out_weight_to_fp16, x = input_115_cast_fp16)[name = tensor("linear_17_cast_fp16")]; + tensor input_117_cast_fp16 = add(x = linear_17_cast_fp16, y = fsmn_memory_9_cast_fp16)[name = tensor("input_117_cast_fp16")]; + tensor input_119_cast_fp16 = add(x = input_105_cast_fp16, y = input_117_cast_fp16)[name = tensor("input_119_cast_fp16")]; + tensor input_121_axes_0 = const()[name = tensor("input_121_axes_0"), val = tensor([-1])]; + tensor e_encoders_3_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_3_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27530880)))]; + tensor e_encoders_3_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_3_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27531968)))]; + tensor input_121_cast_fp16 = layer_norm(axes = input_121_axes_0, beta = e_encoders_3_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_3_norm2_weight_to_fp16, x = input_119_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor e_encoders_3_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_3_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27533056)))]; + tensor e_encoders_3_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_3_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29630272)))]; + tensor linear_18_cast_fp16 = linear(bias = e_encoders_3_feed_forward_w_1_bias_to_fp16, weight = e_encoders_3_feed_forward_w_1_weight_to_fp16, x = input_121_cast_fp16)[name = tensor("linear_18_cast_fp16")]; + tensor input_125_cast_fp16 = relu(x = linear_18_cast_fp16)[name = tensor("input_125_cast_fp16")]; + tensor e_encoders_3_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_3_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29634432)))]; + tensor e_encoders_3_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_3_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31731648)))]; + tensor linear_19_cast_fp16 = linear(bias = e_encoders_3_feed_forward_w_2_bias_to_fp16, weight = e_encoders_3_feed_forward_w_2_weight_to_fp16, x = input_125_cast_fp16)[name = tensor("linear_19_cast_fp16")]; + tensor input_131_cast_fp16 = add(x = input_119_cast_fp16, y = linear_19_cast_fp16)[name = tensor("input_131_cast_fp16")]; + tensor x_55_axes_0 = const()[name = tensor("x_55_axes_0"), val = tensor([-1])]; + tensor e_encoders_4_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_4_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31732736)))]; + tensor e_encoders_4_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_4_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31733824)))]; + tensor x_55_cast_fp16 = layer_norm(axes = x_55_axes_0, beta = e_encoders_4_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_4_norm1_weight_to_fp16, x = input_131_cast_fp16)[name = tensor("x_55_cast_fp16")]; + tensor e_encoders_4_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_4_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31734912)))]; + tensor e_encoders_4_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_4_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33307840)))]; + tensor linear_20_cast_fp16 = linear(bias = e_encoders_4_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_4_self_attn_linear_q_k_v_weight_to_fp16, x = x_55_cast_fp16)[name = tensor("linear_20_cast_fp16")]; + tensor tile_5 = const()[name = tensor("tile_5"), val = tensor([512, 512, 512])]; + tensor var_593_axis_0 = const()[name = tensor("op_593_axis_0"), val = tensor(-1)]; + tensor var_593_cast_fp16_0, tensor var_593_cast_fp16_1, tensor var_593_cast_fp16_2 = split(axis = var_593_axis_0, split_sizes = tile_5, x = linear_20_cast_fp16)[name = tensor("op_593_cast_fp16")]; + tensor concat_16x = const()[name = tensor("concat_16x"), val = tensor([1, -1, 4, 128])]; + tensor var_598_cast_fp16 = reshape(shape = concat_16x, x = var_593_cast_fp16_0)[name = tensor("op_598_cast_fp16")]; + tensor concat_17x = const()[name = tensor("concat_17x"), val = tensor([1, -1, 4, 128])]; + tensor var_601_cast_fp16 = reshape(shape = concat_17x, x = var_593_cast_fp16_1)[name = tensor("op_601_cast_fp16")]; + tensor concat_18x = const()[name = tensor("concat_18x"), val = tensor([1, -1, 4, 128])]; + tensor var_604_cast_fp16 = reshape(shape = concat_18x, x = var_593_cast_fp16_2)[name = tensor("op_604_cast_fp16")]; + tensor value_11_perm_0 = const()[name = tensor("value_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_11_cast_fp16 = mul(x = var_593_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor input_133_perm_0 = const()[name = tensor("input_133_perm_0"), val = tensor([0, 2, 1])]; + tensor input_135_pad_0 = const()[name = tensor("input_135_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_135_mode_0 = const()[name = tensor("input_135_mode_0"), val = tensor("constant")]; + tensor const_19_to_fp16 = const()[name = tensor("const_19_to_fp16"), val = tensor(0x0p+0)]; + tensor input_133_cast_fp16 = transpose(perm = input_133_perm_0, x = inputs_11_cast_fp16)[name = tensor("transpose_518")]; + tensor input_135_cast_fp16 = pad(constant_val = const_19_to_fp16, mode = input_135_mode_0, pad = input_135_pad_0, x = input_133_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor x_57_pad_type_0 = const()[name = tensor("x_57_pad_type_0"), val = tensor("valid")]; + tensor x_57_groups_0 = const()[name = tensor("x_57_groups_0"), val = tensor(512)]; + tensor x_57_strides_0 = const()[name = tensor("x_57_strides_0"), val = tensor([1])]; + tensor x_57_pad_0 = const()[name = tensor("x_57_pad_0"), val = tensor([0, 0])]; + tensor x_57_dilations_0 = const()[name = tensor("x_57_dilations_0"), val = tensor([1])]; + tensor e_encoders_4_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_4_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33310976)))]; + tensor x_57_cast_fp16 = conv(dilations = x_57_dilations_0, groups = x_57_groups_0, pad = x_57_pad_0, pad_type = x_57_pad_type_0, strides = x_57_strides_0, weight = e_encoders_4_self_attn_fsmn_block_weight_to_fp16, x = input_135_cast_fp16)[name = tensor("x_57_cast_fp16")]; + tensor x_59_perm_0 = const()[name = tensor("x_59_perm_0"), val = tensor([0, 2, 1])]; + tensor x_59_cast_fp16 = transpose(perm = x_59_perm_0, x = x_57_cast_fp16)[name = tensor("transpose_517")]; + tensor input_137_cast_fp16 = add(x = x_59_cast_fp16, y = inputs_11_cast_fp16)[name = tensor("input_137_cast_fp16")]; + tensor fsmn_memory_11_cast_fp16 = mul(x = input_137_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_11_cast_fp16")]; + tensor var_623_to_fp16 = const()[name = tensor("op_623_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_23_cast_fp16 = mul(x = var_598_cast_fp16, y = var_623_to_fp16)[name = tensor("q_h_23_cast_fp16")]; + tensor scores_21_transpose_x_0 = const()[name = tensor("scores_21_transpose_x_0"), val = tensor(false)]; + tensor scores_21_transpose_y_0 = const()[name = tensor("scores_21_transpose_y_0"), val = tensor(false)]; + tensor transpose_160_perm_0 = const()[name = tensor("transpose_160_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_161_perm_0 = const()[name = tensor("transpose_161_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_161 = transpose(perm = transpose_161_perm_0, x = var_601_cast_fp16)[name = tensor("transpose_515")]; + tensor transpose_160 = transpose(perm = transpose_160_perm_0, x = q_h_23_cast_fp16)[name = tensor("transpose_516")]; + tensor scores_21_cast_fp16 = matmul(transpose_x = scores_21_transpose_x_0, transpose_y = scores_21_transpose_y_0, x = transpose_160, y = transpose_161)[name = tensor("scores_21_cast_fp16")]; + tensor scores_23_cast_fp16 = select(a = var_11_to_fp16, b = scores_21_cast_fp16, cond = mask_5)[name = tensor("scores_23_cast_fp16")]; + tensor var_631_cast_fp16 = softmax(axis = var_20, x = scores_23_cast_fp16)[name = tensor("op_631_cast_fp16")]; + tensor input_139_cast_fp16 = select(a = var_6_to_fp16, b = var_631_cast_fp16, cond = mask_5)[name = tensor("input_139_cast_fp16")]; + tensor x_63_transpose_x_0 = const()[name = tensor("x_63_transpose_x_0"), val = tensor(false)]; + tensor x_63_transpose_y_0 = const()[name = tensor("x_63_transpose_y_0"), val = tensor(false)]; + tensor value_11_cast_fp16 = transpose(perm = value_11_perm_0, x = var_604_cast_fp16)[name = tensor("transpose_519")]; + tensor x_63_cast_fp16 = matmul(transpose_x = x_63_transpose_x_0, transpose_y = x_63_transpose_y_0, x = input_139_cast_fp16, y = value_11_cast_fp16)[name = tensor("x_63_cast_fp16")]; + tensor var_635_perm_0 = const()[name = tensor("op_635_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_637 = const()[name = tensor("op_637"), val = tensor([1, -1, 512])]; + tensor var_635_cast_fp16 = transpose(perm = var_635_perm_0, x = x_63_cast_fp16)[name = tensor("transpose_514")]; + tensor input_141_cast_fp16 = reshape(shape = var_637, x = var_635_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor e_encoders_4_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_4_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33322304)))]; + tensor e_encoders_4_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_4_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33846656)))]; + tensor linear_21_cast_fp16 = linear(bias = e_encoders_4_self_attn_linear_out_bias_to_fp16, weight = e_encoders_4_self_attn_linear_out_weight_to_fp16, x = input_141_cast_fp16)[name = tensor("linear_21_cast_fp16")]; + tensor input_143_cast_fp16 = add(x = linear_21_cast_fp16, y = fsmn_memory_11_cast_fp16)[name = tensor("input_143_cast_fp16")]; + tensor input_145_cast_fp16 = add(x = input_131_cast_fp16, y = input_143_cast_fp16)[name = tensor("input_145_cast_fp16")]; + tensor input_147_axes_0 = const()[name = tensor("input_147_axes_0"), val = tensor([-1])]; + tensor e_encoders_4_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_4_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33847744)))]; + tensor e_encoders_4_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_4_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33848832)))]; + tensor input_147_cast_fp16 = layer_norm(axes = input_147_axes_0, beta = e_encoders_4_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_4_norm2_weight_to_fp16, x = input_145_cast_fp16)[name = tensor("input_147_cast_fp16")]; + tensor e_encoders_4_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_4_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33849920)))]; + tensor e_encoders_4_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_4_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35947136)))]; + tensor linear_22_cast_fp16 = linear(bias = e_encoders_4_feed_forward_w_1_bias_to_fp16, weight = e_encoders_4_feed_forward_w_1_weight_to_fp16, x = input_147_cast_fp16)[name = tensor("linear_22_cast_fp16")]; + tensor input_151_cast_fp16 = relu(x = linear_22_cast_fp16)[name = tensor("input_151_cast_fp16")]; + tensor e_encoders_4_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_4_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35951296)))]; + tensor e_encoders_4_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_4_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38048512)))]; + tensor linear_23_cast_fp16 = linear(bias = e_encoders_4_feed_forward_w_2_bias_to_fp16, weight = e_encoders_4_feed_forward_w_2_weight_to_fp16, x = input_151_cast_fp16)[name = tensor("linear_23_cast_fp16")]; + tensor input_157_cast_fp16 = add(x = input_145_cast_fp16, y = linear_23_cast_fp16)[name = tensor("input_157_cast_fp16")]; + tensor x_65_axes_0 = const()[name = tensor("x_65_axes_0"), val = tensor([-1])]; + tensor e_encoders_5_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_5_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38049600)))]; + tensor e_encoders_5_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_5_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38050688)))]; + tensor x_65_cast_fp16 = layer_norm(axes = x_65_axes_0, beta = e_encoders_5_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_5_norm1_weight_to_fp16, x = input_157_cast_fp16)[name = tensor("x_65_cast_fp16")]; + tensor e_encoders_5_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_5_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38051776)))]; + tensor e_encoders_5_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_5_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39624704)))]; + tensor linear_24_cast_fp16 = linear(bias = e_encoders_5_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_5_self_attn_linear_q_k_v_weight_to_fp16, x = x_65_cast_fp16)[name = tensor("linear_24_cast_fp16")]; + tensor tile_6 = const()[name = tensor("tile_6"), val = tensor([512, 512, 512])]; + tensor var_681_axis_0 = const()[name = tensor("op_681_axis_0"), val = tensor(-1)]; + tensor var_681_cast_fp16_0, tensor var_681_cast_fp16_1, tensor var_681_cast_fp16_2 = split(axis = var_681_axis_0, split_sizes = tile_6, x = linear_24_cast_fp16)[name = tensor("op_681_cast_fp16")]; + tensor concat_19x = const()[name = tensor("concat_19x"), val = tensor([1, -1, 4, 128])]; + tensor var_686_cast_fp16 = reshape(shape = concat_19x, x = var_681_cast_fp16_0)[name = tensor("op_686_cast_fp16")]; + tensor concat_20x = const()[name = tensor("concat_20x"), val = tensor([1, -1, 4, 128])]; + tensor var_689_cast_fp16 = reshape(shape = concat_20x, x = var_681_cast_fp16_1)[name = tensor("op_689_cast_fp16")]; + tensor concat_21x = const()[name = tensor("concat_21x"), val = tensor([1, -1, 4, 128])]; + tensor var_692_cast_fp16 = reshape(shape = concat_21x, x = var_681_cast_fp16_2)[name = tensor("op_692_cast_fp16")]; + tensor value_13_perm_0 = const()[name = tensor("value_13_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_13_cast_fp16 = mul(x = var_681_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor input_159_perm_0 = const()[name = tensor("input_159_perm_0"), val = tensor([0, 2, 1])]; + tensor input_161_pad_0 = const()[name = tensor("input_161_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_161_mode_0 = const()[name = tensor("input_161_mode_0"), val = tensor("constant")]; + tensor const_21_to_fp16 = const()[name = tensor("const_21_to_fp16"), val = tensor(0x0p+0)]; + tensor input_159_cast_fp16 = transpose(perm = input_159_perm_0, x = inputs_13_cast_fp16)[name = tensor("transpose_512")]; + tensor input_161_cast_fp16 = pad(constant_val = const_21_to_fp16, mode = input_161_mode_0, pad = input_161_pad_0, x = input_159_cast_fp16)[name = tensor("input_161_cast_fp16")]; + tensor x_67_pad_type_0 = const()[name = tensor("x_67_pad_type_0"), val = tensor("valid")]; + tensor x_67_groups_0 = const()[name = tensor("x_67_groups_0"), val = tensor(512)]; + tensor x_67_strides_0 = const()[name = tensor("x_67_strides_0"), val = tensor([1])]; + tensor x_67_pad_0 = const()[name = tensor("x_67_pad_0"), val = tensor([0, 0])]; + tensor x_67_dilations_0 = const()[name = tensor("x_67_dilations_0"), val = tensor([1])]; + tensor e_encoders_5_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_5_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39627840)))]; + tensor x_67_cast_fp16 = conv(dilations = x_67_dilations_0, groups = x_67_groups_0, pad = x_67_pad_0, pad_type = x_67_pad_type_0, strides = x_67_strides_0, weight = e_encoders_5_self_attn_fsmn_block_weight_to_fp16, x = input_161_cast_fp16)[name = tensor("x_67_cast_fp16")]; + tensor x_69_perm_0 = const()[name = tensor("x_69_perm_0"), val = tensor([0, 2, 1])]; + tensor x_69_cast_fp16 = transpose(perm = x_69_perm_0, x = x_67_cast_fp16)[name = tensor("transpose_511")]; + tensor input_163_cast_fp16 = add(x = x_69_cast_fp16, y = inputs_13_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor fsmn_memory_13_cast_fp16 = mul(x = input_163_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_13_cast_fp16")]; + tensor var_711_to_fp16 = const()[name = tensor("op_711_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_27_cast_fp16 = mul(x = var_686_cast_fp16, y = var_711_to_fp16)[name = tensor("q_h_27_cast_fp16")]; + tensor scores_25_transpose_x_0 = const()[name = tensor("scores_25_transpose_x_0"), val = tensor(false)]; + tensor scores_25_transpose_y_0 = const()[name = tensor("scores_25_transpose_y_0"), val = tensor(false)]; + tensor transpose_162_perm_0 = const()[name = tensor("transpose_162_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_163_perm_0 = const()[name = tensor("transpose_163_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_163 = transpose(perm = transpose_163_perm_0, x = var_689_cast_fp16)[name = tensor("transpose_509")]; + tensor transpose_162 = transpose(perm = transpose_162_perm_0, x = q_h_27_cast_fp16)[name = tensor("transpose_510")]; + tensor scores_25_cast_fp16 = matmul(transpose_x = scores_25_transpose_x_0, transpose_y = scores_25_transpose_y_0, x = transpose_162, y = transpose_163)[name = tensor("scores_25_cast_fp16")]; + tensor scores_27_cast_fp16 = select(a = var_11_to_fp16, b = scores_25_cast_fp16, cond = mask_5)[name = tensor("scores_27_cast_fp16")]; + tensor var_719_cast_fp16 = softmax(axis = var_20, x = scores_27_cast_fp16)[name = tensor("op_719_cast_fp16")]; + tensor input_165_cast_fp16 = select(a = var_6_to_fp16, b = var_719_cast_fp16, cond = mask_5)[name = tensor("input_165_cast_fp16")]; + tensor x_73_transpose_x_0 = const()[name = tensor("x_73_transpose_x_0"), val = tensor(false)]; + tensor x_73_transpose_y_0 = const()[name = tensor("x_73_transpose_y_0"), val = tensor(false)]; + tensor value_13_cast_fp16 = transpose(perm = value_13_perm_0, x = var_692_cast_fp16)[name = tensor("transpose_513")]; + tensor x_73_cast_fp16 = matmul(transpose_x = x_73_transpose_x_0, transpose_y = x_73_transpose_y_0, x = input_165_cast_fp16, y = value_13_cast_fp16)[name = tensor("x_73_cast_fp16")]; + tensor var_723_perm_0 = const()[name = tensor("op_723_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_725 = const()[name = tensor("op_725"), val = tensor([1, -1, 512])]; + tensor var_723_cast_fp16 = transpose(perm = var_723_perm_0, x = x_73_cast_fp16)[name = tensor("transpose_508")]; + tensor input_167_cast_fp16 = reshape(shape = var_725, x = var_723_cast_fp16)[name = tensor("input_167_cast_fp16")]; + tensor e_encoders_5_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_5_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39639168)))]; + tensor e_encoders_5_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_5_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40163520)))]; + tensor linear_25_cast_fp16 = linear(bias = e_encoders_5_self_attn_linear_out_bias_to_fp16, weight = e_encoders_5_self_attn_linear_out_weight_to_fp16, x = input_167_cast_fp16)[name = tensor("linear_25_cast_fp16")]; + tensor input_169_cast_fp16 = add(x = linear_25_cast_fp16, y = fsmn_memory_13_cast_fp16)[name = tensor("input_169_cast_fp16")]; + tensor input_171_cast_fp16 = add(x = input_157_cast_fp16, y = input_169_cast_fp16)[name = tensor("input_171_cast_fp16")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor e_encoders_5_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_5_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40164608)))]; + tensor e_encoders_5_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_5_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40165696)))]; + tensor input_173_cast_fp16 = layer_norm(axes = input_173_axes_0, beta = e_encoders_5_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_5_norm2_weight_to_fp16, x = input_171_cast_fp16)[name = tensor("input_173_cast_fp16")]; + tensor e_encoders_5_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_5_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40166784)))]; + tensor e_encoders_5_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_5_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42264000)))]; + tensor linear_26_cast_fp16 = linear(bias = e_encoders_5_feed_forward_w_1_bias_to_fp16, weight = e_encoders_5_feed_forward_w_1_weight_to_fp16, x = input_173_cast_fp16)[name = tensor("linear_26_cast_fp16")]; + tensor input_177_cast_fp16 = relu(x = linear_26_cast_fp16)[name = tensor("input_177_cast_fp16")]; + tensor e_encoders_5_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_5_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42268160)))]; + tensor e_encoders_5_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_5_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44365376)))]; + tensor linear_27_cast_fp16 = linear(bias = e_encoders_5_feed_forward_w_2_bias_to_fp16, weight = e_encoders_5_feed_forward_w_2_weight_to_fp16, x = input_177_cast_fp16)[name = tensor("linear_27_cast_fp16")]; + tensor input_183_cast_fp16 = add(x = input_171_cast_fp16, y = linear_27_cast_fp16)[name = tensor("input_183_cast_fp16")]; + tensor x_75_axes_0 = const()[name = tensor("x_75_axes_0"), val = tensor([-1])]; + tensor e_encoders_6_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_6_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44366464)))]; + tensor e_encoders_6_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_6_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44367552)))]; + tensor x_75_cast_fp16 = layer_norm(axes = x_75_axes_0, beta = e_encoders_6_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_6_norm1_weight_to_fp16, x = input_183_cast_fp16)[name = tensor("x_75_cast_fp16")]; + tensor e_encoders_6_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_6_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44368640)))]; + tensor e_encoders_6_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_6_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45941568)))]; + tensor linear_28_cast_fp16 = linear(bias = e_encoders_6_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_6_self_attn_linear_q_k_v_weight_to_fp16, x = x_75_cast_fp16)[name = tensor("linear_28_cast_fp16")]; + tensor tile_7 = const()[name = tensor("tile_7"), val = tensor([512, 512, 512])]; + tensor var_769_axis_0 = const()[name = tensor("op_769_axis_0"), val = tensor(-1)]; + tensor var_769_cast_fp16_0, tensor var_769_cast_fp16_1, tensor var_769_cast_fp16_2 = split(axis = var_769_axis_0, split_sizes = tile_7, x = linear_28_cast_fp16)[name = tensor("op_769_cast_fp16")]; + tensor concat_22x = const()[name = tensor("concat_22x"), val = tensor([1, -1, 4, 128])]; + tensor var_774_cast_fp16 = reshape(shape = concat_22x, x = var_769_cast_fp16_0)[name = tensor("op_774_cast_fp16")]; + tensor concat_23x = const()[name = tensor("concat_23x"), val = tensor([1, -1, 4, 128])]; + tensor var_777_cast_fp16 = reshape(shape = concat_23x, x = var_769_cast_fp16_1)[name = tensor("op_777_cast_fp16")]; + tensor concat_24x = const()[name = tensor("concat_24x"), val = tensor([1, -1, 4, 128])]; + tensor var_780_cast_fp16 = reshape(shape = concat_24x, x = var_769_cast_fp16_2)[name = tensor("op_780_cast_fp16")]; + tensor value_15_perm_0 = const()[name = tensor("value_15_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_15_cast_fp16 = mul(x = var_769_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor input_185_perm_0 = const()[name = tensor("input_185_perm_0"), val = tensor([0, 2, 1])]; + tensor input_187_pad_0 = const()[name = tensor("input_187_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_187_mode_0 = const()[name = tensor("input_187_mode_0"), val = tensor("constant")]; + tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(0x0p+0)]; + tensor input_185_cast_fp16 = transpose(perm = input_185_perm_0, x = inputs_15_cast_fp16)[name = tensor("transpose_506")]; + tensor input_187_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_187_mode_0, pad = input_187_pad_0, x = input_185_cast_fp16)[name = tensor("input_187_cast_fp16")]; + tensor x_77_pad_type_0 = const()[name = tensor("x_77_pad_type_0"), val = tensor("valid")]; + tensor x_77_groups_0 = const()[name = tensor("x_77_groups_0"), val = tensor(512)]; + tensor x_77_strides_0 = const()[name = tensor("x_77_strides_0"), val = tensor([1])]; + tensor x_77_pad_0 = const()[name = tensor("x_77_pad_0"), val = tensor([0, 0])]; + tensor x_77_dilations_0 = const()[name = tensor("x_77_dilations_0"), val = tensor([1])]; + tensor e_encoders_6_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_6_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45944704)))]; + tensor x_77_cast_fp16 = conv(dilations = x_77_dilations_0, groups = x_77_groups_0, pad = x_77_pad_0, pad_type = x_77_pad_type_0, strides = x_77_strides_0, weight = e_encoders_6_self_attn_fsmn_block_weight_to_fp16, x = input_187_cast_fp16)[name = tensor("x_77_cast_fp16")]; + tensor x_79_perm_0 = const()[name = tensor("x_79_perm_0"), val = tensor([0, 2, 1])]; + tensor x_79_cast_fp16 = transpose(perm = x_79_perm_0, x = x_77_cast_fp16)[name = tensor("transpose_505")]; + tensor input_189_cast_fp16 = add(x = x_79_cast_fp16, y = inputs_15_cast_fp16)[name = tensor("input_189_cast_fp16")]; + tensor fsmn_memory_15_cast_fp16 = mul(x = input_189_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_15_cast_fp16")]; + tensor var_799_to_fp16 = const()[name = tensor("op_799_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_31_cast_fp16 = mul(x = var_774_cast_fp16, y = var_799_to_fp16)[name = tensor("q_h_31_cast_fp16")]; + tensor scores_29_transpose_x_0 = const()[name = tensor("scores_29_transpose_x_0"), val = tensor(false)]; + tensor scores_29_transpose_y_0 = const()[name = tensor("scores_29_transpose_y_0"), val = tensor(false)]; + tensor transpose_164_perm_0 = const()[name = tensor("transpose_164_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_165_perm_0 = const()[name = tensor("transpose_165_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_165 = transpose(perm = transpose_165_perm_0, x = var_777_cast_fp16)[name = tensor("transpose_503")]; + tensor transpose_164 = transpose(perm = transpose_164_perm_0, x = q_h_31_cast_fp16)[name = tensor("transpose_504")]; + tensor scores_29_cast_fp16 = matmul(transpose_x = scores_29_transpose_x_0, transpose_y = scores_29_transpose_y_0, x = transpose_164, y = transpose_165)[name = tensor("scores_29_cast_fp16")]; + tensor scores_31_cast_fp16 = select(a = var_11_to_fp16, b = scores_29_cast_fp16, cond = mask_5)[name = tensor("scores_31_cast_fp16")]; + tensor var_807_cast_fp16 = softmax(axis = var_20, x = scores_31_cast_fp16)[name = tensor("op_807_cast_fp16")]; + tensor input_191_cast_fp16 = select(a = var_6_to_fp16, b = var_807_cast_fp16, cond = mask_5)[name = tensor("input_191_cast_fp16")]; + tensor x_83_transpose_x_0 = const()[name = tensor("x_83_transpose_x_0"), val = tensor(false)]; + tensor x_83_transpose_y_0 = const()[name = tensor("x_83_transpose_y_0"), val = tensor(false)]; + tensor value_15_cast_fp16 = transpose(perm = value_15_perm_0, x = var_780_cast_fp16)[name = tensor("transpose_507")]; + tensor x_83_cast_fp16 = matmul(transpose_x = x_83_transpose_x_0, transpose_y = x_83_transpose_y_0, x = input_191_cast_fp16, y = value_15_cast_fp16)[name = tensor("x_83_cast_fp16")]; + tensor var_811_perm_0 = const()[name = tensor("op_811_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_813 = const()[name = tensor("op_813"), val = tensor([1, -1, 512])]; + tensor var_811_cast_fp16 = transpose(perm = var_811_perm_0, x = x_83_cast_fp16)[name = tensor("transpose_502")]; + tensor input_193_cast_fp16 = reshape(shape = var_813, x = var_811_cast_fp16)[name = tensor("input_193_cast_fp16")]; + tensor e_encoders_6_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_6_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45956032)))]; + tensor e_encoders_6_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_6_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46480384)))]; + tensor linear_29_cast_fp16 = linear(bias = e_encoders_6_self_attn_linear_out_bias_to_fp16, weight = e_encoders_6_self_attn_linear_out_weight_to_fp16, x = input_193_cast_fp16)[name = tensor("linear_29_cast_fp16")]; + tensor input_195_cast_fp16 = add(x = linear_29_cast_fp16, y = fsmn_memory_15_cast_fp16)[name = tensor("input_195_cast_fp16")]; + tensor input_197_cast_fp16 = add(x = input_183_cast_fp16, y = input_195_cast_fp16)[name = tensor("input_197_cast_fp16")]; + tensor input_199_axes_0 = const()[name = tensor("input_199_axes_0"), val = tensor([-1])]; + tensor e_encoders_6_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_6_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46481472)))]; + tensor e_encoders_6_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_6_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46482560)))]; + tensor input_199_cast_fp16 = layer_norm(axes = input_199_axes_0, beta = e_encoders_6_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_6_norm2_weight_to_fp16, x = input_197_cast_fp16)[name = tensor("input_199_cast_fp16")]; + tensor e_encoders_6_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_6_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46483648)))]; + tensor e_encoders_6_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_6_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48580864)))]; + tensor linear_30_cast_fp16 = linear(bias = e_encoders_6_feed_forward_w_1_bias_to_fp16, weight = e_encoders_6_feed_forward_w_1_weight_to_fp16, x = input_199_cast_fp16)[name = tensor("linear_30_cast_fp16")]; + tensor input_203_cast_fp16 = relu(x = linear_30_cast_fp16)[name = tensor("input_203_cast_fp16")]; + tensor e_encoders_6_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_6_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48585024)))]; + tensor e_encoders_6_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_6_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50682240)))]; + tensor linear_31_cast_fp16 = linear(bias = e_encoders_6_feed_forward_w_2_bias_to_fp16, weight = e_encoders_6_feed_forward_w_2_weight_to_fp16, x = input_203_cast_fp16)[name = tensor("linear_31_cast_fp16")]; + tensor input_209_cast_fp16 = add(x = input_197_cast_fp16, y = linear_31_cast_fp16)[name = tensor("input_209_cast_fp16")]; + tensor x_85_axes_0 = const()[name = tensor("x_85_axes_0"), val = tensor([-1])]; + tensor e_encoders_7_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_7_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50683328)))]; + tensor e_encoders_7_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_7_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50684416)))]; + tensor x_85_cast_fp16 = layer_norm(axes = x_85_axes_0, beta = e_encoders_7_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_7_norm1_weight_to_fp16, x = input_209_cast_fp16)[name = tensor("x_85_cast_fp16")]; + tensor e_encoders_7_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_7_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50685504)))]; + tensor e_encoders_7_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_7_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52258432)))]; + tensor linear_32_cast_fp16 = linear(bias = e_encoders_7_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_7_self_attn_linear_q_k_v_weight_to_fp16, x = x_85_cast_fp16)[name = tensor("linear_32_cast_fp16")]; + tensor tile_8 = const()[name = tensor("tile_8"), val = tensor([512, 512, 512])]; + tensor var_857_axis_0 = const()[name = tensor("op_857_axis_0"), val = tensor(-1)]; + tensor var_857_cast_fp16_0, tensor var_857_cast_fp16_1, tensor var_857_cast_fp16_2 = split(axis = var_857_axis_0, split_sizes = tile_8, x = linear_32_cast_fp16)[name = tensor("op_857_cast_fp16")]; + tensor concat_25x = const()[name = tensor("concat_25x"), val = tensor([1, -1, 4, 128])]; + tensor var_862_cast_fp16 = reshape(shape = concat_25x, x = var_857_cast_fp16_0)[name = tensor("op_862_cast_fp16")]; + tensor concat_26x = const()[name = tensor("concat_26x"), val = tensor([1, -1, 4, 128])]; + tensor var_865_cast_fp16 = reshape(shape = concat_26x, x = var_857_cast_fp16_1)[name = tensor("op_865_cast_fp16")]; + tensor concat_27x = const()[name = tensor("concat_27x"), val = tensor([1, -1, 4, 128])]; + tensor var_868_cast_fp16 = reshape(shape = concat_27x, x = var_857_cast_fp16_2)[name = tensor("op_868_cast_fp16")]; + tensor value_17_perm_0 = const()[name = tensor("value_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_17_cast_fp16 = mul(x = var_857_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor input_211_perm_0 = const()[name = tensor("input_211_perm_0"), val = tensor([0, 2, 1])]; + tensor input_213_pad_0 = const()[name = tensor("input_213_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_213_mode_0 = const()[name = tensor("input_213_mode_0"), val = tensor("constant")]; + tensor const_25_to_fp16 = const()[name = tensor("const_25_to_fp16"), val = tensor(0x0p+0)]; + tensor input_211_cast_fp16 = transpose(perm = input_211_perm_0, x = inputs_17_cast_fp16)[name = tensor("transpose_500")]; + tensor input_213_cast_fp16 = pad(constant_val = const_25_to_fp16, mode = input_213_mode_0, pad = input_213_pad_0, x = input_211_cast_fp16)[name = tensor("input_213_cast_fp16")]; + tensor x_87_pad_type_0 = const()[name = tensor("x_87_pad_type_0"), val = tensor("valid")]; + tensor x_87_groups_0 = const()[name = tensor("x_87_groups_0"), val = tensor(512)]; + tensor x_87_strides_0 = const()[name = tensor("x_87_strides_0"), val = tensor([1])]; + tensor x_87_pad_0 = const()[name = tensor("x_87_pad_0"), val = tensor([0, 0])]; + tensor x_87_dilations_0 = const()[name = tensor("x_87_dilations_0"), val = tensor([1])]; + tensor e_encoders_7_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_7_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52261568)))]; + tensor x_87_cast_fp16 = conv(dilations = x_87_dilations_0, groups = x_87_groups_0, pad = x_87_pad_0, pad_type = x_87_pad_type_0, strides = x_87_strides_0, weight = e_encoders_7_self_attn_fsmn_block_weight_to_fp16, x = input_213_cast_fp16)[name = tensor("x_87_cast_fp16")]; + tensor x_89_perm_0 = const()[name = tensor("x_89_perm_0"), val = tensor([0, 2, 1])]; + tensor x_89_cast_fp16 = transpose(perm = x_89_perm_0, x = x_87_cast_fp16)[name = tensor("transpose_499")]; + tensor input_215_cast_fp16 = add(x = x_89_cast_fp16, y = inputs_17_cast_fp16)[name = tensor("input_215_cast_fp16")]; + tensor fsmn_memory_17_cast_fp16 = mul(x = input_215_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_17_cast_fp16")]; + tensor var_887_to_fp16 = const()[name = tensor("op_887_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_35_cast_fp16 = mul(x = var_862_cast_fp16, y = var_887_to_fp16)[name = tensor("q_h_35_cast_fp16")]; + tensor scores_33_transpose_x_0 = const()[name = tensor("scores_33_transpose_x_0"), val = tensor(false)]; + tensor scores_33_transpose_y_0 = const()[name = tensor("scores_33_transpose_y_0"), val = tensor(false)]; + tensor transpose_166_perm_0 = const()[name = tensor("transpose_166_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_167_perm_0 = const()[name = tensor("transpose_167_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_167 = transpose(perm = transpose_167_perm_0, x = var_865_cast_fp16)[name = tensor("transpose_497")]; + tensor transpose_166 = transpose(perm = transpose_166_perm_0, x = q_h_35_cast_fp16)[name = tensor("transpose_498")]; + tensor scores_33_cast_fp16 = matmul(transpose_x = scores_33_transpose_x_0, transpose_y = scores_33_transpose_y_0, x = transpose_166, y = transpose_167)[name = tensor("scores_33_cast_fp16")]; + tensor scores_35_cast_fp16 = select(a = var_11_to_fp16, b = scores_33_cast_fp16, cond = mask_5)[name = tensor("scores_35_cast_fp16")]; + tensor var_895_cast_fp16 = softmax(axis = var_20, x = scores_35_cast_fp16)[name = tensor("op_895_cast_fp16")]; + tensor input_217_cast_fp16 = select(a = var_6_to_fp16, b = var_895_cast_fp16, cond = mask_5)[name = tensor("input_217_cast_fp16")]; + tensor x_93_transpose_x_0 = const()[name = tensor("x_93_transpose_x_0"), val = tensor(false)]; + tensor x_93_transpose_y_0 = const()[name = tensor("x_93_transpose_y_0"), val = tensor(false)]; + tensor value_17_cast_fp16 = transpose(perm = value_17_perm_0, x = var_868_cast_fp16)[name = tensor("transpose_501")]; + tensor x_93_cast_fp16 = matmul(transpose_x = x_93_transpose_x_0, transpose_y = x_93_transpose_y_0, x = input_217_cast_fp16, y = value_17_cast_fp16)[name = tensor("x_93_cast_fp16")]; + tensor var_899_perm_0 = const()[name = tensor("op_899_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_901 = const()[name = tensor("op_901"), val = tensor([1, -1, 512])]; + tensor var_899_cast_fp16 = transpose(perm = var_899_perm_0, x = x_93_cast_fp16)[name = tensor("transpose_496")]; + tensor input_219_cast_fp16 = reshape(shape = var_901, x = var_899_cast_fp16)[name = tensor("input_219_cast_fp16")]; + tensor e_encoders_7_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_7_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52272896)))]; + tensor e_encoders_7_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_7_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52797248)))]; + tensor linear_33_cast_fp16 = linear(bias = e_encoders_7_self_attn_linear_out_bias_to_fp16, weight = e_encoders_7_self_attn_linear_out_weight_to_fp16, x = input_219_cast_fp16)[name = tensor("linear_33_cast_fp16")]; + tensor input_221_cast_fp16 = add(x = linear_33_cast_fp16, y = fsmn_memory_17_cast_fp16)[name = tensor("input_221_cast_fp16")]; + tensor input_223_cast_fp16 = add(x = input_209_cast_fp16, y = input_221_cast_fp16)[name = tensor("input_223_cast_fp16")]; + tensor input_225_axes_0 = const()[name = tensor("input_225_axes_0"), val = tensor([-1])]; + tensor e_encoders_7_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_7_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52798336)))]; + tensor e_encoders_7_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_7_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52799424)))]; + tensor input_225_cast_fp16 = layer_norm(axes = input_225_axes_0, beta = e_encoders_7_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_7_norm2_weight_to_fp16, x = input_223_cast_fp16)[name = tensor("input_225_cast_fp16")]; + tensor e_encoders_7_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_7_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52800512)))]; + tensor e_encoders_7_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_7_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54897728)))]; + tensor linear_34_cast_fp16 = linear(bias = e_encoders_7_feed_forward_w_1_bias_to_fp16, weight = e_encoders_7_feed_forward_w_1_weight_to_fp16, x = input_225_cast_fp16)[name = tensor("linear_34_cast_fp16")]; + tensor input_229_cast_fp16 = relu(x = linear_34_cast_fp16)[name = tensor("input_229_cast_fp16")]; + tensor e_encoders_7_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_7_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54901888)))]; + tensor e_encoders_7_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_7_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56999104)))]; + tensor linear_35_cast_fp16 = linear(bias = e_encoders_7_feed_forward_w_2_bias_to_fp16, weight = e_encoders_7_feed_forward_w_2_weight_to_fp16, x = input_229_cast_fp16)[name = tensor("linear_35_cast_fp16")]; + tensor input_235_cast_fp16 = add(x = input_223_cast_fp16, y = linear_35_cast_fp16)[name = tensor("input_235_cast_fp16")]; + tensor x_95_axes_0 = const()[name = tensor("x_95_axes_0"), val = tensor([-1])]; + tensor e_encoders_8_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_8_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57000192)))]; + tensor e_encoders_8_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_8_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57001280)))]; + tensor x_95_cast_fp16 = layer_norm(axes = x_95_axes_0, beta = e_encoders_8_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_8_norm1_weight_to_fp16, x = input_235_cast_fp16)[name = tensor("x_95_cast_fp16")]; + tensor e_encoders_8_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_8_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57002368)))]; + tensor e_encoders_8_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_8_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58575296)))]; + tensor linear_36_cast_fp16 = linear(bias = e_encoders_8_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_8_self_attn_linear_q_k_v_weight_to_fp16, x = x_95_cast_fp16)[name = tensor("linear_36_cast_fp16")]; + tensor tile_9 = const()[name = tensor("tile_9"), val = tensor([512, 512, 512])]; + tensor var_945_axis_0 = const()[name = tensor("op_945_axis_0"), val = tensor(-1)]; + tensor var_945_cast_fp16_0, tensor var_945_cast_fp16_1, tensor var_945_cast_fp16_2 = split(axis = var_945_axis_0, split_sizes = tile_9, x = linear_36_cast_fp16)[name = tensor("op_945_cast_fp16")]; + tensor concat_28x = const()[name = tensor("concat_28x"), val = tensor([1, -1, 4, 128])]; + tensor var_950_cast_fp16 = reshape(shape = concat_28x, x = var_945_cast_fp16_0)[name = tensor("op_950_cast_fp16")]; + tensor concat_29x = const()[name = tensor("concat_29x"), val = tensor([1, -1, 4, 128])]; + tensor var_953_cast_fp16 = reshape(shape = concat_29x, x = var_945_cast_fp16_1)[name = tensor("op_953_cast_fp16")]; + tensor concat_30x = const()[name = tensor("concat_30x"), val = tensor([1, -1, 4, 128])]; + tensor var_956_cast_fp16 = reshape(shape = concat_30x, x = var_945_cast_fp16_2)[name = tensor("op_956_cast_fp16")]; + tensor value_19_perm_0 = const()[name = tensor("value_19_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_19_cast_fp16 = mul(x = var_945_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor input_237_perm_0 = const()[name = tensor("input_237_perm_0"), val = tensor([0, 2, 1])]; + tensor input_239_pad_0 = const()[name = tensor("input_239_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_239_mode_0 = const()[name = tensor("input_239_mode_0"), val = tensor("constant")]; + tensor const_27_to_fp16 = const()[name = tensor("const_27_to_fp16"), val = tensor(0x0p+0)]; + tensor input_237_cast_fp16 = transpose(perm = input_237_perm_0, x = inputs_19_cast_fp16)[name = tensor("transpose_494")]; + tensor input_239_cast_fp16 = pad(constant_val = const_27_to_fp16, mode = input_239_mode_0, pad = input_239_pad_0, x = input_237_cast_fp16)[name = tensor("input_239_cast_fp16")]; + tensor x_97_pad_type_0 = const()[name = tensor("x_97_pad_type_0"), val = tensor("valid")]; + tensor x_97_groups_0 = const()[name = tensor("x_97_groups_0"), val = tensor(512)]; + tensor x_97_strides_0 = const()[name = tensor("x_97_strides_0"), val = tensor([1])]; + tensor x_97_pad_0 = const()[name = tensor("x_97_pad_0"), val = tensor([0, 0])]; + tensor x_97_dilations_0 = const()[name = tensor("x_97_dilations_0"), val = tensor([1])]; + tensor e_encoders_8_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_8_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58578432)))]; + tensor x_97_cast_fp16 = conv(dilations = x_97_dilations_0, groups = x_97_groups_0, pad = x_97_pad_0, pad_type = x_97_pad_type_0, strides = x_97_strides_0, weight = e_encoders_8_self_attn_fsmn_block_weight_to_fp16, x = input_239_cast_fp16)[name = tensor("x_97_cast_fp16")]; + tensor x_99_perm_0 = const()[name = tensor("x_99_perm_0"), val = tensor([0, 2, 1])]; + tensor x_99_cast_fp16 = transpose(perm = x_99_perm_0, x = x_97_cast_fp16)[name = tensor("transpose_493")]; + tensor input_241_cast_fp16 = add(x = x_99_cast_fp16, y = inputs_19_cast_fp16)[name = tensor("input_241_cast_fp16")]; + tensor fsmn_memory_19_cast_fp16 = mul(x = input_241_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_19_cast_fp16")]; + tensor var_975_to_fp16 = const()[name = tensor("op_975_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_39_cast_fp16 = mul(x = var_950_cast_fp16, y = var_975_to_fp16)[name = tensor("q_h_39_cast_fp16")]; + tensor scores_37_transpose_x_0 = const()[name = tensor("scores_37_transpose_x_0"), val = tensor(false)]; + tensor scores_37_transpose_y_0 = const()[name = tensor("scores_37_transpose_y_0"), val = tensor(false)]; + tensor transpose_168_perm_0 = const()[name = tensor("transpose_168_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_169_perm_0 = const()[name = tensor("transpose_169_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_169 = transpose(perm = transpose_169_perm_0, x = var_953_cast_fp16)[name = tensor("transpose_491")]; + tensor transpose_168 = transpose(perm = transpose_168_perm_0, x = q_h_39_cast_fp16)[name = tensor("transpose_492")]; + tensor scores_37_cast_fp16 = matmul(transpose_x = scores_37_transpose_x_0, transpose_y = scores_37_transpose_y_0, x = transpose_168, y = transpose_169)[name = tensor("scores_37_cast_fp16")]; + tensor scores_39_cast_fp16 = select(a = var_11_to_fp16, b = scores_37_cast_fp16, cond = mask_5)[name = tensor("scores_39_cast_fp16")]; + tensor var_983_cast_fp16 = softmax(axis = var_20, x = scores_39_cast_fp16)[name = tensor("op_983_cast_fp16")]; + tensor input_243_cast_fp16 = select(a = var_6_to_fp16, b = var_983_cast_fp16, cond = mask_5)[name = tensor("input_243_cast_fp16")]; + tensor x_103_transpose_x_0 = const()[name = tensor("x_103_transpose_x_0"), val = tensor(false)]; + tensor x_103_transpose_y_0 = const()[name = tensor("x_103_transpose_y_0"), val = tensor(false)]; + tensor value_19_cast_fp16 = transpose(perm = value_19_perm_0, x = var_956_cast_fp16)[name = tensor("transpose_495")]; + tensor x_103_cast_fp16 = matmul(transpose_x = x_103_transpose_x_0, transpose_y = x_103_transpose_y_0, x = input_243_cast_fp16, y = value_19_cast_fp16)[name = tensor("x_103_cast_fp16")]; + tensor var_987_perm_0 = const()[name = tensor("op_987_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_989 = const()[name = tensor("op_989"), val = tensor([1, -1, 512])]; + tensor var_987_cast_fp16 = transpose(perm = var_987_perm_0, x = x_103_cast_fp16)[name = tensor("transpose_490")]; + tensor input_245_cast_fp16 = reshape(shape = var_989, x = var_987_cast_fp16)[name = tensor("input_245_cast_fp16")]; + tensor e_encoders_8_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_8_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58589760)))]; + tensor e_encoders_8_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_8_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59114112)))]; + tensor linear_37_cast_fp16 = linear(bias = e_encoders_8_self_attn_linear_out_bias_to_fp16, weight = e_encoders_8_self_attn_linear_out_weight_to_fp16, x = input_245_cast_fp16)[name = tensor("linear_37_cast_fp16")]; + tensor input_247_cast_fp16 = add(x = linear_37_cast_fp16, y = fsmn_memory_19_cast_fp16)[name = tensor("input_247_cast_fp16")]; + tensor input_249_cast_fp16 = add(x = input_235_cast_fp16, y = input_247_cast_fp16)[name = tensor("input_249_cast_fp16")]; + tensor input_251_axes_0 = const()[name = tensor("input_251_axes_0"), val = tensor([-1])]; + tensor e_encoders_8_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_8_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59115200)))]; + tensor e_encoders_8_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_8_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59116288)))]; + tensor input_251_cast_fp16 = layer_norm(axes = input_251_axes_0, beta = e_encoders_8_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_8_norm2_weight_to_fp16, x = input_249_cast_fp16)[name = tensor("input_251_cast_fp16")]; + tensor e_encoders_8_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_8_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59117376)))]; + tensor e_encoders_8_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_8_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61214592)))]; + tensor linear_38_cast_fp16 = linear(bias = e_encoders_8_feed_forward_w_1_bias_to_fp16, weight = e_encoders_8_feed_forward_w_1_weight_to_fp16, x = input_251_cast_fp16)[name = tensor("linear_38_cast_fp16")]; + tensor input_255_cast_fp16 = relu(x = linear_38_cast_fp16)[name = tensor("input_255_cast_fp16")]; + tensor e_encoders_8_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_8_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61218752)))]; + tensor e_encoders_8_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_8_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63315968)))]; + tensor linear_39_cast_fp16 = linear(bias = e_encoders_8_feed_forward_w_2_bias_to_fp16, weight = e_encoders_8_feed_forward_w_2_weight_to_fp16, x = input_255_cast_fp16)[name = tensor("linear_39_cast_fp16")]; + tensor input_261_cast_fp16 = add(x = input_249_cast_fp16, y = linear_39_cast_fp16)[name = tensor("input_261_cast_fp16")]; + tensor x_105_axes_0 = const()[name = tensor("x_105_axes_0"), val = tensor([-1])]; + tensor e_encoders_9_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_9_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63317056)))]; + tensor e_encoders_9_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_9_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63318144)))]; + tensor x_105_cast_fp16 = layer_norm(axes = x_105_axes_0, beta = e_encoders_9_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_9_norm1_weight_to_fp16, x = input_261_cast_fp16)[name = tensor("x_105_cast_fp16")]; + tensor e_encoders_9_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_9_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63319232)))]; + tensor e_encoders_9_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_9_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64892160)))]; + tensor linear_40_cast_fp16 = linear(bias = e_encoders_9_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_9_self_attn_linear_q_k_v_weight_to_fp16, x = x_105_cast_fp16)[name = tensor("linear_40_cast_fp16")]; + tensor tile_10 = const()[name = tensor("tile_10"), val = tensor([512, 512, 512])]; + tensor var_1033_axis_0 = const()[name = tensor("op_1033_axis_0"), val = tensor(-1)]; + tensor var_1033_cast_fp16_0, tensor var_1033_cast_fp16_1, tensor var_1033_cast_fp16_2 = split(axis = var_1033_axis_0, split_sizes = tile_10, x = linear_40_cast_fp16)[name = tensor("op_1033_cast_fp16")]; + tensor concat_31x = const()[name = tensor("concat_31x"), val = tensor([1, -1, 4, 128])]; + tensor var_1038_cast_fp16 = reshape(shape = concat_31x, x = var_1033_cast_fp16_0)[name = tensor("op_1038_cast_fp16")]; + tensor concat_32x = const()[name = tensor("concat_32x"), val = tensor([1, -1, 4, 128])]; + tensor var_1041_cast_fp16 = reshape(shape = concat_32x, x = var_1033_cast_fp16_1)[name = tensor("op_1041_cast_fp16")]; + tensor concat_33x = const()[name = tensor("concat_33x"), val = tensor([1, -1, 4, 128])]; + tensor var_1044_cast_fp16 = reshape(shape = concat_33x, x = var_1033_cast_fp16_2)[name = tensor("op_1044_cast_fp16")]; + tensor value_21_perm_0 = const()[name = tensor("value_21_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_21_cast_fp16 = mul(x = var_1033_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor input_263_perm_0 = const()[name = tensor("input_263_perm_0"), val = tensor([0, 2, 1])]; + tensor input_265_pad_0 = const()[name = tensor("input_265_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_265_mode_0 = const()[name = tensor("input_265_mode_0"), val = tensor("constant")]; + tensor const_29_to_fp16 = const()[name = tensor("const_29_to_fp16"), val = tensor(0x0p+0)]; + tensor input_263_cast_fp16 = transpose(perm = input_263_perm_0, x = inputs_21_cast_fp16)[name = tensor("transpose_488")]; + tensor input_265_cast_fp16 = pad(constant_val = const_29_to_fp16, mode = input_265_mode_0, pad = input_265_pad_0, x = input_263_cast_fp16)[name = tensor("input_265_cast_fp16")]; + tensor x_107_pad_type_0 = const()[name = tensor("x_107_pad_type_0"), val = tensor("valid")]; + tensor x_107_groups_0 = const()[name = tensor("x_107_groups_0"), val = tensor(512)]; + tensor x_107_strides_0 = const()[name = tensor("x_107_strides_0"), val = tensor([1])]; + tensor x_107_pad_0 = const()[name = tensor("x_107_pad_0"), val = tensor([0, 0])]; + tensor x_107_dilations_0 = const()[name = tensor("x_107_dilations_0"), val = tensor([1])]; + tensor e_encoders_9_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_9_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64895296)))]; + tensor x_107_cast_fp16 = conv(dilations = x_107_dilations_0, groups = x_107_groups_0, pad = x_107_pad_0, pad_type = x_107_pad_type_0, strides = x_107_strides_0, weight = e_encoders_9_self_attn_fsmn_block_weight_to_fp16, x = input_265_cast_fp16)[name = tensor("x_107_cast_fp16")]; + tensor x_109_perm_0 = const()[name = tensor("x_109_perm_0"), val = tensor([0, 2, 1])]; + tensor x_109_cast_fp16 = transpose(perm = x_109_perm_0, x = x_107_cast_fp16)[name = tensor("transpose_487")]; + tensor input_267_cast_fp16 = add(x = x_109_cast_fp16, y = inputs_21_cast_fp16)[name = tensor("input_267_cast_fp16")]; + tensor fsmn_memory_21_cast_fp16 = mul(x = input_267_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_21_cast_fp16")]; + tensor var_1063_to_fp16 = const()[name = tensor("op_1063_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_43_cast_fp16 = mul(x = var_1038_cast_fp16, y = var_1063_to_fp16)[name = tensor("q_h_43_cast_fp16")]; + tensor scores_41_transpose_x_0 = const()[name = tensor("scores_41_transpose_x_0"), val = tensor(false)]; + tensor scores_41_transpose_y_0 = const()[name = tensor("scores_41_transpose_y_0"), val = tensor(false)]; + tensor transpose_170_perm_0 = const()[name = tensor("transpose_170_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_171_perm_0 = const()[name = tensor("transpose_171_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_171 = transpose(perm = transpose_171_perm_0, x = var_1041_cast_fp16)[name = tensor("transpose_485")]; + tensor transpose_170 = transpose(perm = transpose_170_perm_0, x = q_h_43_cast_fp16)[name = tensor("transpose_486")]; + tensor scores_41_cast_fp16 = matmul(transpose_x = scores_41_transpose_x_0, transpose_y = scores_41_transpose_y_0, x = transpose_170, y = transpose_171)[name = tensor("scores_41_cast_fp16")]; + tensor scores_43_cast_fp16 = select(a = var_11_to_fp16, b = scores_41_cast_fp16, cond = mask_5)[name = tensor("scores_43_cast_fp16")]; + tensor var_1071_cast_fp16 = softmax(axis = var_20, x = scores_43_cast_fp16)[name = tensor("op_1071_cast_fp16")]; + tensor input_269_cast_fp16 = select(a = var_6_to_fp16, b = var_1071_cast_fp16, cond = mask_5)[name = tensor("input_269_cast_fp16")]; + tensor x_113_transpose_x_0 = const()[name = tensor("x_113_transpose_x_0"), val = tensor(false)]; + tensor x_113_transpose_y_0 = const()[name = tensor("x_113_transpose_y_0"), val = tensor(false)]; + tensor value_21_cast_fp16 = transpose(perm = value_21_perm_0, x = var_1044_cast_fp16)[name = tensor("transpose_489")]; + tensor x_113_cast_fp16 = matmul(transpose_x = x_113_transpose_x_0, transpose_y = x_113_transpose_y_0, x = input_269_cast_fp16, y = value_21_cast_fp16)[name = tensor("x_113_cast_fp16")]; + tensor var_1075_perm_0 = const()[name = tensor("op_1075_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1077 = const()[name = tensor("op_1077"), val = tensor([1, -1, 512])]; + tensor var_1075_cast_fp16 = transpose(perm = var_1075_perm_0, x = x_113_cast_fp16)[name = tensor("transpose_484")]; + tensor input_271_cast_fp16 = reshape(shape = var_1077, x = var_1075_cast_fp16)[name = tensor("input_271_cast_fp16")]; + tensor e_encoders_9_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_9_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64906624)))]; + tensor e_encoders_9_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_9_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65430976)))]; + tensor linear_41_cast_fp16 = linear(bias = e_encoders_9_self_attn_linear_out_bias_to_fp16, weight = e_encoders_9_self_attn_linear_out_weight_to_fp16, x = input_271_cast_fp16)[name = tensor("linear_41_cast_fp16")]; + tensor input_273_cast_fp16 = add(x = linear_41_cast_fp16, y = fsmn_memory_21_cast_fp16)[name = tensor("input_273_cast_fp16")]; + tensor input_275_cast_fp16 = add(x = input_261_cast_fp16, y = input_273_cast_fp16)[name = tensor("input_275_cast_fp16")]; + tensor input_277_axes_0 = const()[name = tensor("input_277_axes_0"), val = tensor([-1])]; + tensor e_encoders_9_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_9_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65432064)))]; + tensor e_encoders_9_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_9_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65433152)))]; + tensor input_277_cast_fp16 = layer_norm(axes = input_277_axes_0, beta = e_encoders_9_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_9_norm2_weight_to_fp16, x = input_275_cast_fp16)[name = tensor("input_277_cast_fp16")]; + tensor e_encoders_9_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_9_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65434240)))]; + tensor e_encoders_9_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_9_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67531456)))]; + tensor linear_42_cast_fp16 = linear(bias = e_encoders_9_feed_forward_w_1_bias_to_fp16, weight = e_encoders_9_feed_forward_w_1_weight_to_fp16, x = input_277_cast_fp16)[name = tensor("linear_42_cast_fp16")]; + tensor input_281_cast_fp16 = relu(x = linear_42_cast_fp16)[name = tensor("input_281_cast_fp16")]; + tensor e_encoders_9_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_9_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67535616)))]; + tensor e_encoders_9_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_9_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69632832)))]; + tensor linear_43_cast_fp16 = linear(bias = e_encoders_9_feed_forward_w_2_bias_to_fp16, weight = e_encoders_9_feed_forward_w_2_weight_to_fp16, x = input_281_cast_fp16)[name = tensor("linear_43_cast_fp16")]; + tensor input_287_cast_fp16 = add(x = input_275_cast_fp16, y = linear_43_cast_fp16)[name = tensor("input_287_cast_fp16")]; + tensor x_115_axes_0 = const()[name = tensor("x_115_axes_0"), val = tensor([-1])]; + tensor e_encoders_10_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_10_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69633920)))]; + tensor e_encoders_10_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_10_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69635008)))]; + tensor x_115_cast_fp16 = layer_norm(axes = x_115_axes_0, beta = e_encoders_10_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_10_norm1_weight_to_fp16, x = input_287_cast_fp16)[name = tensor("x_115_cast_fp16")]; + tensor e_encoders_10_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_10_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69636096)))]; + tensor e_encoders_10_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_10_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71209024)))]; + tensor linear_44_cast_fp16 = linear(bias = e_encoders_10_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_10_self_attn_linear_q_k_v_weight_to_fp16, x = x_115_cast_fp16)[name = tensor("linear_44_cast_fp16")]; + tensor tile_11 = const()[name = tensor("tile_11"), val = tensor([512, 512, 512])]; + tensor var_1121_axis_0 = const()[name = tensor("op_1121_axis_0"), val = tensor(-1)]; + tensor var_1121_cast_fp16_0, tensor var_1121_cast_fp16_1, tensor var_1121_cast_fp16_2 = split(axis = var_1121_axis_0, split_sizes = tile_11, x = linear_44_cast_fp16)[name = tensor("op_1121_cast_fp16")]; + tensor concat_34x = const()[name = tensor("concat_34x"), val = tensor([1, -1, 4, 128])]; + tensor var_1126_cast_fp16 = reshape(shape = concat_34x, x = var_1121_cast_fp16_0)[name = tensor("op_1126_cast_fp16")]; + tensor concat_35x = const()[name = tensor("concat_35x"), val = tensor([1, -1, 4, 128])]; + tensor var_1129_cast_fp16 = reshape(shape = concat_35x, x = var_1121_cast_fp16_1)[name = tensor("op_1129_cast_fp16")]; + tensor concat_36x = const()[name = tensor("concat_36x"), val = tensor([1, -1, 4, 128])]; + tensor var_1132_cast_fp16 = reshape(shape = concat_36x, x = var_1121_cast_fp16_2)[name = tensor("op_1132_cast_fp16")]; + tensor value_23_perm_0 = const()[name = tensor("value_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_23_cast_fp16 = mul(x = var_1121_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor input_289_perm_0 = const()[name = tensor("input_289_perm_0"), val = tensor([0, 2, 1])]; + tensor input_291_pad_0 = const()[name = tensor("input_291_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_291_mode_0 = const()[name = tensor("input_291_mode_0"), val = tensor("constant")]; + tensor const_31_to_fp16 = const()[name = tensor("const_31_to_fp16"), val = tensor(0x0p+0)]; + tensor input_289_cast_fp16 = transpose(perm = input_289_perm_0, x = inputs_23_cast_fp16)[name = tensor("transpose_482")]; + tensor input_291_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_291_mode_0, pad = input_291_pad_0, x = input_289_cast_fp16)[name = tensor("input_291_cast_fp16")]; + tensor x_117_pad_type_0 = const()[name = tensor("x_117_pad_type_0"), val = tensor("valid")]; + tensor x_117_groups_0 = const()[name = tensor("x_117_groups_0"), val = tensor(512)]; + tensor x_117_strides_0 = const()[name = tensor("x_117_strides_0"), val = tensor([1])]; + tensor x_117_pad_0 = const()[name = tensor("x_117_pad_0"), val = tensor([0, 0])]; + tensor x_117_dilations_0 = const()[name = tensor("x_117_dilations_0"), val = tensor([1])]; + tensor e_encoders_10_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_10_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71212160)))]; + tensor x_117_cast_fp16 = conv(dilations = x_117_dilations_0, groups = x_117_groups_0, pad = x_117_pad_0, pad_type = x_117_pad_type_0, strides = x_117_strides_0, weight = e_encoders_10_self_attn_fsmn_block_weight_to_fp16, x = input_291_cast_fp16)[name = tensor("x_117_cast_fp16")]; + tensor x_119_perm_0 = const()[name = tensor("x_119_perm_0"), val = tensor([0, 2, 1])]; + tensor x_119_cast_fp16 = transpose(perm = x_119_perm_0, x = x_117_cast_fp16)[name = tensor("transpose_481")]; + tensor input_293_cast_fp16 = add(x = x_119_cast_fp16, y = inputs_23_cast_fp16)[name = tensor("input_293_cast_fp16")]; + tensor fsmn_memory_23_cast_fp16 = mul(x = input_293_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_23_cast_fp16")]; + tensor var_1151_to_fp16 = const()[name = tensor("op_1151_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_47_cast_fp16 = mul(x = var_1126_cast_fp16, y = var_1151_to_fp16)[name = tensor("q_h_47_cast_fp16")]; + tensor scores_45_transpose_x_0 = const()[name = tensor("scores_45_transpose_x_0"), val = tensor(false)]; + tensor scores_45_transpose_y_0 = const()[name = tensor("scores_45_transpose_y_0"), val = tensor(false)]; + tensor transpose_172_perm_0 = const()[name = tensor("transpose_172_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_173_perm_0 = const()[name = tensor("transpose_173_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_173 = transpose(perm = transpose_173_perm_0, x = var_1129_cast_fp16)[name = tensor("transpose_479")]; + tensor transpose_172 = transpose(perm = transpose_172_perm_0, x = q_h_47_cast_fp16)[name = tensor("transpose_480")]; + tensor scores_45_cast_fp16 = matmul(transpose_x = scores_45_transpose_x_0, transpose_y = scores_45_transpose_y_0, x = transpose_172, y = transpose_173)[name = tensor("scores_45_cast_fp16")]; + tensor scores_47_cast_fp16 = select(a = var_11_to_fp16, b = scores_45_cast_fp16, cond = mask_5)[name = tensor("scores_47_cast_fp16")]; + tensor var_1159_cast_fp16 = softmax(axis = var_20, x = scores_47_cast_fp16)[name = tensor("op_1159_cast_fp16")]; + tensor input_295_cast_fp16 = select(a = var_6_to_fp16, b = var_1159_cast_fp16, cond = mask_5)[name = tensor("input_295_cast_fp16")]; + tensor x_123_transpose_x_0 = const()[name = tensor("x_123_transpose_x_0"), val = tensor(false)]; + tensor x_123_transpose_y_0 = const()[name = tensor("x_123_transpose_y_0"), val = tensor(false)]; + tensor value_23_cast_fp16 = transpose(perm = value_23_perm_0, x = var_1132_cast_fp16)[name = tensor("transpose_483")]; + tensor x_123_cast_fp16 = matmul(transpose_x = x_123_transpose_x_0, transpose_y = x_123_transpose_y_0, x = input_295_cast_fp16, y = value_23_cast_fp16)[name = tensor("x_123_cast_fp16")]; + tensor var_1163_perm_0 = const()[name = tensor("op_1163_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1165 = const()[name = tensor("op_1165"), val = tensor([1, -1, 512])]; + tensor var_1163_cast_fp16 = transpose(perm = var_1163_perm_0, x = x_123_cast_fp16)[name = tensor("transpose_478")]; + tensor input_297_cast_fp16 = reshape(shape = var_1165, x = var_1163_cast_fp16)[name = tensor("input_297_cast_fp16")]; + tensor e_encoders_10_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_10_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71223488)))]; + tensor e_encoders_10_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_10_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71747840)))]; + tensor linear_45_cast_fp16 = linear(bias = e_encoders_10_self_attn_linear_out_bias_to_fp16, weight = e_encoders_10_self_attn_linear_out_weight_to_fp16, x = input_297_cast_fp16)[name = tensor("linear_45_cast_fp16")]; + tensor input_299_cast_fp16 = add(x = linear_45_cast_fp16, y = fsmn_memory_23_cast_fp16)[name = tensor("input_299_cast_fp16")]; + tensor input_301_cast_fp16 = add(x = input_287_cast_fp16, y = input_299_cast_fp16)[name = tensor("input_301_cast_fp16")]; + tensor input_303_axes_0 = const()[name = tensor("input_303_axes_0"), val = tensor([-1])]; + tensor e_encoders_10_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_10_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71748928)))]; + tensor e_encoders_10_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_10_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71750016)))]; + tensor input_303_cast_fp16 = layer_norm(axes = input_303_axes_0, beta = e_encoders_10_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_10_norm2_weight_to_fp16, x = input_301_cast_fp16)[name = tensor("input_303_cast_fp16")]; + tensor e_encoders_10_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_10_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71751104)))]; + tensor e_encoders_10_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_10_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73848320)))]; + tensor linear_46_cast_fp16 = linear(bias = e_encoders_10_feed_forward_w_1_bias_to_fp16, weight = e_encoders_10_feed_forward_w_1_weight_to_fp16, x = input_303_cast_fp16)[name = tensor("linear_46_cast_fp16")]; + tensor input_307_cast_fp16 = relu(x = linear_46_cast_fp16)[name = tensor("input_307_cast_fp16")]; + tensor e_encoders_10_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_10_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73852480)))]; + tensor e_encoders_10_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_10_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75949696)))]; + tensor linear_47_cast_fp16 = linear(bias = e_encoders_10_feed_forward_w_2_bias_to_fp16, weight = e_encoders_10_feed_forward_w_2_weight_to_fp16, x = input_307_cast_fp16)[name = tensor("linear_47_cast_fp16")]; + tensor input_313_cast_fp16 = add(x = input_301_cast_fp16, y = linear_47_cast_fp16)[name = tensor("input_313_cast_fp16")]; + tensor x_125_axes_0 = const()[name = tensor("x_125_axes_0"), val = tensor([-1])]; + tensor e_encoders_11_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_11_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75950784)))]; + tensor e_encoders_11_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_11_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75951872)))]; + tensor x_125_cast_fp16 = layer_norm(axes = x_125_axes_0, beta = e_encoders_11_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_11_norm1_weight_to_fp16, x = input_313_cast_fp16)[name = tensor("x_125_cast_fp16")]; + tensor e_encoders_11_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_11_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75952960)))]; + tensor e_encoders_11_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_11_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77525888)))]; + tensor linear_48_cast_fp16 = linear(bias = e_encoders_11_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_11_self_attn_linear_q_k_v_weight_to_fp16, x = x_125_cast_fp16)[name = tensor("linear_48_cast_fp16")]; + tensor tile_12 = const()[name = tensor("tile_12"), val = tensor([512, 512, 512])]; + tensor var_1209_axis_0 = const()[name = tensor("op_1209_axis_0"), val = tensor(-1)]; + tensor var_1209_cast_fp16_0, tensor var_1209_cast_fp16_1, tensor var_1209_cast_fp16_2 = split(axis = var_1209_axis_0, split_sizes = tile_12, x = linear_48_cast_fp16)[name = tensor("op_1209_cast_fp16")]; + tensor concat_37x = const()[name = tensor("concat_37x"), val = tensor([1, -1, 4, 128])]; + tensor var_1214_cast_fp16 = reshape(shape = concat_37x, x = var_1209_cast_fp16_0)[name = tensor("op_1214_cast_fp16")]; + tensor concat_38x = const()[name = tensor("concat_38x"), val = tensor([1, -1, 4, 128])]; + tensor var_1217_cast_fp16 = reshape(shape = concat_38x, x = var_1209_cast_fp16_1)[name = tensor("op_1217_cast_fp16")]; + tensor concat_39x = const()[name = tensor("concat_39x"), val = tensor([1, -1, 4, 128])]; + tensor var_1220_cast_fp16 = reshape(shape = concat_39x, x = var_1209_cast_fp16_2)[name = tensor("op_1220_cast_fp16")]; + tensor value_25_perm_0 = const()[name = tensor("value_25_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_25_cast_fp16 = mul(x = var_1209_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor input_315_perm_0 = const()[name = tensor("input_315_perm_0"), val = tensor([0, 2, 1])]; + tensor input_317_pad_0 = const()[name = tensor("input_317_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_317_mode_0 = const()[name = tensor("input_317_mode_0"), val = tensor("constant")]; + tensor const_33_to_fp16 = const()[name = tensor("const_33_to_fp16"), val = tensor(0x0p+0)]; + tensor input_315_cast_fp16 = transpose(perm = input_315_perm_0, x = inputs_25_cast_fp16)[name = tensor("transpose_476")]; + tensor input_317_cast_fp16 = pad(constant_val = const_33_to_fp16, mode = input_317_mode_0, pad = input_317_pad_0, x = input_315_cast_fp16)[name = tensor("input_317_cast_fp16")]; + tensor x_127_pad_type_0 = const()[name = tensor("x_127_pad_type_0"), val = tensor("valid")]; + tensor x_127_groups_0 = const()[name = tensor("x_127_groups_0"), val = tensor(512)]; + tensor x_127_strides_0 = const()[name = tensor("x_127_strides_0"), val = tensor([1])]; + tensor x_127_pad_0 = const()[name = tensor("x_127_pad_0"), val = tensor([0, 0])]; + tensor x_127_dilations_0 = const()[name = tensor("x_127_dilations_0"), val = tensor([1])]; + tensor e_encoders_11_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_11_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77529024)))]; + tensor x_127_cast_fp16 = conv(dilations = x_127_dilations_0, groups = x_127_groups_0, pad = x_127_pad_0, pad_type = x_127_pad_type_0, strides = x_127_strides_0, weight = e_encoders_11_self_attn_fsmn_block_weight_to_fp16, x = input_317_cast_fp16)[name = tensor("x_127_cast_fp16")]; + tensor x_129_perm_0 = const()[name = tensor("x_129_perm_0"), val = tensor([0, 2, 1])]; + tensor x_129_cast_fp16 = transpose(perm = x_129_perm_0, x = x_127_cast_fp16)[name = tensor("transpose_475")]; + tensor input_319_cast_fp16 = add(x = x_129_cast_fp16, y = inputs_25_cast_fp16)[name = tensor("input_319_cast_fp16")]; + tensor fsmn_memory_25_cast_fp16 = mul(x = input_319_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_25_cast_fp16")]; + tensor var_1239_to_fp16 = const()[name = tensor("op_1239_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_51_cast_fp16 = mul(x = var_1214_cast_fp16, y = var_1239_to_fp16)[name = tensor("q_h_51_cast_fp16")]; + tensor scores_49_transpose_x_0 = const()[name = tensor("scores_49_transpose_x_0"), val = tensor(false)]; + tensor scores_49_transpose_y_0 = const()[name = tensor("scores_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_174_perm_0 = const()[name = tensor("transpose_174_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_175_perm_0 = const()[name = tensor("transpose_175_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_175 = transpose(perm = transpose_175_perm_0, x = var_1217_cast_fp16)[name = tensor("transpose_473")]; + tensor transpose_174 = transpose(perm = transpose_174_perm_0, x = q_h_51_cast_fp16)[name = tensor("transpose_474")]; + tensor scores_49_cast_fp16 = matmul(transpose_x = scores_49_transpose_x_0, transpose_y = scores_49_transpose_y_0, x = transpose_174, y = transpose_175)[name = tensor("scores_49_cast_fp16")]; + tensor scores_51_cast_fp16 = select(a = var_11_to_fp16, b = scores_49_cast_fp16, cond = mask_5)[name = tensor("scores_51_cast_fp16")]; + tensor var_1247_cast_fp16 = softmax(axis = var_20, x = scores_51_cast_fp16)[name = tensor("op_1247_cast_fp16")]; + tensor input_321_cast_fp16 = select(a = var_6_to_fp16, b = var_1247_cast_fp16, cond = mask_5)[name = tensor("input_321_cast_fp16")]; + tensor x_133_transpose_x_0 = const()[name = tensor("x_133_transpose_x_0"), val = tensor(false)]; + tensor x_133_transpose_y_0 = const()[name = tensor("x_133_transpose_y_0"), val = tensor(false)]; + tensor value_25_cast_fp16 = transpose(perm = value_25_perm_0, x = var_1220_cast_fp16)[name = tensor("transpose_477")]; + tensor x_133_cast_fp16 = matmul(transpose_x = x_133_transpose_x_0, transpose_y = x_133_transpose_y_0, x = input_321_cast_fp16, y = value_25_cast_fp16)[name = tensor("x_133_cast_fp16")]; + tensor var_1251_perm_0 = const()[name = tensor("op_1251_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1253 = const()[name = tensor("op_1253"), val = tensor([1, -1, 512])]; + tensor var_1251_cast_fp16 = transpose(perm = var_1251_perm_0, x = x_133_cast_fp16)[name = tensor("transpose_472")]; + tensor input_323_cast_fp16 = reshape(shape = var_1253, x = var_1251_cast_fp16)[name = tensor("input_323_cast_fp16")]; + tensor e_encoders_11_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_11_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77540352)))]; + tensor e_encoders_11_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_11_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78064704)))]; + tensor linear_49_cast_fp16 = linear(bias = e_encoders_11_self_attn_linear_out_bias_to_fp16, weight = e_encoders_11_self_attn_linear_out_weight_to_fp16, x = input_323_cast_fp16)[name = tensor("linear_49_cast_fp16")]; + tensor input_325_cast_fp16 = add(x = linear_49_cast_fp16, y = fsmn_memory_25_cast_fp16)[name = tensor("input_325_cast_fp16")]; + tensor input_327_cast_fp16 = add(x = input_313_cast_fp16, y = input_325_cast_fp16)[name = tensor("input_327_cast_fp16")]; + tensor input_329_axes_0 = const()[name = tensor("input_329_axes_0"), val = tensor([-1])]; + tensor e_encoders_11_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_11_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78065792)))]; + tensor e_encoders_11_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_11_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78066880)))]; + tensor input_329_cast_fp16 = layer_norm(axes = input_329_axes_0, beta = e_encoders_11_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_11_norm2_weight_to_fp16, x = input_327_cast_fp16)[name = tensor("input_329_cast_fp16")]; + tensor e_encoders_11_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_11_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78067968)))]; + tensor e_encoders_11_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_11_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80165184)))]; + tensor linear_50_cast_fp16 = linear(bias = e_encoders_11_feed_forward_w_1_bias_to_fp16, weight = e_encoders_11_feed_forward_w_1_weight_to_fp16, x = input_329_cast_fp16)[name = tensor("linear_50_cast_fp16")]; + tensor input_333_cast_fp16 = relu(x = linear_50_cast_fp16)[name = tensor("input_333_cast_fp16")]; + tensor e_encoders_11_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_11_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80169344)))]; + tensor e_encoders_11_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_11_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82266560)))]; + tensor linear_51_cast_fp16 = linear(bias = e_encoders_11_feed_forward_w_2_bias_to_fp16, weight = e_encoders_11_feed_forward_w_2_weight_to_fp16, x = input_333_cast_fp16)[name = tensor("linear_51_cast_fp16")]; + tensor input_339_cast_fp16 = add(x = input_327_cast_fp16, y = linear_51_cast_fp16)[name = tensor("input_339_cast_fp16")]; + tensor x_135_axes_0 = const()[name = tensor("x_135_axes_0"), val = tensor([-1])]; + tensor e_encoders_12_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_12_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82267648)))]; + tensor e_encoders_12_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_12_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82268736)))]; + tensor x_135_cast_fp16 = layer_norm(axes = x_135_axes_0, beta = e_encoders_12_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_12_norm1_weight_to_fp16, x = input_339_cast_fp16)[name = tensor("x_135_cast_fp16")]; + tensor e_encoders_12_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_12_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82269824)))]; + tensor e_encoders_12_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_12_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83842752)))]; + tensor linear_52_cast_fp16 = linear(bias = e_encoders_12_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_12_self_attn_linear_q_k_v_weight_to_fp16, x = x_135_cast_fp16)[name = tensor("linear_52_cast_fp16")]; + tensor tile_13 = const()[name = tensor("tile_13"), val = tensor([512, 512, 512])]; + tensor var_1297_axis_0 = const()[name = tensor("op_1297_axis_0"), val = tensor(-1)]; + tensor var_1297_cast_fp16_0, tensor var_1297_cast_fp16_1, tensor var_1297_cast_fp16_2 = split(axis = var_1297_axis_0, split_sizes = tile_13, x = linear_52_cast_fp16)[name = tensor("op_1297_cast_fp16")]; + tensor concat_40x = const()[name = tensor("concat_40x"), val = tensor([1, -1, 4, 128])]; + tensor var_1302_cast_fp16 = reshape(shape = concat_40x, x = var_1297_cast_fp16_0)[name = tensor("op_1302_cast_fp16")]; + tensor concat_41x = const()[name = tensor("concat_41x"), val = tensor([1, -1, 4, 128])]; + tensor var_1305_cast_fp16 = reshape(shape = concat_41x, x = var_1297_cast_fp16_1)[name = tensor("op_1305_cast_fp16")]; + tensor concat_42x = const()[name = tensor("concat_42x"), val = tensor([1, -1, 4, 128])]; + tensor var_1308_cast_fp16 = reshape(shape = concat_42x, x = var_1297_cast_fp16_2)[name = tensor("op_1308_cast_fp16")]; + tensor value_27_perm_0 = const()[name = tensor("value_27_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_27_cast_fp16 = mul(x = var_1297_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor input_341_perm_0 = const()[name = tensor("input_341_perm_0"), val = tensor([0, 2, 1])]; + tensor input_343_pad_0 = const()[name = tensor("input_343_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_343_mode_0 = const()[name = tensor("input_343_mode_0"), val = tensor("constant")]; + tensor const_35_to_fp16 = const()[name = tensor("const_35_to_fp16"), val = tensor(0x0p+0)]; + tensor input_341_cast_fp16 = transpose(perm = input_341_perm_0, x = inputs_27_cast_fp16)[name = tensor("transpose_470")]; + tensor input_343_cast_fp16 = pad(constant_val = const_35_to_fp16, mode = input_343_mode_0, pad = input_343_pad_0, x = input_341_cast_fp16)[name = tensor("input_343_cast_fp16")]; + tensor x_137_pad_type_0 = const()[name = tensor("x_137_pad_type_0"), val = tensor("valid")]; + tensor x_137_groups_0 = const()[name = tensor("x_137_groups_0"), val = tensor(512)]; + tensor x_137_strides_0 = const()[name = tensor("x_137_strides_0"), val = tensor([1])]; + tensor x_137_pad_0 = const()[name = tensor("x_137_pad_0"), val = tensor([0, 0])]; + tensor x_137_dilations_0 = const()[name = tensor("x_137_dilations_0"), val = tensor([1])]; + tensor e_encoders_12_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_12_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83845888)))]; + tensor x_137_cast_fp16 = conv(dilations = x_137_dilations_0, groups = x_137_groups_0, pad = x_137_pad_0, pad_type = x_137_pad_type_0, strides = x_137_strides_0, weight = e_encoders_12_self_attn_fsmn_block_weight_to_fp16, x = input_343_cast_fp16)[name = tensor("x_137_cast_fp16")]; + tensor x_139_perm_0 = const()[name = tensor("x_139_perm_0"), val = tensor([0, 2, 1])]; + tensor x_139_cast_fp16 = transpose(perm = x_139_perm_0, x = x_137_cast_fp16)[name = tensor("transpose_469")]; + tensor input_345_cast_fp16 = add(x = x_139_cast_fp16, y = inputs_27_cast_fp16)[name = tensor("input_345_cast_fp16")]; + tensor fsmn_memory_27_cast_fp16 = mul(x = input_345_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_27_cast_fp16")]; + tensor var_1327_to_fp16 = const()[name = tensor("op_1327_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_55_cast_fp16 = mul(x = var_1302_cast_fp16, y = var_1327_to_fp16)[name = tensor("q_h_55_cast_fp16")]; + tensor scores_53_transpose_x_0 = const()[name = tensor("scores_53_transpose_x_0"), val = tensor(false)]; + tensor scores_53_transpose_y_0 = const()[name = tensor("scores_53_transpose_y_0"), val = tensor(false)]; + tensor transpose_176_perm_0 = const()[name = tensor("transpose_176_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_177_perm_0 = const()[name = tensor("transpose_177_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_177 = transpose(perm = transpose_177_perm_0, x = var_1305_cast_fp16)[name = tensor("transpose_467")]; + tensor transpose_176 = transpose(perm = transpose_176_perm_0, x = q_h_55_cast_fp16)[name = tensor("transpose_468")]; + tensor scores_53_cast_fp16 = matmul(transpose_x = scores_53_transpose_x_0, transpose_y = scores_53_transpose_y_0, x = transpose_176, y = transpose_177)[name = tensor("scores_53_cast_fp16")]; + tensor scores_55_cast_fp16 = select(a = var_11_to_fp16, b = scores_53_cast_fp16, cond = mask_5)[name = tensor("scores_55_cast_fp16")]; + tensor var_1335_cast_fp16 = softmax(axis = var_20, x = scores_55_cast_fp16)[name = tensor("op_1335_cast_fp16")]; + tensor input_347_cast_fp16 = select(a = var_6_to_fp16, b = var_1335_cast_fp16, cond = mask_5)[name = tensor("input_347_cast_fp16")]; + tensor x_143_transpose_x_0 = const()[name = tensor("x_143_transpose_x_0"), val = tensor(false)]; + tensor x_143_transpose_y_0 = const()[name = tensor("x_143_transpose_y_0"), val = tensor(false)]; + tensor value_27_cast_fp16 = transpose(perm = value_27_perm_0, x = var_1308_cast_fp16)[name = tensor("transpose_471")]; + tensor x_143_cast_fp16 = matmul(transpose_x = x_143_transpose_x_0, transpose_y = x_143_transpose_y_0, x = input_347_cast_fp16, y = value_27_cast_fp16)[name = tensor("x_143_cast_fp16")]; + tensor var_1339_perm_0 = const()[name = tensor("op_1339_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1341 = const()[name = tensor("op_1341"), val = tensor([1, -1, 512])]; + tensor var_1339_cast_fp16 = transpose(perm = var_1339_perm_0, x = x_143_cast_fp16)[name = tensor("transpose_466")]; + tensor input_349_cast_fp16 = reshape(shape = var_1341, x = var_1339_cast_fp16)[name = tensor("input_349_cast_fp16")]; + tensor e_encoders_12_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_12_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83857216)))]; + tensor e_encoders_12_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_12_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84381568)))]; + tensor linear_53_cast_fp16 = linear(bias = e_encoders_12_self_attn_linear_out_bias_to_fp16, weight = e_encoders_12_self_attn_linear_out_weight_to_fp16, x = input_349_cast_fp16)[name = tensor("linear_53_cast_fp16")]; + tensor input_351_cast_fp16 = add(x = linear_53_cast_fp16, y = fsmn_memory_27_cast_fp16)[name = tensor("input_351_cast_fp16")]; + tensor input_353_cast_fp16 = add(x = input_339_cast_fp16, y = input_351_cast_fp16)[name = tensor("input_353_cast_fp16")]; + tensor input_355_axes_0 = const()[name = tensor("input_355_axes_0"), val = tensor([-1])]; + tensor e_encoders_12_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_12_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84382656)))]; + tensor e_encoders_12_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_12_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84383744)))]; + tensor input_355_cast_fp16 = layer_norm(axes = input_355_axes_0, beta = e_encoders_12_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_12_norm2_weight_to_fp16, x = input_353_cast_fp16)[name = tensor("input_355_cast_fp16")]; + tensor e_encoders_12_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_12_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84384832)))]; + tensor e_encoders_12_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_12_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86482048)))]; + tensor linear_54_cast_fp16 = linear(bias = e_encoders_12_feed_forward_w_1_bias_to_fp16, weight = e_encoders_12_feed_forward_w_1_weight_to_fp16, x = input_355_cast_fp16)[name = tensor("linear_54_cast_fp16")]; + tensor input_359_cast_fp16 = relu(x = linear_54_cast_fp16)[name = tensor("input_359_cast_fp16")]; + tensor e_encoders_12_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_12_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86486208)))]; + tensor e_encoders_12_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_12_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88583424)))]; + tensor linear_55_cast_fp16 = linear(bias = e_encoders_12_feed_forward_w_2_bias_to_fp16, weight = e_encoders_12_feed_forward_w_2_weight_to_fp16, x = input_359_cast_fp16)[name = tensor("linear_55_cast_fp16")]; + tensor input_365_cast_fp16 = add(x = input_353_cast_fp16, y = linear_55_cast_fp16)[name = tensor("input_365_cast_fp16")]; + tensor x_145_axes_0 = const()[name = tensor("x_145_axes_0"), val = tensor([-1])]; + tensor e_encoders_13_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_13_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88584512)))]; + tensor e_encoders_13_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_13_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88585600)))]; + tensor x_145_cast_fp16 = layer_norm(axes = x_145_axes_0, beta = e_encoders_13_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_13_norm1_weight_to_fp16, x = input_365_cast_fp16)[name = tensor("x_145_cast_fp16")]; + tensor e_encoders_13_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_13_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88586688)))]; + tensor e_encoders_13_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_13_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90159616)))]; + tensor linear_56_cast_fp16 = linear(bias = e_encoders_13_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_13_self_attn_linear_q_k_v_weight_to_fp16, x = x_145_cast_fp16)[name = tensor("linear_56_cast_fp16")]; + tensor tile_14 = const()[name = tensor("tile_14"), val = tensor([512, 512, 512])]; + tensor var_1385_axis_0 = const()[name = tensor("op_1385_axis_0"), val = tensor(-1)]; + tensor var_1385_cast_fp16_0, tensor var_1385_cast_fp16_1, tensor var_1385_cast_fp16_2 = split(axis = var_1385_axis_0, split_sizes = tile_14, x = linear_56_cast_fp16)[name = tensor("op_1385_cast_fp16")]; + tensor concat_43x = const()[name = tensor("concat_43x"), val = tensor([1, -1, 4, 128])]; + tensor var_1390_cast_fp16 = reshape(shape = concat_43x, x = var_1385_cast_fp16_0)[name = tensor("op_1390_cast_fp16")]; + tensor concat_44x = const()[name = tensor("concat_44x"), val = tensor([1, -1, 4, 128])]; + tensor var_1393_cast_fp16 = reshape(shape = concat_44x, x = var_1385_cast_fp16_1)[name = tensor("op_1393_cast_fp16")]; + tensor concat_45x = const()[name = tensor("concat_45x"), val = tensor([1, -1, 4, 128])]; + tensor var_1396_cast_fp16 = reshape(shape = concat_45x, x = var_1385_cast_fp16_2)[name = tensor("op_1396_cast_fp16")]; + tensor value_29_perm_0 = const()[name = tensor("value_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_29_cast_fp16 = mul(x = var_1385_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor input_367_perm_0 = const()[name = tensor("input_367_perm_0"), val = tensor([0, 2, 1])]; + tensor input_369_pad_0 = const()[name = tensor("input_369_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_369_mode_0 = const()[name = tensor("input_369_mode_0"), val = tensor("constant")]; + tensor const_37_to_fp16 = const()[name = tensor("const_37_to_fp16"), val = tensor(0x0p+0)]; + tensor input_367_cast_fp16 = transpose(perm = input_367_perm_0, x = inputs_29_cast_fp16)[name = tensor("transpose_464")]; + tensor input_369_cast_fp16 = pad(constant_val = const_37_to_fp16, mode = input_369_mode_0, pad = input_369_pad_0, x = input_367_cast_fp16)[name = tensor("input_369_cast_fp16")]; + tensor x_147_pad_type_0 = const()[name = tensor("x_147_pad_type_0"), val = tensor("valid")]; + tensor x_147_groups_0 = const()[name = tensor("x_147_groups_0"), val = tensor(512)]; + tensor x_147_strides_0 = const()[name = tensor("x_147_strides_0"), val = tensor([1])]; + tensor x_147_pad_0 = const()[name = tensor("x_147_pad_0"), val = tensor([0, 0])]; + tensor x_147_dilations_0 = const()[name = tensor("x_147_dilations_0"), val = tensor([1])]; + tensor e_encoders_13_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_13_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90162752)))]; + tensor x_147_cast_fp16 = conv(dilations = x_147_dilations_0, groups = x_147_groups_0, pad = x_147_pad_0, pad_type = x_147_pad_type_0, strides = x_147_strides_0, weight = e_encoders_13_self_attn_fsmn_block_weight_to_fp16, x = input_369_cast_fp16)[name = tensor("x_147_cast_fp16")]; + tensor x_149_perm_0 = const()[name = tensor("x_149_perm_0"), val = tensor([0, 2, 1])]; + tensor x_149_cast_fp16 = transpose(perm = x_149_perm_0, x = x_147_cast_fp16)[name = tensor("transpose_463")]; + tensor input_371_cast_fp16 = add(x = x_149_cast_fp16, y = inputs_29_cast_fp16)[name = tensor("input_371_cast_fp16")]; + tensor fsmn_memory_29_cast_fp16 = mul(x = input_371_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_29_cast_fp16")]; + tensor var_1415_to_fp16 = const()[name = tensor("op_1415_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_59_cast_fp16 = mul(x = var_1390_cast_fp16, y = var_1415_to_fp16)[name = tensor("q_h_59_cast_fp16")]; + tensor scores_57_transpose_x_0 = const()[name = tensor("scores_57_transpose_x_0"), val = tensor(false)]; + tensor scores_57_transpose_y_0 = const()[name = tensor("scores_57_transpose_y_0"), val = tensor(false)]; + tensor transpose_178_perm_0 = const()[name = tensor("transpose_178_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_179_perm_0 = const()[name = tensor("transpose_179_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_179 = transpose(perm = transpose_179_perm_0, x = var_1393_cast_fp16)[name = tensor("transpose_461")]; + tensor transpose_178 = transpose(perm = transpose_178_perm_0, x = q_h_59_cast_fp16)[name = tensor("transpose_462")]; + tensor scores_57_cast_fp16 = matmul(transpose_x = scores_57_transpose_x_0, transpose_y = scores_57_transpose_y_0, x = transpose_178, y = transpose_179)[name = tensor("scores_57_cast_fp16")]; + tensor scores_59_cast_fp16 = select(a = var_11_to_fp16, b = scores_57_cast_fp16, cond = mask_5)[name = tensor("scores_59_cast_fp16")]; + tensor var_1423_cast_fp16 = softmax(axis = var_20, x = scores_59_cast_fp16)[name = tensor("op_1423_cast_fp16")]; + tensor input_373_cast_fp16 = select(a = var_6_to_fp16, b = var_1423_cast_fp16, cond = mask_5)[name = tensor("input_373_cast_fp16")]; + tensor x_153_transpose_x_0 = const()[name = tensor("x_153_transpose_x_0"), val = tensor(false)]; + tensor x_153_transpose_y_0 = const()[name = tensor("x_153_transpose_y_0"), val = tensor(false)]; + tensor value_29_cast_fp16 = transpose(perm = value_29_perm_0, x = var_1396_cast_fp16)[name = tensor("transpose_465")]; + tensor x_153_cast_fp16 = matmul(transpose_x = x_153_transpose_x_0, transpose_y = x_153_transpose_y_0, x = input_373_cast_fp16, y = value_29_cast_fp16)[name = tensor("x_153_cast_fp16")]; + tensor var_1427_perm_0 = const()[name = tensor("op_1427_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1429 = const()[name = tensor("op_1429"), val = tensor([1, -1, 512])]; + tensor var_1427_cast_fp16 = transpose(perm = var_1427_perm_0, x = x_153_cast_fp16)[name = tensor("transpose_460")]; + tensor input_375_cast_fp16 = reshape(shape = var_1429, x = var_1427_cast_fp16)[name = tensor("input_375_cast_fp16")]; + tensor e_encoders_13_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_13_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90174080)))]; + tensor e_encoders_13_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_13_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90698432)))]; + tensor linear_57_cast_fp16 = linear(bias = e_encoders_13_self_attn_linear_out_bias_to_fp16, weight = e_encoders_13_self_attn_linear_out_weight_to_fp16, x = input_375_cast_fp16)[name = tensor("linear_57_cast_fp16")]; + tensor input_377_cast_fp16 = add(x = linear_57_cast_fp16, y = fsmn_memory_29_cast_fp16)[name = tensor("input_377_cast_fp16")]; + tensor input_379_cast_fp16 = add(x = input_365_cast_fp16, y = input_377_cast_fp16)[name = tensor("input_379_cast_fp16")]; + tensor input_381_axes_0 = const()[name = tensor("input_381_axes_0"), val = tensor([-1])]; + tensor e_encoders_13_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_13_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90699520)))]; + tensor e_encoders_13_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_13_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90700608)))]; + tensor input_381_cast_fp16 = layer_norm(axes = input_381_axes_0, beta = e_encoders_13_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_13_norm2_weight_to_fp16, x = input_379_cast_fp16)[name = tensor("input_381_cast_fp16")]; + tensor e_encoders_13_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_13_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90701696)))]; + tensor e_encoders_13_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_13_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92798912)))]; + tensor linear_58_cast_fp16 = linear(bias = e_encoders_13_feed_forward_w_1_bias_to_fp16, weight = e_encoders_13_feed_forward_w_1_weight_to_fp16, x = input_381_cast_fp16)[name = tensor("linear_58_cast_fp16")]; + tensor input_385_cast_fp16 = relu(x = linear_58_cast_fp16)[name = tensor("input_385_cast_fp16")]; + tensor e_encoders_13_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_13_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92803072)))]; + tensor e_encoders_13_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_13_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94900288)))]; + tensor linear_59_cast_fp16 = linear(bias = e_encoders_13_feed_forward_w_2_bias_to_fp16, weight = e_encoders_13_feed_forward_w_2_weight_to_fp16, x = input_385_cast_fp16)[name = tensor("linear_59_cast_fp16")]; + tensor input_391_cast_fp16 = add(x = input_379_cast_fp16, y = linear_59_cast_fp16)[name = tensor("input_391_cast_fp16")]; + tensor x_155_axes_0 = const()[name = tensor("x_155_axes_0"), val = tensor([-1])]; + tensor e_encoders_14_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_14_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94901376)))]; + tensor e_encoders_14_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_14_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94902464)))]; + tensor x_155_cast_fp16 = layer_norm(axes = x_155_axes_0, beta = e_encoders_14_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_14_norm1_weight_to_fp16, x = input_391_cast_fp16)[name = tensor("x_155_cast_fp16")]; + tensor e_encoders_14_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_14_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94903552)))]; + tensor e_encoders_14_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_14_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96476480)))]; + tensor linear_60_cast_fp16 = linear(bias = e_encoders_14_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_14_self_attn_linear_q_k_v_weight_to_fp16, x = x_155_cast_fp16)[name = tensor("linear_60_cast_fp16")]; + tensor tile_15 = const()[name = tensor("tile_15"), val = tensor([512, 512, 512])]; + tensor var_1473_axis_0 = const()[name = tensor("op_1473_axis_0"), val = tensor(-1)]; + tensor var_1473_cast_fp16_0, tensor var_1473_cast_fp16_1, tensor var_1473_cast_fp16_2 = split(axis = var_1473_axis_0, split_sizes = tile_15, x = linear_60_cast_fp16)[name = tensor("op_1473_cast_fp16")]; + tensor concat_46x = const()[name = tensor("concat_46x"), val = tensor([1, -1, 4, 128])]; + tensor var_1478_cast_fp16 = reshape(shape = concat_46x, x = var_1473_cast_fp16_0)[name = tensor("op_1478_cast_fp16")]; + tensor concat_47x = const()[name = tensor("concat_47x"), val = tensor([1, -1, 4, 128])]; + tensor var_1481_cast_fp16 = reshape(shape = concat_47x, x = var_1473_cast_fp16_1)[name = tensor("op_1481_cast_fp16")]; + tensor concat_48x = const()[name = tensor("concat_48x"), val = tensor([1, -1, 4, 128])]; + tensor var_1484_cast_fp16 = reshape(shape = concat_48x, x = var_1473_cast_fp16_2)[name = tensor("op_1484_cast_fp16")]; + tensor value_31_perm_0 = const()[name = tensor("value_31_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_31_cast_fp16 = mul(x = var_1473_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor input_393_perm_0 = const()[name = tensor("input_393_perm_0"), val = tensor([0, 2, 1])]; + tensor input_395_pad_0 = const()[name = tensor("input_395_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_395_mode_0 = const()[name = tensor("input_395_mode_0"), val = tensor("constant")]; + tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(0x0p+0)]; + tensor input_393_cast_fp16 = transpose(perm = input_393_perm_0, x = inputs_31_cast_fp16)[name = tensor("transpose_458")]; + tensor input_395_cast_fp16 = pad(constant_val = const_39_to_fp16, mode = input_395_mode_0, pad = input_395_pad_0, x = input_393_cast_fp16)[name = tensor("input_395_cast_fp16")]; + tensor x_157_pad_type_0 = const()[name = tensor("x_157_pad_type_0"), val = tensor("valid")]; + tensor x_157_groups_0 = const()[name = tensor("x_157_groups_0"), val = tensor(512)]; + tensor x_157_strides_0 = const()[name = tensor("x_157_strides_0"), val = tensor([1])]; + tensor x_157_pad_0 = const()[name = tensor("x_157_pad_0"), val = tensor([0, 0])]; + tensor x_157_dilations_0 = const()[name = tensor("x_157_dilations_0"), val = tensor([1])]; + tensor e_encoders_14_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_14_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96479616)))]; + tensor x_157_cast_fp16 = conv(dilations = x_157_dilations_0, groups = x_157_groups_0, pad = x_157_pad_0, pad_type = x_157_pad_type_0, strides = x_157_strides_0, weight = e_encoders_14_self_attn_fsmn_block_weight_to_fp16, x = input_395_cast_fp16)[name = tensor("x_157_cast_fp16")]; + tensor x_159_perm_0 = const()[name = tensor("x_159_perm_0"), val = tensor([0, 2, 1])]; + tensor x_159_cast_fp16 = transpose(perm = x_159_perm_0, x = x_157_cast_fp16)[name = tensor("transpose_457")]; + tensor input_397_cast_fp16 = add(x = x_159_cast_fp16, y = inputs_31_cast_fp16)[name = tensor("input_397_cast_fp16")]; + tensor fsmn_memory_31_cast_fp16 = mul(x = input_397_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_31_cast_fp16")]; + tensor var_1503_to_fp16 = const()[name = tensor("op_1503_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_63_cast_fp16 = mul(x = var_1478_cast_fp16, y = var_1503_to_fp16)[name = tensor("q_h_63_cast_fp16")]; + tensor scores_61_transpose_x_0 = const()[name = tensor("scores_61_transpose_x_0"), val = tensor(false)]; + tensor scores_61_transpose_y_0 = const()[name = tensor("scores_61_transpose_y_0"), val = tensor(false)]; + tensor transpose_180_perm_0 = const()[name = tensor("transpose_180_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_181_perm_0 = const()[name = tensor("transpose_181_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_181 = transpose(perm = transpose_181_perm_0, x = var_1481_cast_fp16)[name = tensor("transpose_455")]; + tensor transpose_180 = transpose(perm = transpose_180_perm_0, x = q_h_63_cast_fp16)[name = tensor("transpose_456")]; + tensor scores_61_cast_fp16 = matmul(transpose_x = scores_61_transpose_x_0, transpose_y = scores_61_transpose_y_0, x = transpose_180, y = transpose_181)[name = tensor("scores_61_cast_fp16")]; + tensor scores_63_cast_fp16 = select(a = var_11_to_fp16, b = scores_61_cast_fp16, cond = mask_5)[name = tensor("scores_63_cast_fp16")]; + tensor var_1511_cast_fp16 = softmax(axis = var_20, x = scores_63_cast_fp16)[name = tensor("op_1511_cast_fp16")]; + tensor input_399_cast_fp16 = select(a = var_6_to_fp16, b = var_1511_cast_fp16, cond = mask_5)[name = tensor("input_399_cast_fp16")]; + tensor x_163_transpose_x_0 = const()[name = tensor("x_163_transpose_x_0"), val = tensor(false)]; + tensor x_163_transpose_y_0 = const()[name = tensor("x_163_transpose_y_0"), val = tensor(false)]; + tensor value_31_cast_fp16 = transpose(perm = value_31_perm_0, x = var_1484_cast_fp16)[name = tensor("transpose_459")]; + tensor x_163_cast_fp16 = matmul(transpose_x = x_163_transpose_x_0, transpose_y = x_163_transpose_y_0, x = input_399_cast_fp16, y = value_31_cast_fp16)[name = tensor("x_163_cast_fp16")]; + tensor var_1515_perm_0 = const()[name = tensor("op_1515_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1517 = const()[name = tensor("op_1517"), val = tensor([1, -1, 512])]; + tensor var_1515_cast_fp16 = transpose(perm = var_1515_perm_0, x = x_163_cast_fp16)[name = tensor("transpose_454")]; + tensor input_401_cast_fp16 = reshape(shape = var_1517, x = var_1515_cast_fp16)[name = tensor("input_401_cast_fp16")]; + tensor e_encoders_14_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_14_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96490944)))]; + tensor e_encoders_14_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_14_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97015296)))]; + tensor linear_61_cast_fp16 = linear(bias = e_encoders_14_self_attn_linear_out_bias_to_fp16, weight = e_encoders_14_self_attn_linear_out_weight_to_fp16, x = input_401_cast_fp16)[name = tensor("linear_61_cast_fp16")]; + tensor input_403_cast_fp16 = add(x = linear_61_cast_fp16, y = fsmn_memory_31_cast_fp16)[name = tensor("input_403_cast_fp16")]; + tensor input_405_cast_fp16 = add(x = input_391_cast_fp16, y = input_403_cast_fp16)[name = tensor("input_405_cast_fp16")]; + tensor input_407_axes_0 = const()[name = tensor("input_407_axes_0"), val = tensor([-1])]; + tensor e_encoders_14_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_14_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97016384)))]; + tensor e_encoders_14_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_14_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97017472)))]; + tensor input_407_cast_fp16 = layer_norm(axes = input_407_axes_0, beta = e_encoders_14_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_14_norm2_weight_to_fp16, x = input_405_cast_fp16)[name = tensor("input_407_cast_fp16")]; + tensor e_encoders_14_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_14_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97018560)))]; + tensor e_encoders_14_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_14_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99115776)))]; + tensor linear_62_cast_fp16 = linear(bias = e_encoders_14_feed_forward_w_1_bias_to_fp16, weight = e_encoders_14_feed_forward_w_1_weight_to_fp16, x = input_407_cast_fp16)[name = tensor("linear_62_cast_fp16")]; + tensor input_411_cast_fp16 = relu(x = linear_62_cast_fp16)[name = tensor("input_411_cast_fp16")]; + tensor e_encoders_14_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_14_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99119936)))]; + tensor e_encoders_14_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_14_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101217152)))]; + tensor linear_63_cast_fp16 = linear(bias = e_encoders_14_feed_forward_w_2_bias_to_fp16, weight = e_encoders_14_feed_forward_w_2_weight_to_fp16, x = input_411_cast_fp16)[name = tensor("linear_63_cast_fp16")]; + tensor input_417_cast_fp16 = add(x = input_405_cast_fp16, y = linear_63_cast_fp16)[name = tensor("input_417_cast_fp16")]; + tensor x_165_axes_0 = const()[name = tensor("x_165_axes_0"), val = tensor([-1])]; + tensor e_encoders_15_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_15_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101218240)))]; + tensor e_encoders_15_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_15_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101219328)))]; + tensor x_165_cast_fp16 = layer_norm(axes = x_165_axes_0, beta = e_encoders_15_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_15_norm1_weight_to_fp16, x = input_417_cast_fp16)[name = tensor("x_165_cast_fp16")]; + tensor e_encoders_15_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_15_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101220416)))]; + tensor e_encoders_15_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_15_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102793344)))]; + tensor linear_64_cast_fp16 = linear(bias = e_encoders_15_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_15_self_attn_linear_q_k_v_weight_to_fp16, x = x_165_cast_fp16)[name = tensor("linear_64_cast_fp16")]; + tensor tile_16 = const()[name = tensor("tile_16"), val = tensor([512, 512, 512])]; + tensor var_1561_axis_0 = const()[name = tensor("op_1561_axis_0"), val = tensor(-1)]; + tensor var_1561_cast_fp16_0, tensor var_1561_cast_fp16_1, tensor var_1561_cast_fp16_2 = split(axis = var_1561_axis_0, split_sizes = tile_16, x = linear_64_cast_fp16)[name = tensor("op_1561_cast_fp16")]; + tensor concat_49x = const()[name = tensor("concat_49x"), val = tensor([1, -1, 4, 128])]; + tensor var_1566_cast_fp16 = reshape(shape = concat_49x, x = var_1561_cast_fp16_0)[name = tensor("op_1566_cast_fp16")]; + tensor concat_50x = const()[name = tensor("concat_50x"), val = tensor([1, -1, 4, 128])]; + tensor var_1569_cast_fp16 = reshape(shape = concat_50x, x = var_1561_cast_fp16_1)[name = tensor("op_1569_cast_fp16")]; + tensor concat_51x = const()[name = tensor("concat_51x"), val = tensor([1, -1, 4, 128])]; + tensor var_1572_cast_fp16 = reshape(shape = concat_51x, x = var_1561_cast_fp16_2)[name = tensor("op_1572_cast_fp16")]; + tensor value_33_perm_0 = const()[name = tensor("value_33_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_33_cast_fp16 = mul(x = var_1561_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor input_419_perm_0 = const()[name = tensor("input_419_perm_0"), val = tensor([0, 2, 1])]; + tensor input_421_pad_0 = const()[name = tensor("input_421_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_421_mode_0 = const()[name = tensor("input_421_mode_0"), val = tensor("constant")]; + tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(0x0p+0)]; + tensor input_419_cast_fp16 = transpose(perm = input_419_perm_0, x = inputs_33_cast_fp16)[name = tensor("transpose_452")]; + tensor input_421_cast_fp16 = pad(constant_val = const_41_to_fp16, mode = input_421_mode_0, pad = input_421_pad_0, x = input_419_cast_fp16)[name = tensor("input_421_cast_fp16")]; + tensor x_167_pad_type_0 = const()[name = tensor("x_167_pad_type_0"), val = tensor("valid")]; + tensor x_167_groups_0 = const()[name = tensor("x_167_groups_0"), val = tensor(512)]; + tensor x_167_strides_0 = const()[name = tensor("x_167_strides_0"), val = tensor([1])]; + tensor x_167_pad_0 = const()[name = tensor("x_167_pad_0"), val = tensor([0, 0])]; + tensor x_167_dilations_0 = const()[name = tensor("x_167_dilations_0"), val = tensor([1])]; + tensor e_encoders_15_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_15_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102796480)))]; + tensor x_167_cast_fp16 = conv(dilations = x_167_dilations_0, groups = x_167_groups_0, pad = x_167_pad_0, pad_type = x_167_pad_type_0, strides = x_167_strides_0, weight = e_encoders_15_self_attn_fsmn_block_weight_to_fp16, x = input_421_cast_fp16)[name = tensor("x_167_cast_fp16")]; + tensor x_169_perm_0 = const()[name = tensor("x_169_perm_0"), val = tensor([0, 2, 1])]; + tensor x_169_cast_fp16 = transpose(perm = x_169_perm_0, x = x_167_cast_fp16)[name = tensor("transpose_451")]; + tensor input_423_cast_fp16 = add(x = x_169_cast_fp16, y = inputs_33_cast_fp16)[name = tensor("input_423_cast_fp16")]; + tensor fsmn_memory_33_cast_fp16 = mul(x = input_423_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_33_cast_fp16")]; + tensor var_1591_to_fp16 = const()[name = tensor("op_1591_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_67_cast_fp16 = mul(x = var_1566_cast_fp16, y = var_1591_to_fp16)[name = tensor("q_h_67_cast_fp16")]; + tensor scores_65_transpose_x_0 = const()[name = tensor("scores_65_transpose_x_0"), val = tensor(false)]; + tensor scores_65_transpose_y_0 = const()[name = tensor("scores_65_transpose_y_0"), val = tensor(false)]; + tensor transpose_182_perm_0 = const()[name = tensor("transpose_182_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_183_perm_0 = const()[name = tensor("transpose_183_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_183 = transpose(perm = transpose_183_perm_0, x = var_1569_cast_fp16)[name = tensor("transpose_449")]; + tensor transpose_182 = transpose(perm = transpose_182_perm_0, x = q_h_67_cast_fp16)[name = tensor("transpose_450")]; + tensor scores_65_cast_fp16 = matmul(transpose_x = scores_65_transpose_x_0, transpose_y = scores_65_transpose_y_0, x = transpose_182, y = transpose_183)[name = tensor("scores_65_cast_fp16")]; + tensor scores_67_cast_fp16 = select(a = var_11_to_fp16, b = scores_65_cast_fp16, cond = mask_5)[name = tensor("scores_67_cast_fp16")]; + tensor var_1599_cast_fp16 = softmax(axis = var_20, x = scores_67_cast_fp16)[name = tensor("op_1599_cast_fp16")]; + tensor input_425_cast_fp16 = select(a = var_6_to_fp16, b = var_1599_cast_fp16, cond = mask_5)[name = tensor("input_425_cast_fp16")]; + tensor x_173_transpose_x_0 = const()[name = tensor("x_173_transpose_x_0"), val = tensor(false)]; + tensor x_173_transpose_y_0 = const()[name = tensor("x_173_transpose_y_0"), val = tensor(false)]; + tensor value_33_cast_fp16 = transpose(perm = value_33_perm_0, x = var_1572_cast_fp16)[name = tensor("transpose_453")]; + tensor x_173_cast_fp16 = matmul(transpose_x = x_173_transpose_x_0, transpose_y = x_173_transpose_y_0, x = input_425_cast_fp16, y = value_33_cast_fp16)[name = tensor("x_173_cast_fp16")]; + tensor var_1603_perm_0 = const()[name = tensor("op_1603_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1605 = const()[name = tensor("op_1605"), val = tensor([1, -1, 512])]; + tensor var_1603_cast_fp16 = transpose(perm = var_1603_perm_0, x = x_173_cast_fp16)[name = tensor("transpose_448")]; + tensor input_427_cast_fp16 = reshape(shape = var_1605, x = var_1603_cast_fp16)[name = tensor("input_427_cast_fp16")]; + tensor e_encoders_15_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_15_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102807808)))]; + tensor e_encoders_15_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_15_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103332160)))]; + tensor linear_65_cast_fp16 = linear(bias = e_encoders_15_self_attn_linear_out_bias_to_fp16, weight = e_encoders_15_self_attn_linear_out_weight_to_fp16, x = input_427_cast_fp16)[name = tensor("linear_65_cast_fp16")]; + tensor input_429_cast_fp16 = add(x = linear_65_cast_fp16, y = fsmn_memory_33_cast_fp16)[name = tensor("input_429_cast_fp16")]; + tensor input_431_cast_fp16 = add(x = input_417_cast_fp16, y = input_429_cast_fp16)[name = tensor("input_431_cast_fp16")]; + tensor input_433_axes_0 = const()[name = tensor("input_433_axes_0"), val = tensor([-1])]; + tensor e_encoders_15_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_15_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103333248)))]; + tensor e_encoders_15_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_15_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103334336)))]; + tensor input_433_cast_fp16 = layer_norm(axes = input_433_axes_0, beta = e_encoders_15_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_15_norm2_weight_to_fp16, x = input_431_cast_fp16)[name = tensor("input_433_cast_fp16")]; + tensor e_encoders_15_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_15_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103335424)))]; + tensor e_encoders_15_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_15_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105432640)))]; + tensor linear_66_cast_fp16 = linear(bias = e_encoders_15_feed_forward_w_1_bias_to_fp16, weight = e_encoders_15_feed_forward_w_1_weight_to_fp16, x = input_433_cast_fp16)[name = tensor("linear_66_cast_fp16")]; + tensor input_437_cast_fp16 = relu(x = linear_66_cast_fp16)[name = tensor("input_437_cast_fp16")]; + tensor e_encoders_15_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_15_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105436800)))]; + tensor e_encoders_15_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_15_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107534016)))]; + tensor linear_67_cast_fp16 = linear(bias = e_encoders_15_feed_forward_w_2_bias_to_fp16, weight = e_encoders_15_feed_forward_w_2_weight_to_fp16, x = input_437_cast_fp16)[name = tensor("linear_67_cast_fp16")]; + tensor input_443_cast_fp16 = add(x = input_431_cast_fp16, y = linear_67_cast_fp16)[name = tensor("input_443_cast_fp16")]; + tensor x_175_axes_0 = const()[name = tensor("x_175_axes_0"), val = tensor([-1])]; + tensor e_encoders_16_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_16_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107535104)))]; + tensor e_encoders_16_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_16_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107536192)))]; + tensor x_175_cast_fp16 = layer_norm(axes = x_175_axes_0, beta = e_encoders_16_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_16_norm1_weight_to_fp16, x = input_443_cast_fp16)[name = tensor("x_175_cast_fp16")]; + tensor e_encoders_16_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_16_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107537280)))]; + tensor e_encoders_16_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_16_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109110208)))]; + tensor linear_68_cast_fp16 = linear(bias = e_encoders_16_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_16_self_attn_linear_q_k_v_weight_to_fp16, x = x_175_cast_fp16)[name = tensor("linear_68_cast_fp16")]; + tensor tile_17 = const()[name = tensor("tile_17"), val = tensor([512, 512, 512])]; + tensor var_1649_axis_0 = const()[name = tensor("op_1649_axis_0"), val = tensor(-1)]; + tensor var_1649_cast_fp16_0, tensor var_1649_cast_fp16_1, tensor var_1649_cast_fp16_2 = split(axis = var_1649_axis_0, split_sizes = tile_17, x = linear_68_cast_fp16)[name = tensor("op_1649_cast_fp16")]; + tensor concat_52x = const()[name = tensor("concat_52x"), val = tensor([1, -1, 4, 128])]; + tensor var_1654_cast_fp16 = reshape(shape = concat_52x, x = var_1649_cast_fp16_0)[name = tensor("op_1654_cast_fp16")]; + tensor concat_53x = const()[name = tensor("concat_53x"), val = tensor([1, -1, 4, 128])]; + tensor var_1657_cast_fp16 = reshape(shape = concat_53x, x = var_1649_cast_fp16_1)[name = tensor("op_1657_cast_fp16")]; + tensor concat_54x = const()[name = tensor("concat_54x"), val = tensor([1, -1, 4, 128])]; + tensor var_1660_cast_fp16 = reshape(shape = concat_54x, x = var_1649_cast_fp16_2)[name = tensor("op_1660_cast_fp16")]; + tensor value_35_perm_0 = const()[name = tensor("value_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_35_cast_fp16 = mul(x = var_1649_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor input_445_perm_0 = const()[name = tensor("input_445_perm_0"), val = tensor([0, 2, 1])]; + tensor input_447_pad_0 = const()[name = tensor("input_447_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_447_mode_0 = const()[name = tensor("input_447_mode_0"), val = tensor("constant")]; + tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(0x0p+0)]; + tensor input_445_cast_fp16 = transpose(perm = input_445_perm_0, x = inputs_35_cast_fp16)[name = tensor("transpose_446")]; + tensor input_447_cast_fp16 = pad(constant_val = const_43_to_fp16, mode = input_447_mode_0, pad = input_447_pad_0, x = input_445_cast_fp16)[name = tensor("input_447_cast_fp16")]; + tensor x_177_pad_type_0 = const()[name = tensor("x_177_pad_type_0"), val = tensor("valid")]; + tensor x_177_groups_0 = const()[name = tensor("x_177_groups_0"), val = tensor(512)]; + tensor x_177_strides_0 = const()[name = tensor("x_177_strides_0"), val = tensor([1])]; + tensor x_177_pad_0 = const()[name = tensor("x_177_pad_0"), val = tensor([0, 0])]; + tensor x_177_dilations_0 = const()[name = tensor("x_177_dilations_0"), val = tensor([1])]; + tensor e_encoders_16_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_16_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109113344)))]; + tensor x_177_cast_fp16 = conv(dilations = x_177_dilations_0, groups = x_177_groups_0, pad = x_177_pad_0, pad_type = x_177_pad_type_0, strides = x_177_strides_0, weight = e_encoders_16_self_attn_fsmn_block_weight_to_fp16, x = input_447_cast_fp16)[name = tensor("x_177_cast_fp16")]; + tensor x_179_perm_0 = const()[name = tensor("x_179_perm_0"), val = tensor([0, 2, 1])]; + tensor x_179_cast_fp16 = transpose(perm = x_179_perm_0, x = x_177_cast_fp16)[name = tensor("transpose_445")]; + tensor input_449_cast_fp16 = add(x = x_179_cast_fp16, y = inputs_35_cast_fp16)[name = tensor("input_449_cast_fp16")]; + tensor fsmn_memory_35_cast_fp16 = mul(x = input_449_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_35_cast_fp16")]; + tensor var_1679_to_fp16 = const()[name = tensor("op_1679_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_71_cast_fp16 = mul(x = var_1654_cast_fp16, y = var_1679_to_fp16)[name = tensor("q_h_71_cast_fp16")]; + tensor scores_69_transpose_x_0 = const()[name = tensor("scores_69_transpose_x_0"), val = tensor(false)]; + tensor scores_69_transpose_y_0 = const()[name = tensor("scores_69_transpose_y_0"), val = tensor(false)]; + tensor transpose_184_perm_0 = const()[name = tensor("transpose_184_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_185_perm_0 = const()[name = tensor("transpose_185_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_185 = transpose(perm = transpose_185_perm_0, x = var_1657_cast_fp16)[name = tensor("transpose_443")]; + tensor transpose_184 = transpose(perm = transpose_184_perm_0, x = q_h_71_cast_fp16)[name = tensor("transpose_444")]; + tensor scores_69_cast_fp16 = matmul(transpose_x = scores_69_transpose_x_0, transpose_y = scores_69_transpose_y_0, x = transpose_184, y = transpose_185)[name = tensor("scores_69_cast_fp16")]; + tensor scores_71_cast_fp16 = select(a = var_11_to_fp16, b = scores_69_cast_fp16, cond = mask_5)[name = tensor("scores_71_cast_fp16")]; + tensor var_1687_cast_fp16 = softmax(axis = var_20, x = scores_71_cast_fp16)[name = tensor("op_1687_cast_fp16")]; + tensor input_451_cast_fp16 = select(a = var_6_to_fp16, b = var_1687_cast_fp16, cond = mask_5)[name = tensor("input_451_cast_fp16")]; + tensor x_183_transpose_x_0 = const()[name = tensor("x_183_transpose_x_0"), val = tensor(false)]; + tensor x_183_transpose_y_0 = const()[name = tensor("x_183_transpose_y_0"), val = tensor(false)]; + tensor value_35_cast_fp16 = transpose(perm = value_35_perm_0, x = var_1660_cast_fp16)[name = tensor("transpose_447")]; + tensor x_183_cast_fp16 = matmul(transpose_x = x_183_transpose_x_0, transpose_y = x_183_transpose_y_0, x = input_451_cast_fp16, y = value_35_cast_fp16)[name = tensor("x_183_cast_fp16")]; + tensor var_1691_perm_0 = const()[name = tensor("op_1691_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1693 = const()[name = tensor("op_1693"), val = tensor([1, -1, 512])]; + tensor var_1691_cast_fp16 = transpose(perm = var_1691_perm_0, x = x_183_cast_fp16)[name = tensor("transpose_442")]; + tensor input_453_cast_fp16 = reshape(shape = var_1693, x = var_1691_cast_fp16)[name = tensor("input_453_cast_fp16")]; + tensor e_encoders_16_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_16_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109124672)))]; + tensor e_encoders_16_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_16_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109649024)))]; + tensor linear_69_cast_fp16 = linear(bias = e_encoders_16_self_attn_linear_out_bias_to_fp16, weight = e_encoders_16_self_attn_linear_out_weight_to_fp16, x = input_453_cast_fp16)[name = tensor("linear_69_cast_fp16")]; + tensor input_455_cast_fp16 = add(x = linear_69_cast_fp16, y = fsmn_memory_35_cast_fp16)[name = tensor("input_455_cast_fp16")]; + tensor input_457_cast_fp16 = add(x = input_443_cast_fp16, y = input_455_cast_fp16)[name = tensor("input_457_cast_fp16")]; + tensor input_459_axes_0 = const()[name = tensor("input_459_axes_0"), val = tensor([-1])]; + tensor e_encoders_16_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_16_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109650112)))]; + tensor e_encoders_16_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_16_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109651200)))]; + tensor input_459_cast_fp16 = layer_norm(axes = input_459_axes_0, beta = e_encoders_16_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_16_norm2_weight_to_fp16, x = input_457_cast_fp16)[name = tensor("input_459_cast_fp16")]; + tensor e_encoders_16_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_16_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109652288)))]; + tensor e_encoders_16_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_16_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111749504)))]; + tensor linear_70_cast_fp16 = linear(bias = e_encoders_16_feed_forward_w_1_bias_to_fp16, weight = e_encoders_16_feed_forward_w_1_weight_to_fp16, x = input_459_cast_fp16)[name = tensor("linear_70_cast_fp16")]; + tensor input_463_cast_fp16 = relu(x = linear_70_cast_fp16)[name = tensor("input_463_cast_fp16")]; + tensor e_encoders_16_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_16_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111753664)))]; + tensor e_encoders_16_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_16_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113850880)))]; + tensor linear_71_cast_fp16 = linear(bias = e_encoders_16_feed_forward_w_2_bias_to_fp16, weight = e_encoders_16_feed_forward_w_2_weight_to_fp16, x = input_463_cast_fp16)[name = tensor("linear_71_cast_fp16")]; + tensor input_469_cast_fp16 = add(x = input_457_cast_fp16, y = linear_71_cast_fp16)[name = tensor("input_469_cast_fp16")]; + tensor x_185_axes_0 = const()[name = tensor("x_185_axes_0"), val = tensor([-1])]; + tensor e_encoders_17_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_17_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113851968)))]; + tensor e_encoders_17_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_17_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113853056)))]; + tensor x_185_cast_fp16 = layer_norm(axes = x_185_axes_0, beta = e_encoders_17_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_17_norm1_weight_to_fp16, x = input_469_cast_fp16)[name = tensor("x_185_cast_fp16")]; + tensor e_encoders_17_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_17_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113854144)))]; + tensor e_encoders_17_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_17_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115427072)))]; + tensor linear_72_cast_fp16 = linear(bias = e_encoders_17_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_17_self_attn_linear_q_k_v_weight_to_fp16, x = x_185_cast_fp16)[name = tensor("linear_72_cast_fp16")]; + tensor tile_18 = const()[name = tensor("tile_18"), val = tensor([512, 512, 512])]; + tensor var_1737_axis_0 = const()[name = tensor("op_1737_axis_0"), val = tensor(-1)]; + tensor var_1737_cast_fp16_0, tensor var_1737_cast_fp16_1, tensor var_1737_cast_fp16_2 = split(axis = var_1737_axis_0, split_sizes = tile_18, x = linear_72_cast_fp16)[name = tensor("op_1737_cast_fp16")]; + tensor concat_55x = const()[name = tensor("concat_55x"), val = tensor([1, -1, 4, 128])]; + tensor var_1742_cast_fp16 = reshape(shape = concat_55x, x = var_1737_cast_fp16_0)[name = tensor("op_1742_cast_fp16")]; + tensor concat_56x = const()[name = tensor("concat_56x"), val = tensor([1, -1, 4, 128])]; + tensor var_1745_cast_fp16 = reshape(shape = concat_56x, x = var_1737_cast_fp16_1)[name = tensor("op_1745_cast_fp16")]; + tensor concat_57x = const()[name = tensor("concat_57x"), val = tensor([1, -1, 4, 128])]; + tensor var_1748_cast_fp16 = reshape(shape = concat_57x, x = var_1737_cast_fp16_2)[name = tensor("op_1748_cast_fp16")]; + tensor value_37_perm_0 = const()[name = tensor("value_37_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_37_cast_fp16 = mul(x = var_1737_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor input_471_perm_0 = const()[name = tensor("input_471_perm_0"), val = tensor([0, 2, 1])]; + tensor input_473_pad_0 = const()[name = tensor("input_473_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_473_mode_0 = const()[name = tensor("input_473_mode_0"), val = tensor("constant")]; + tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(0x0p+0)]; + tensor input_471_cast_fp16 = transpose(perm = input_471_perm_0, x = inputs_37_cast_fp16)[name = tensor("transpose_440")]; + tensor input_473_cast_fp16 = pad(constant_val = const_45_to_fp16, mode = input_473_mode_0, pad = input_473_pad_0, x = input_471_cast_fp16)[name = tensor("input_473_cast_fp16")]; + tensor x_187_pad_type_0 = const()[name = tensor("x_187_pad_type_0"), val = tensor("valid")]; + tensor x_187_groups_0 = const()[name = tensor("x_187_groups_0"), val = tensor(512)]; + tensor x_187_strides_0 = const()[name = tensor("x_187_strides_0"), val = tensor([1])]; + tensor x_187_pad_0 = const()[name = tensor("x_187_pad_0"), val = tensor([0, 0])]; + tensor x_187_dilations_0 = const()[name = tensor("x_187_dilations_0"), val = tensor([1])]; + tensor e_encoders_17_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_17_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115430208)))]; + tensor x_187_cast_fp16 = conv(dilations = x_187_dilations_0, groups = x_187_groups_0, pad = x_187_pad_0, pad_type = x_187_pad_type_0, strides = x_187_strides_0, weight = e_encoders_17_self_attn_fsmn_block_weight_to_fp16, x = input_473_cast_fp16)[name = tensor("x_187_cast_fp16")]; + tensor x_189_perm_0 = const()[name = tensor("x_189_perm_0"), val = tensor([0, 2, 1])]; + tensor x_189_cast_fp16 = transpose(perm = x_189_perm_0, x = x_187_cast_fp16)[name = tensor("transpose_439")]; + tensor input_475_cast_fp16 = add(x = x_189_cast_fp16, y = inputs_37_cast_fp16)[name = tensor("input_475_cast_fp16")]; + tensor fsmn_memory_37_cast_fp16 = mul(x = input_475_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_37_cast_fp16")]; + tensor var_1767_to_fp16 = const()[name = tensor("op_1767_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_75_cast_fp16 = mul(x = var_1742_cast_fp16, y = var_1767_to_fp16)[name = tensor("q_h_75_cast_fp16")]; + tensor scores_73_transpose_x_0 = const()[name = tensor("scores_73_transpose_x_0"), val = tensor(false)]; + tensor scores_73_transpose_y_0 = const()[name = tensor("scores_73_transpose_y_0"), val = tensor(false)]; + tensor transpose_186_perm_0 = const()[name = tensor("transpose_186_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_187_perm_0 = const()[name = tensor("transpose_187_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_187 = transpose(perm = transpose_187_perm_0, x = var_1745_cast_fp16)[name = tensor("transpose_437")]; + tensor transpose_186 = transpose(perm = transpose_186_perm_0, x = q_h_75_cast_fp16)[name = tensor("transpose_438")]; + tensor scores_73_cast_fp16 = matmul(transpose_x = scores_73_transpose_x_0, transpose_y = scores_73_transpose_y_0, x = transpose_186, y = transpose_187)[name = tensor("scores_73_cast_fp16")]; + tensor scores_75_cast_fp16 = select(a = var_11_to_fp16, b = scores_73_cast_fp16, cond = mask_5)[name = tensor("scores_75_cast_fp16")]; + tensor var_1775_cast_fp16 = softmax(axis = var_20, x = scores_75_cast_fp16)[name = tensor("op_1775_cast_fp16")]; + tensor input_477_cast_fp16 = select(a = var_6_to_fp16, b = var_1775_cast_fp16, cond = mask_5)[name = tensor("input_477_cast_fp16")]; + tensor x_193_transpose_x_0 = const()[name = tensor("x_193_transpose_x_0"), val = tensor(false)]; + tensor x_193_transpose_y_0 = const()[name = tensor("x_193_transpose_y_0"), val = tensor(false)]; + tensor value_37_cast_fp16 = transpose(perm = value_37_perm_0, x = var_1748_cast_fp16)[name = tensor("transpose_441")]; + tensor x_193_cast_fp16 = matmul(transpose_x = x_193_transpose_x_0, transpose_y = x_193_transpose_y_0, x = input_477_cast_fp16, y = value_37_cast_fp16)[name = tensor("x_193_cast_fp16")]; + tensor var_1779_perm_0 = const()[name = tensor("op_1779_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1781 = const()[name = tensor("op_1781"), val = tensor([1, -1, 512])]; + tensor var_1779_cast_fp16 = transpose(perm = var_1779_perm_0, x = x_193_cast_fp16)[name = tensor("transpose_436")]; + tensor input_479_cast_fp16 = reshape(shape = var_1781, x = var_1779_cast_fp16)[name = tensor("input_479_cast_fp16")]; + tensor e_encoders_17_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_17_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115441536)))]; + tensor e_encoders_17_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_17_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115965888)))]; + tensor linear_73_cast_fp16 = linear(bias = e_encoders_17_self_attn_linear_out_bias_to_fp16, weight = e_encoders_17_self_attn_linear_out_weight_to_fp16, x = input_479_cast_fp16)[name = tensor("linear_73_cast_fp16")]; + tensor input_481_cast_fp16 = add(x = linear_73_cast_fp16, y = fsmn_memory_37_cast_fp16)[name = tensor("input_481_cast_fp16")]; + tensor input_483_cast_fp16 = add(x = input_469_cast_fp16, y = input_481_cast_fp16)[name = tensor("input_483_cast_fp16")]; + tensor input_485_axes_0 = const()[name = tensor("input_485_axes_0"), val = tensor([-1])]; + tensor e_encoders_17_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_17_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115966976)))]; + tensor e_encoders_17_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_17_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115968064)))]; + tensor input_485_cast_fp16 = layer_norm(axes = input_485_axes_0, beta = e_encoders_17_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_17_norm2_weight_to_fp16, x = input_483_cast_fp16)[name = tensor("input_485_cast_fp16")]; + tensor e_encoders_17_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_17_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115969152)))]; + tensor e_encoders_17_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_17_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118066368)))]; + tensor linear_74_cast_fp16 = linear(bias = e_encoders_17_feed_forward_w_1_bias_to_fp16, weight = e_encoders_17_feed_forward_w_1_weight_to_fp16, x = input_485_cast_fp16)[name = tensor("linear_74_cast_fp16")]; + tensor input_489_cast_fp16 = relu(x = linear_74_cast_fp16)[name = tensor("input_489_cast_fp16")]; + tensor e_encoders_17_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_17_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118070528)))]; + tensor e_encoders_17_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_17_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120167744)))]; + tensor linear_75_cast_fp16 = linear(bias = e_encoders_17_feed_forward_w_2_bias_to_fp16, weight = e_encoders_17_feed_forward_w_2_weight_to_fp16, x = input_489_cast_fp16)[name = tensor("linear_75_cast_fp16")]; + tensor input_495_cast_fp16 = add(x = input_483_cast_fp16, y = linear_75_cast_fp16)[name = tensor("input_495_cast_fp16")]; + tensor x_195_axes_0 = const()[name = tensor("x_195_axes_0"), val = tensor([-1])]; + tensor e_encoders_18_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_18_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120168832)))]; + tensor e_encoders_18_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_18_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120169920)))]; + tensor x_195_cast_fp16 = layer_norm(axes = x_195_axes_0, beta = e_encoders_18_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_18_norm1_weight_to_fp16, x = input_495_cast_fp16)[name = tensor("x_195_cast_fp16")]; + tensor e_encoders_18_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_18_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120171008)))]; + tensor e_encoders_18_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_18_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121743936)))]; + tensor linear_76_cast_fp16 = linear(bias = e_encoders_18_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_18_self_attn_linear_q_k_v_weight_to_fp16, x = x_195_cast_fp16)[name = tensor("linear_76_cast_fp16")]; + tensor tile_19 = const()[name = tensor("tile_19"), val = tensor([512, 512, 512])]; + tensor var_1825_axis_0 = const()[name = tensor("op_1825_axis_0"), val = tensor(-1)]; + tensor var_1825_cast_fp16_0, tensor var_1825_cast_fp16_1, tensor var_1825_cast_fp16_2 = split(axis = var_1825_axis_0, split_sizes = tile_19, x = linear_76_cast_fp16)[name = tensor("op_1825_cast_fp16")]; + tensor concat_58x = const()[name = tensor("concat_58x"), val = tensor([1, -1, 4, 128])]; + tensor var_1830_cast_fp16 = reshape(shape = concat_58x, x = var_1825_cast_fp16_0)[name = tensor("op_1830_cast_fp16")]; + tensor concat_59x = const()[name = tensor("concat_59x"), val = tensor([1, -1, 4, 128])]; + tensor var_1833_cast_fp16 = reshape(shape = concat_59x, x = var_1825_cast_fp16_1)[name = tensor("op_1833_cast_fp16")]; + tensor concat_60x = const()[name = tensor("concat_60x"), val = tensor([1, -1, 4, 128])]; + tensor var_1836_cast_fp16 = reshape(shape = concat_60x, x = var_1825_cast_fp16_2)[name = tensor("op_1836_cast_fp16")]; + tensor value_39_perm_0 = const()[name = tensor("value_39_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_39_cast_fp16 = mul(x = var_1825_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor input_497_perm_0 = const()[name = tensor("input_497_perm_0"), val = tensor([0, 2, 1])]; + tensor input_499_pad_0 = const()[name = tensor("input_499_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_499_mode_0 = const()[name = tensor("input_499_mode_0"), val = tensor("constant")]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(0x0p+0)]; + tensor input_497_cast_fp16 = transpose(perm = input_497_perm_0, x = inputs_39_cast_fp16)[name = tensor("transpose_434")]; + tensor input_499_cast_fp16 = pad(constant_val = const_47_to_fp16, mode = input_499_mode_0, pad = input_499_pad_0, x = input_497_cast_fp16)[name = tensor("input_499_cast_fp16")]; + tensor x_197_pad_type_0 = const()[name = tensor("x_197_pad_type_0"), val = tensor("valid")]; + tensor x_197_groups_0 = const()[name = tensor("x_197_groups_0"), val = tensor(512)]; + tensor x_197_strides_0 = const()[name = tensor("x_197_strides_0"), val = tensor([1])]; + tensor x_197_pad_0 = const()[name = tensor("x_197_pad_0"), val = tensor([0, 0])]; + tensor x_197_dilations_0 = const()[name = tensor("x_197_dilations_0"), val = tensor([1])]; + tensor e_encoders_18_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_18_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121747072)))]; + tensor x_197_cast_fp16 = conv(dilations = x_197_dilations_0, groups = x_197_groups_0, pad = x_197_pad_0, pad_type = x_197_pad_type_0, strides = x_197_strides_0, weight = e_encoders_18_self_attn_fsmn_block_weight_to_fp16, x = input_499_cast_fp16)[name = tensor("x_197_cast_fp16")]; + tensor x_199_perm_0 = const()[name = tensor("x_199_perm_0"), val = tensor([0, 2, 1])]; + tensor x_199_cast_fp16 = transpose(perm = x_199_perm_0, x = x_197_cast_fp16)[name = tensor("transpose_433")]; + tensor input_501_cast_fp16 = add(x = x_199_cast_fp16, y = inputs_39_cast_fp16)[name = tensor("input_501_cast_fp16")]; + tensor fsmn_memory_39_cast_fp16 = mul(x = input_501_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_39_cast_fp16")]; + tensor var_1855_to_fp16 = const()[name = tensor("op_1855_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_79_cast_fp16 = mul(x = var_1830_cast_fp16, y = var_1855_to_fp16)[name = tensor("q_h_79_cast_fp16")]; + tensor scores_77_transpose_x_0 = const()[name = tensor("scores_77_transpose_x_0"), val = tensor(false)]; + tensor scores_77_transpose_y_0 = const()[name = tensor("scores_77_transpose_y_0"), val = tensor(false)]; + tensor transpose_188_perm_0 = const()[name = tensor("transpose_188_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_189_perm_0 = const()[name = tensor("transpose_189_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_189 = transpose(perm = transpose_189_perm_0, x = var_1833_cast_fp16)[name = tensor("transpose_431")]; + tensor transpose_188 = transpose(perm = transpose_188_perm_0, x = q_h_79_cast_fp16)[name = tensor("transpose_432")]; + tensor scores_77_cast_fp16 = matmul(transpose_x = scores_77_transpose_x_0, transpose_y = scores_77_transpose_y_0, x = transpose_188, y = transpose_189)[name = tensor("scores_77_cast_fp16")]; + tensor scores_79_cast_fp16 = select(a = var_11_to_fp16, b = scores_77_cast_fp16, cond = mask_5)[name = tensor("scores_79_cast_fp16")]; + tensor var_1863_cast_fp16 = softmax(axis = var_20, x = scores_79_cast_fp16)[name = tensor("op_1863_cast_fp16")]; + tensor input_503_cast_fp16 = select(a = var_6_to_fp16, b = var_1863_cast_fp16, cond = mask_5)[name = tensor("input_503_cast_fp16")]; + tensor x_203_transpose_x_0 = const()[name = tensor("x_203_transpose_x_0"), val = tensor(false)]; + tensor x_203_transpose_y_0 = const()[name = tensor("x_203_transpose_y_0"), val = tensor(false)]; + tensor value_39_cast_fp16 = transpose(perm = value_39_perm_0, x = var_1836_cast_fp16)[name = tensor("transpose_435")]; + tensor x_203_cast_fp16 = matmul(transpose_x = x_203_transpose_x_0, transpose_y = x_203_transpose_y_0, x = input_503_cast_fp16, y = value_39_cast_fp16)[name = tensor("x_203_cast_fp16")]; + tensor var_1867_perm_0 = const()[name = tensor("op_1867_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1869 = const()[name = tensor("op_1869"), val = tensor([1, -1, 512])]; + tensor var_1867_cast_fp16 = transpose(perm = var_1867_perm_0, x = x_203_cast_fp16)[name = tensor("transpose_430")]; + tensor input_505_cast_fp16 = reshape(shape = var_1869, x = var_1867_cast_fp16)[name = tensor("input_505_cast_fp16")]; + tensor e_encoders_18_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_18_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121758400)))]; + tensor e_encoders_18_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_18_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122282752)))]; + tensor linear_77_cast_fp16 = linear(bias = e_encoders_18_self_attn_linear_out_bias_to_fp16, weight = e_encoders_18_self_attn_linear_out_weight_to_fp16, x = input_505_cast_fp16)[name = tensor("linear_77_cast_fp16")]; + tensor input_507_cast_fp16 = add(x = linear_77_cast_fp16, y = fsmn_memory_39_cast_fp16)[name = tensor("input_507_cast_fp16")]; + tensor input_509_cast_fp16 = add(x = input_495_cast_fp16, y = input_507_cast_fp16)[name = tensor("input_509_cast_fp16")]; + tensor input_511_axes_0 = const()[name = tensor("input_511_axes_0"), val = tensor([-1])]; + tensor e_encoders_18_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_18_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122283840)))]; + tensor e_encoders_18_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_18_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122284928)))]; + tensor input_511_cast_fp16 = layer_norm(axes = input_511_axes_0, beta = e_encoders_18_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_18_norm2_weight_to_fp16, x = input_509_cast_fp16)[name = tensor("input_511_cast_fp16")]; + tensor e_encoders_18_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_18_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122286016)))]; + tensor e_encoders_18_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_18_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124383232)))]; + tensor linear_78_cast_fp16 = linear(bias = e_encoders_18_feed_forward_w_1_bias_to_fp16, weight = e_encoders_18_feed_forward_w_1_weight_to_fp16, x = input_511_cast_fp16)[name = tensor("linear_78_cast_fp16")]; + tensor input_515_cast_fp16 = relu(x = linear_78_cast_fp16)[name = tensor("input_515_cast_fp16")]; + tensor e_encoders_18_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_18_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124387392)))]; + tensor e_encoders_18_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_18_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126484608)))]; + tensor linear_79_cast_fp16 = linear(bias = e_encoders_18_feed_forward_w_2_bias_to_fp16, weight = e_encoders_18_feed_forward_w_2_weight_to_fp16, x = input_515_cast_fp16)[name = tensor("linear_79_cast_fp16")]; + tensor input_521_cast_fp16 = add(x = input_509_cast_fp16, y = linear_79_cast_fp16)[name = tensor("input_521_cast_fp16")]; + tensor x_205_axes_0 = const()[name = tensor("x_205_axes_0"), val = tensor([-1])]; + tensor e_encoders_19_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_19_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126485696)))]; + tensor e_encoders_19_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_19_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126486784)))]; + tensor x_205_cast_fp16 = layer_norm(axes = x_205_axes_0, beta = e_encoders_19_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_19_norm1_weight_to_fp16, x = input_521_cast_fp16)[name = tensor("x_205_cast_fp16")]; + tensor e_encoders_19_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_19_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126487872)))]; + tensor e_encoders_19_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_19_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128060800)))]; + tensor linear_80_cast_fp16 = linear(bias = e_encoders_19_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_19_self_attn_linear_q_k_v_weight_to_fp16, x = x_205_cast_fp16)[name = tensor("linear_80_cast_fp16")]; + tensor tile_20 = const()[name = tensor("tile_20"), val = tensor([512, 512, 512])]; + tensor var_1913_axis_0 = const()[name = tensor("op_1913_axis_0"), val = tensor(-1)]; + tensor var_1913_cast_fp16_0, tensor var_1913_cast_fp16_1, tensor var_1913_cast_fp16_2 = split(axis = var_1913_axis_0, split_sizes = tile_20, x = linear_80_cast_fp16)[name = tensor("op_1913_cast_fp16")]; + tensor concat_61x = const()[name = tensor("concat_61x"), val = tensor([1, -1, 4, 128])]; + tensor var_1918_cast_fp16 = reshape(shape = concat_61x, x = var_1913_cast_fp16_0)[name = tensor("op_1918_cast_fp16")]; + tensor concat_62x = const()[name = tensor("concat_62x"), val = tensor([1, -1, 4, 128])]; + tensor var_1921_cast_fp16 = reshape(shape = concat_62x, x = var_1913_cast_fp16_1)[name = tensor("op_1921_cast_fp16")]; + tensor concat_63x = const()[name = tensor("concat_63x"), val = tensor([1, -1, 4, 128])]; + tensor var_1924_cast_fp16 = reshape(shape = concat_63x, x = var_1913_cast_fp16_2)[name = tensor("op_1924_cast_fp16")]; + tensor value_41_perm_0 = const()[name = tensor("value_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_41_cast_fp16 = mul(x = var_1913_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor input_523_perm_0 = const()[name = tensor("input_523_perm_0"), val = tensor([0, 2, 1])]; + tensor input_525_pad_0 = const()[name = tensor("input_525_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_525_mode_0 = const()[name = tensor("input_525_mode_0"), val = tensor("constant")]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(0x0p+0)]; + tensor input_523_cast_fp16 = transpose(perm = input_523_perm_0, x = inputs_41_cast_fp16)[name = tensor("transpose_428")]; + tensor input_525_cast_fp16 = pad(constant_val = const_49_to_fp16, mode = input_525_mode_0, pad = input_525_pad_0, x = input_523_cast_fp16)[name = tensor("input_525_cast_fp16")]; + tensor x_207_pad_type_0 = const()[name = tensor("x_207_pad_type_0"), val = tensor("valid")]; + tensor x_207_groups_0 = const()[name = tensor("x_207_groups_0"), val = tensor(512)]; + tensor x_207_strides_0 = const()[name = tensor("x_207_strides_0"), val = tensor([1])]; + tensor x_207_pad_0 = const()[name = tensor("x_207_pad_0"), val = tensor([0, 0])]; + tensor x_207_dilations_0 = const()[name = tensor("x_207_dilations_0"), val = tensor([1])]; + tensor e_encoders_19_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_19_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128063936)))]; + tensor x_207_cast_fp16 = conv(dilations = x_207_dilations_0, groups = x_207_groups_0, pad = x_207_pad_0, pad_type = x_207_pad_type_0, strides = x_207_strides_0, weight = e_encoders_19_self_attn_fsmn_block_weight_to_fp16, x = input_525_cast_fp16)[name = tensor("x_207_cast_fp16")]; + tensor x_209_perm_0 = const()[name = tensor("x_209_perm_0"), val = tensor([0, 2, 1])]; + tensor x_209_cast_fp16 = transpose(perm = x_209_perm_0, x = x_207_cast_fp16)[name = tensor("transpose_427")]; + tensor input_527_cast_fp16 = add(x = x_209_cast_fp16, y = inputs_41_cast_fp16)[name = tensor("input_527_cast_fp16")]; + tensor fsmn_memory_41_cast_fp16 = mul(x = input_527_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_41_cast_fp16")]; + tensor var_1943_to_fp16 = const()[name = tensor("op_1943_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_83_cast_fp16 = mul(x = var_1918_cast_fp16, y = var_1943_to_fp16)[name = tensor("q_h_83_cast_fp16")]; + tensor scores_81_transpose_x_0 = const()[name = tensor("scores_81_transpose_x_0"), val = tensor(false)]; + tensor scores_81_transpose_y_0 = const()[name = tensor("scores_81_transpose_y_0"), val = tensor(false)]; + tensor transpose_190_perm_0 = const()[name = tensor("transpose_190_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_191_perm_0 = const()[name = tensor("transpose_191_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_191 = transpose(perm = transpose_191_perm_0, x = var_1921_cast_fp16)[name = tensor("transpose_425")]; + tensor transpose_190 = transpose(perm = transpose_190_perm_0, x = q_h_83_cast_fp16)[name = tensor("transpose_426")]; + tensor scores_81_cast_fp16 = matmul(transpose_x = scores_81_transpose_x_0, transpose_y = scores_81_transpose_y_0, x = transpose_190, y = transpose_191)[name = tensor("scores_81_cast_fp16")]; + tensor scores_83_cast_fp16 = select(a = var_11_to_fp16, b = scores_81_cast_fp16, cond = mask_5)[name = tensor("scores_83_cast_fp16")]; + tensor var_1951_cast_fp16 = softmax(axis = var_20, x = scores_83_cast_fp16)[name = tensor("op_1951_cast_fp16")]; + tensor input_529_cast_fp16 = select(a = var_6_to_fp16, b = var_1951_cast_fp16, cond = mask_5)[name = tensor("input_529_cast_fp16")]; + tensor x_213_transpose_x_0 = const()[name = tensor("x_213_transpose_x_0"), val = tensor(false)]; + tensor x_213_transpose_y_0 = const()[name = tensor("x_213_transpose_y_0"), val = tensor(false)]; + tensor value_41_cast_fp16 = transpose(perm = value_41_perm_0, x = var_1924_cast_fp16)[name = tensor("transpose_429")]; + tensor x_213_cast_fp16 = matmul(transpose_x = x_213_transpose_x_0, transpose_y = x_213_transpose_y_0, x = input_529_cast_fp16, y = value_41_cast_fp16)[name = tensor("x_213_cast_fp16")]; + tensor var_1955_perm_0 = const()[name = tensor("op_1955_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1957 = const()[name = tensor("op_1957"), val = tensor([1, -1, 512])]; + tensor var_1955_cast_fp16 = transpose(perm = var_1955_perm_0, x = x_213_cast_fp16)[name = tensor("transpose_424")]; + tensor input_531_cast_fp16 = reshape(shape = var_1957, x = var_1955_cast_fp16)[name = tensor("input_531_cast_fp16")]; + tensor e_encoders_19_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_19_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128075264)))]; + tensor e_encoders_19_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_19_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128599616)))]; + tensor linear_81_cast_fp16 = linear(bias = e_encoders_19_self_attn_linear_out_bias_to_fp16, weight = e_encoders_19_self_attn_linear_out_weight_to_fp16, x = input_531_cast_fp16)[name = tensor("linear_81_cast_fp16")]; + tensor input_533_cast_fp16 = add(x = linear_81_cast_fp16, y = fsmn_memory_41_cast_fp16)[name = tensor("input_533_cast_fp16")]; + tensor input_535_cast_fp16 = add(x = input_521_cast_fp16, y = input_533_cast_fp16)[name = tensor("input_535_cast_fp16")]; + tensor input_537_axes_0 = const()[name = tensor("input_537_axes_0"), val = tensor([-1])]; + tensor e_encoders_19_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_19_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128600704)))]; + tensor e_encoders_19_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_19_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128601792)))]; + tensor input_537_cast_fp16 = layer_norm(axes = input_537_axes_0, beta = e_encoders_19_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_19_norm2_weight_to_fp16, x = input_535_cast_fp16)[name = tensor("input_537_cast_fp16")]; + tensor e_encoders_19_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_19_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128602880)))]; + tensor e_encoders_19_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_19_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130700096)))]; + tensor linear_82_cast_fp16 = linear(bias = e_encoders_19_feed_forward_w_1_bias_to_fp16, weight = e_encoders_19_feed_forward_w_1_weight_to_fp16, x = input_537_cast_fp16)[name = tensor("linear_82_cast_fp16")]; + tensor input_541_cast_fp16 = relu(x = linear_82_cast_fp16)[name = tensor("input_541_cast_fp16")]; + tensor e_encoders_19_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_19_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130704256)))]; + tensor e_encoders_19_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_19_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132801472)))]; + tensor linear_83_cast_fp16 = linear(bias = e_encoders_19_feed_forward_w_2_bias_to_fp16, weight = e_encoders_19_feed_forward_w_2_weight_to_fp16, x = input_541_cast_fp16)[name = tensor("linear_83_cast_fp16")]; + tensor input_547_cast_fp16 = add(x = input_535_cast_fp16, y = linear_83_cast_fp16)[name = tensor("input_547_cast_fp16")]; + tensor x_215_axes_0 = const()[name = tensor("x_215_axes_0"), val = tensor([-1])]; + tensor e_encoders_20_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_20_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132802560)))]; + tensor e_encoders_20_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_20_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132803648)))]; + tensor x_215_cast_fp16 = layer_norm(axes = x_215_axes_0, beta = e_encoders_20_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_20_norm1_weight_to_fp16, x = input_547_cast_fp16)[name = tensor("x_215_cast_fp16")]; + tensor e_encoders_20_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_20_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132804736)))]; + tensor e_encoders_20_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_20_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134377664)))]; + tensor linear_84_cast_fp16 = linear(bias = e_encoders_20_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_20_self_attn_linear_q_k_v_weight_to_fp16, x = x_215_cast_fp16)[name = tensor("linear_84_cast_fp16")]; + tensor tile_21 = const()[name = tensor("tile_21"), val = tensor([512, 512, 512])]; + tensor var_2001_axis_0 = const()[name = tensor("op_2001_axis_0"), val = tensor(-1)]; + tensor var_2001_cast_fp16_0, tensor var_2001_cast_fp16_1, tensor var_2001_cast_fp16_2 = split(axis = var_2001_axis_0, split_sizes = tile_21, x = linear_84_cast_fp16)[name = tensor("op_2001_cast_fp16")]; + tensor concat_64x = const()[name = tensor("concat_64x"), val = tensor([1, -1, 4, 128])]; + tensor var_2006_cast_fp16 = reshape(shape = concat_64x, x = var_2001_cast_fp16_0)[name = tensor("op_2006_cast_fp16")]; + tensor concat_65x = const()[name = tensor("concat_65x"), val = tensor([1, -1, 4, 128])]; + tensor var_2009_cast_fp16 = reshape(shape = concat_65x, x = var_2001_cast_fp16_1)[name = tensor("op_2009_cast_fp16")]; + tensor concat_66x = const()[name = tensor("concat_66x"), val = tensor([1, -1, 4, 128])]; + tensor var_2012_cast_fp16 = reshape(shape = concat_66x, x = var_2001_cast_fp16_2)[name = tensor("op_2012_cast_fp16")]; + tensor value_43_perm_0 = const()[name = tensor("value_43_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_43_cast_fp16 = mul(x = var_2001_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor input_549_perm_0 = const()[name = tensor("input_549_perm_0"), val = tensor([0, 2, 1])]; + tensor input_551_pad_0 = const()[name = tensor("input_551_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_551_mode_0 = const()[name = tensor("input_551_mode_0"), val = tensor("constant")]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(0x0p+0)]; + tensor input_549_cast_fp16 = transpose(perm = input_549_perm_0, x = inputs_43_cast_fp16)[name = tensor("transpose_422")]; + tensor input_551_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_551_mode_0, pad = input_551_pad_0, x = input_549_cast_fp16)[name = tensor("input_551_cast_fp16")]; + tensor x_217_pad_type_0 = const()[name = tensor("x_217_pad_type_0"), val = tensor("valid")]; + tensor x_217_groups_0 = const()[name = tensor("x_217_groups_0"), val = tensor(512)]; + tensor x_217_strides_0 = const()[name = tensor("x_217_strides_0"), val = tensor([1])]; + tensor x_217_pad_0 = const()[name = tensor("x_217_pad_0"), val = tensor([0, 0])]; + tensor x_217_dilations_0 = const()[name = tensor("x_217_dilations_0"), val = tensor([1])]; + tensor e_encoders_20_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_20_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134380800)))]; + tensor x_217_cast_fp16 = conv(dilations = x_217_dilations_0, groups = x_217_groups_0, pad = x_217_pad_0, pad_type = x_217_pad_type_0, strides = x_217_strides_0, weight = e_encoders_20_self_attn_fsmn_block_weight_to_fp16, x = input_551_cast_fp16)[name = tensor("x_217_cast_fp16")]; + tensor x_219_perm_0 = const()[name = tensor("x_219_perm_0"), val = tensor([0, 2, 1])]; + tensor x_219_cast_fp16 = transpose(perm = x_219_perm_0, x = x_217_cast_fp16)[name = tensor("transpose_421")]; + tensor input_553_cast_fp16 = add(x = x_219_cast_fp16, y = inputs_43_cast_fp16)[name = tensor("input_553_cast_fp16")]; + tensor fsmn_memory_43_cast_fp16 = mul(x = input_553_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_43_cast_fp16")]; + tensor var_2031_to_fp16 = const()[name = tensor("op_2031_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_87_cast_fp16 = mul(x = var_2006_cast_fp16, y = var_2031_to_fp16)[name = tensor("q_h_87_cast_fp16")]; + tensor scores_85_transpose_x_0 = const()[name = tensor("scores_85_transpose_x_0"), val = tensor(false)]; + tensor scores_85_transpose_y_0 = const()[name = tensor("scores_85_transpose_y_0"), val = tensor(false)]; + tensor transpose_192_perm_0 = const()[name = tensor("transpose_192_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_193_perm_0 = const()[name = tensor("transpose_193_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_193 = transpose(perm = transpose_193_perm_0, x = var_2009_cast_fp16)[name = tensor("transpose_419")]; + tensor transpose_192 = transpose(perm = transpose_192_perm_0, x = q_h_87_cast_fp16)[name = tensor("transpose_420")]; + tensor scores_85_cast_fp16 = matmul(transpose_x = scores_85_transpose_x_0, transpose_y = scores_85_transpose_y_0, x = transpose_192, y = transpose_193)[name = tensor("scores_85_cast_fp16")]; + tensor scores_87_cast_fp16 = select(a = var_11_to_fp16, b = scores_85_cast_fp16, cond = mask_5)[name = tensor("scores_87_cast_fp16")]; + tensor var_2039_cast_fp16 = softmax(axis = var_20, x = scores_87_cast_fp16)[name = tensor("op_2039_cast_fp16")]; + tensor input_555_cast_fp16 = select(a = var_6_to_fp16, b = var_2039_cast_fp16, cond = mask_5)[name = tensor("input_555_cast_fp16")]; + tensor x_223_transpose_x_0 = const()[name = tensor("x_223_transpose_x_0"), val = tensor(false)]; + tensor x_223_transpose_y_0 = const()[name = tensor("x_223_transpose_y_0"), val = tensor(false)]; + tensor value_43_cast_fp16 = transpose(perm = value_43_perm_0, x = var_2012_cast_fp16)[name = tensor("transpose_423")]; + tensor x_223_cast_fp16 = matmul(transpose_x = x_223_transpose_x_0, transpose_y = x_223_transpose_y_0, x = input_555_cast_fp16, y = value_43_cast_fp16)[name = tensor("x_223_cast_fp16")]; + tensor var_2043_perm_0 = const()[name = tensor("op_2043_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2045 = const()[name = tensor("op_2045"), val = tensor([1, -1, 512])]; + tensor var_2043_cast_fp16 = transpose(perm = var_2043_perm_0, x = x_223_cast_fp16)[name = tensor("transpose_418")]; + tensor input_557_cast_fp16 = reshape(shape = var_2045, x = var_2043_cast_fp16)[name = tensor("input_557_cast_fp16")]; + tensor e_encoders_20_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_20_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134392128)))]; + tensor e_encoders_20_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_20_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134916480)))]; + tensor linear_85_cast_fp16 = linear(bias = e_encoders_20_self_attn_linear_out_bias_to_fp16, weight = e_encoders_20_self_attn_linear_out_weight_to_fp16, x = input_557_cast_fp16)[name = tensor("linear_85_cast_fp16")]; + tensor input_559_cast_fp16 = add(x = linear_85_cast_fp16, y = fsmn_memory_43_cast_fp16)[name = tensor("input_559_cast_fp16")]; + tensor input_561_cast_fp16 = add(x = input_547_cast_fp16, y = input_559_cast_fp16)[name = tensor("input_561_cast_fp16")]; + tensor input_563_axes_0 = const()[name = tensor("input_563_axes_0"), val = tensor([-1])]; + tensor e_encoders_20_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_20_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134917568)))]; + tensor e_encoders_20_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_20_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134918656)))]; + tensor input_563_cast_fp16 = layer_norm(axes = input_563_axes_0, beta = e_encoders_20_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_20_norm2_weight_to_fp16, x = input_561_cast_fp16)[name = tensor("input_563_cast_fp16")]; + tensor e_encoders_20_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_20_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134919744)))]; + tensor e_encoders_20_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_20_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137016960)))]; + tensor linear_86_cast_fp16 = linear(bias = e_encoders_20_feed_forward_w_1_bias_to_fp16, weight = e_encoders_20_feed_forward_w_1_weight_to_fp16, x = input_563_cast_fp16)[name = tensor("linear_86_cast_fp16")]; + tensor input_567_cast_fp16 = relu(x = linear_86_cast_fp16)[name = tensor("input_567_cast_fp16")]; + tensor e_encoders_20_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_20_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137021120)))]; + tensor e_encoders_20_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_20_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139118336)))]; + tensor linear_87_cast_fp16 = linear(bias = e_encoders_20_feed_forward_w_2_bias_to_fp16, weight = e_encoders_20_feed_forward_w_2_weight_to_fp16, x = input_567_cast_fp16)[name = tensor("linear_87_cast_fp16")]; + tensor input_573_cast_fp16 = add(x = input_561_cast_fp16, y = linear_87_cast_fp16)[name = tensor("input_573_cast_fp16")]; + tensor x_225_axes_0 = const()[name = tensor("x_225_axes_0"), val = tensor([-1])]; + tensor e_encoders_21_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_21_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139119424)))]; + tensor e_encoders_21_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_21_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139120512)))]; + tensor x_225_cast_fp16 = layer_norm(axes = x_225_axes_0, beta = e_encoders_21_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_21_norm1_weight_to_fp16, x = input_573_cast_fp16)[name = tensor("x_225_cast_fp16")]; + tensor e_encoders_21_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_21_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139121600)))]; + tensor e_encoders_21_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_21_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140694528)))]; + tensor linear_88_cast_fp16 = linear(bias = e_encoders_21_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_21_self_attn_linear_q_k_v_weight_to_fp16, x = x_225_cast_fp16)[name = tensor("linear_88_cast_fp16")]; + tensor tile_22 = const()[name = tensor("tile_22"), val = tensor([512, 512, 512])]; + tensor var_2089_axis_0 = const()[name = tensor("op_2089_axis_0"), val = tensor(-1)]; + tensor var_2089_cast_fp16_0, tensor var_2089_cast_fp16_1, tensor var_2089_cast_fp16_2 = split(axis = var_2089_axis_0, split_sizes = tile_22, x = linear_88_cast_fp16)[name = tensor("op_2089_cast_fp16")]; + tensor concat_67x = const()[name = tensor("concat_67x"), val = tensor([1, -1, 4, 128])]; + tensor var_2094_cast_fp16 = reshape(shape = concat_67x, x = var_2089_cast_fp16_0)[name = tensor("op_2094_cast_fp16")]; + tensor concat_68x = const()[name = tensor("concat_68x"), val = tensor([1, -1, 4, 128])]; + tensor var_2097_cast_fp16 = reshape(shape = concat_68x, x = var_2089_cast_fp16_1)[name = tensor("op_2097_cast_fp16")]; + tensor concat_69x = const()[name = tensor("concat_69x"), val = tensor([1, -1, 4, 128])]; + tensor var_2100_cast_fp16 = reshape(shape = concat_69x, x = var_2089_cast_fp16_2)[name = tensor("op_2100_cast_fp16")]; + tensor value_45_perm_0 = const()[name = tensor("value_45_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_45_cast_fp16 = mul(x = var_2089_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor input_575_perm_0 = const()[name = tensor("input_575_perm_0"), val = tensor([0, 2, 1])]; + tensor input_577_pad_0 = const()[name = tensor("input_577_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_577_mode_0 = const()[name = tensor("input_577_mode_0"), val = tensor("constant")]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(0x0p+0)]; + tensor input_575_cast_fp16 = transpose(perm = input_575_perm_0, x = inputs_45_cast_fp16)[name = tensor("transpose_416")]; + tensor input_577_cast_fp16 = pad(constant_val = const_53_to_fp16, mode = input_577_mode_0, pad = input_577_pad_0, x = input_575_cast_fp16)[name = tensor("input_577_cast_fp16")]; + tensor x_227_pad_type_0 = const()[name = tensor("x_227_pad_type_0"), val = tensor("valid")]; + tensor x_227_groups_0 = const()[name = tensor("x_227_groups_0"), val = tensor(512)]; + tensor x_227_strides_0 = const()[name = tensor("x_227_strides_0"), val = tensor([1])]; + tensor x_227_pad_0 = const()[name = tensor("x_227_pad_0"), val = tensor([0, 0])]; + tensor x_227_dilations_0 = const()[name = tensor("x_227_dilations_0"), val = tensor([1])]; + tensor e_encoders_21_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_21_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140697664)))]; + tensor x_227_cast_fp16 = conv(dilations = x_227_dilations_0, groups = x_227_groups_0, pad = x_227_pad_0, pad_type = x_227_pad_type_0, strides = x_227_strides_0, weight = e_encoders_21_self_attn_fsmn_block_weight_to_fp16, x = input_577_cast_fp16)[name = tensor("x_227_cast_fp16")]; + tensor x_229_perm_0 = const()[name = tensor("x_229_perm_0"), val = tensor([0, 2, 1])]; + tensor x_229_cast_fp16 = transpose(perm = x_229_perm_0, x = x_227_cast_fp16)[name = tensor("transpose_415")]; + tensor input_579_cast_fp16 = add(x = x_229_cast_fp16, y = inputs_45_cast_fp16)[name = tensor("input_579_cast_fp16")]; + tensor fsmn_memory_45_cast_fp16 = mul(x = input_579_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_45_cast_fp16")]; + tensor var_2119_to_fp16 = const()[name = tensor("op_2119_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_91_cast_fp16 = mul(x = var_2094_cast_fp16, y = var_2119_to_fp16)[name = tensor("q_h_91_cast_fp16")]; + tensor scores_89_transpose_x_0 = const()[name = tensor("scores_89_transpose_x_0"), val = tensor(false)]; + tensor scores_89_transpose_y_0 = const()[name = tensor("scores_89_transpose_y_0"), val = tensor(false)]; + tensor transpose_194_perm_0 = const()[name = tensor("transpose_194_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_195_perm_0 = const()[name = tensor("transpose_195_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_195 = transpose(perm = transpose_195_perm_0, x = var_2097_cast_fp16)[name = tensor("transpose_413")]; + tensor transpose_194 = transpose(perm = transpose_194_perm_0, x = q_h_91_cast_fp16)[name = tensor("transpose_414")]; + tensor scores_89_cast_fp16 = matmul(transpose_x = scores_89_transpose_x_0, transpose_y = scores_89_transpose_y_0, x = transpose_194, y = transpose_195)[name = tensor("scores_89_cast_fp16")]; + tensor scores_91_cast_fp16 = select(a = var_11_to_fp16, b = scores_89_cast_fp16, cond = mask_5)[name = tensor("scores_91_cast_fp16")]; + tensor var_2127_cast_fp16 = softmax(axis = var_20, x = scores_91_cast_fp16)[name = tensor("op_2127_cast_fp16")]; + tensor input_581_cast_fp16 = select(a = var_6_to_fp16, b = var_2127_cast_fp16, cond = mask_5)[name = tensor("input_581_cast_fp16")]; + tensor x_233_transpose_x_0 = const()[name = tensor("x_233_transpose_x_0"), val = tensor(false)]; + tensor x_233_transpose_y_0 = const()[name = tensor("x_233_transpose_y_0"), val = tensor(false)]; + tensor value_45_cast_fp16 = transpose(perm = value_45_perm_0, x = var_2100_cast_fp16)[name = tensor("transpose_417")]; + tensor x_233_cast_fp16 = matmul(transpose_x = x_233_transpose_x_0, transpose_y = x_233_transpose_y_0, x = input_581_cast_fp16, y = value_45_cast_fp16)[name = tensor("x_233_cast_fp16")]; + tensor var_2131_perm_0 = const()[name = tensor("op_2131_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2133 = const()[name = tensor("op_2133"), val = tensor([1, -1, 512])]; + tensor var_2131_cast_fp16 = transpose(perm = var_2131_perm_0, x = x_233_cast_fp16)[name = tensor("transpose_412")]; + tensor input_583_cast_fp16 = reshape(shape = var_2133, x = var_2131_cast_fp16)[name = tensor("input_583_cast_fp16")]; + tensor e_encoders_21_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_21_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140708992)))]; + tensor e_encoders_21_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_21_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141233344)))]; + tensor linear_89_cast_fp16 = linear(bias = e_encoders_21_self_attn_linear_out_bias_to_fp16, weight = e_encoders_21_self_attn_linear_out_weight_to_fp16, x = input_583_cast_fp16)[name = tensor("linear_89_cast_fp16")]; + tensor input_585_cast_fp16 = add(x = linear_89_cast_fp16, y = fsmn_memory_45_cast_fp16)[name = tensor("input_585_cast_fp16")]; + tensor input_587_cast_fp16 = add(x = input_573_cast_fp16, y = input_585_cast_fp16)[name = tensor("input_587_cast_fp16")]; + tensor input_589_axes_0 = const()[name = tensor("input_589_axes_0"), val = tensor([-1])]; + tensor e_encoders_21_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_21_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141234432)))]; + tensor e_encoders_21_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_21_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141235520)))]; + tensor input_589_cast_fp16 = layer_norm(axes = input_589_axes_0, beta = e_encoders_21_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_21_norm2_weight_to_fp16, x = input_587_cast_fp16)[name = tensor("input_589_cast_fp16")]; + tensor e_encoders_21_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_21_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141236608)))]; + tensor e_encoders_21_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_21_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143333824)))]; + tensor linear_90_cast_fp16 = linear(bias = e_encoders_21_feed_forward_w_1_bias_to_fp16, weight = e_encoders_21_feed_forward_w_1_weight_to_fp16, x = input_589_cast_fp16)[name = tensor("linear_90_cast_fp16")]; + tensor input_593_cast_fp16 = relu(x = linear_90_cast_fp16)[name = tensor("input_593_cast_fp16")]; + tensor e_encoders_21_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_21_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143337984)))]; + tensor e_encoders_21_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_21_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145435200)))]; + tensor linear_91_cast_fp16 = linear(bias = e_encoders_21_feed_forward_w_2_bias_to_fp16, weight = e_encoders_21_feed_forward_w_2_weight_to_fp16, x = input_593_cast_fp16)[name = tensor("linear_91_cast_fp16")]; + tensor input_599_cast_fp16 = add(x = input_587_cast_fp16, y = linear_91_cast_fp16)[name = tensor("input_599_cast_fp16")]; + tensor x_235_axes_0 = const()[name = tensor("x_235_axes_0"), val = tensor([-1])]; + tensor e_encoders_22_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_22_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145436288)))]; + tensor e_encoders_22_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_22_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145437376)))]; + tensor x_235_cast_fp16 = layer_norm(axes = x_235_axes_0, beta = e_encoders_22_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_22_norm1_weight_to_fp16, x = input_599_cast_fp16)[name = tensor("x_235_cast_fp16")]; + tensor e_encoders_22_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_22_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145438464)))]; + tensor e_encoders_22_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_22_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147011392)))]; + tensor linear_92_cast_fp16 = linear(bias = e_encoders_22_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_22_self_attn_linear_q_k_v_weight_to_fp16, x = x_235_cast_fp16)[name = tensor("linear_92_cast_fp16")]; + tensor tile_23 = const()[name = tensor("tile_23"), val = tensor([512, 512, 512])]; + tensor var_2177_axis_0 = const()[name = tensor("op_2177_axis_0"), val = tensor(-1)]; + tensor var_2177_cast_fp16_0, tensor var_2177_cast_fp16_1, tensor var_2177_cast_fp16_2 = split(axis = var_2177_axis_0, split_sizes = tile_23, x = linear_92_cast_fp16)[name = tensor("op_2177_cast_fp16")]; + tensor concat_70x = const()[name = tensor("concat_70x"), val = tensor([1, -1, 4, 128])]; + tensor var_2182_cast_fp16 = reshape(shape = concat_70x, x = var_2177_cast_fp16_0)[name = tensor("op_2182_cast_fp16")]; + tensor concat_71x = const()[name = tensor("concat_71x"), val = tensor([1, -1, 4, 128])]; + tensor var_2185_cast_fp16 = reshape(shape = concat_71x, x = var_2177_cast_fp16_1)[name = tensor("op_2185_cast_fp16")]; + tensor concat_72x = const()[name = tensor("concat_72x"), val = tensor([1, -1, 4, 128])]; + tensor var_2188_cast_fp16 = reshape(shape = concat_72x, x = var_2177_cast_fp16_2)[name = tensor("op_2188_cast_fp16")]; + tensor value_47_perm_0 = const()[name = tensor("value_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_47_cast_fp16 = mul(x = var_2177_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor input_601_perm_0 = const()[name = tensor("input_601_perm_0"), val = tensor([0, 2, 1])]; + tensor input_603_pad_0 = const()[name = tensor("input_603_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_603_mode_0 = const()[name = tensor("input_603_mode_0"), val = tensor("constant")]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(0x0p+0)]; + tensor input_601_cast_fp16 = transpose(perm = input_601_perm_0, x = inputs_47_cast_fp16)[name = tensor("transpose_410")]; + tensor input_603_cast_fp16 = pad(constant_val = const_55_to_fp16, mode = input_603_mode_0, pad = input_603_pad_0, x = input_601_cast_fp16)[name = tensor("input_603_cast_fp16")]; + tensor x_237_pad_type_0 = const()[name = tensor("x_237_pad_type_0"), val = tensor("valid")]; + tensor x_237_groups_0 = const()[name = tensor("x_237_groups_0"), val = tensor(512)]; + tensor x_237_strides_0 = const()[name = tensor("x_237_strides_0"), val = tensor([1])]; + tensor x_237_pad_0 = const()[name = tensor("x_237_pad_0"), val = tensor([0, 0])]; + tensor x_237_dilations_0 = const()[name = tensor("x_237_dilations_0"), val = tensor([1])]; + tensor e_encoders_22_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_22_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147014528)))]; + tensor x_237_cast_fp16 = conv(dilations = x_237_dilations_0, groups = x_237_groups_0, pad = x_237_pad_0, pad_type = x_237_pad_type_0, strides = x_237_strides_0, weight = e_encoders_22_self_attn_fsmn_block_weight_to_fp16, x = input_603_cast_fp16)[name = tensor("x_237_cast_fp16")]; + tensor x_239_perm_0 = const()[name = tensor("x_239_perm_0"), val = tensor([0, 2, 1])]; + tensor x_239_cast_fp16 = transpose(perm = x_239_perm_0, x = x_237_cast_fp16)[name = tensor("transpose_409")]; + tensor input_605_cast_fp16 = add(x = x_239_cast_fp16, y = inputs_47_cast_fp16)[name = tensor("input_605_cast_fp16")]; + tensor fsmn_memory_47_cast_fp16 = mul(x = input_605_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_47_cast_fp16")]; + tensor var_2207_to_fp16 = const()[name = tensor("op_2207_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_95_cast_fp16 = mul(x = var_2182_cast_fp16, y = var_2207_to_fp16)[name = tensor("q_h_95_cast_fp16")]; + tensor scores_93_transpose_x_0 = const()[name = tensor("scores_93_transpose_x_0"), val = tensor(false)]; + tensor scores_93_transpose_y_0 = const()[name = tensor("scores_93_transpose_y_0"), val = tensor(false)]; + tensor transpose_196_perm_0 = const()[name = tensor("transpose_196_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_197_perm_0 = const()[name = tensor("transpose_197_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_197 = transpose(perm = transpose_197_perm_0, x = var_2185_cast_fp16)[name = tensor("transpose_407")]; + tensor transpose_196 = transpose(perm = transpose_196_perm_0, x = q_h_95_cast_fp16)[name = tensor("transpose_408")]; + tensor scores_93_cast_fp16 = matmul(transpose_x = scores_93_transpose_x_0, transpose_y = scores_93_transpose_y_0, x = transpose_196, y = transpose_197)[name = tensor("scores_93_cast_fp16")]; + tensor scores_95_cast_fp16 = select(a = var_11_to_fp16, b = scores_93_cast_fp16, cond = mask_5)[name = tensor("scores_95_cast_fp16")]; + tensor var_2215_cast_fp16 = softmax(axis = var_20, x = scores_95_cast_fp16)[name = tensor("op_2215_cast_fp16")]; + tensor input_607_cast_fp16 = select(a = var_6_to_fp16, b = var_2215_cast_fp16, cond = mask_5)[name = tensor("input_607_cast_fp16")]; + tensor x_243_transpose_x_0 = const()[name = tensor("x_243_transpose_x_0"), val = tensor(false)]; + tensor x_243_transpose_y_0 = const()[name = tensor("x_243_transpose_y_0"), val = tensor(false)]; + tensor value_47_cast_fp16 = transpose(perm = value_47_perm_0, x = var_2188_cast_fp16)[name = tensor("transpose_411")]; + tensor x_243_cast_fp16 = matmul(transpose_x = x_243_transpose_x_0, transpose_y = x_243_transpose_y_0, x = input_607_cast_fp16, y = value_47_cast_fp16)[name = tensor("x_243_cast_fp16")]; + tensor var_2219_perm_0 = const()[name = tensor("op_2219_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2221 = const()[name = tensor("op_2221"), val = tensor([1, -1, 512])]; + tensor var_2219_cast_fp16 = transpose(perm = var_2219_perm_0, x = x_243_cast_fp16)[name = tensor("transpose_406")]; + tensor input_609_cast_fp16 = reshape(shape = var_2221, x = var_2219_cast_fp16)[name = tensor("input_609_cast_fp16")]; + tensor e_encoders_22_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_22_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147025856)))]; + tensor e_encoders_22_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_22_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147550208)))]; + tensor linear_93_cast_fp16 = linear(bias = e_encoders_22_self_attn_linear_out_bias_to_fp16, weight = e_encoders_22_self_attn_linear_out_weight_to_fp16, x = input_609_cast_fp16)[name = tensor("linear_93_cast_fp16")]; + tensor input_611_cast_fp16 = add(x = linear_93_cast_fp16, y = fsmn_memory_47_cast_fp16)[name = tensor("input_611_cast_fp16")]; + tensor input_613_cast_fp16 = add(x = input_599_cast_fp16, y = input_611_cast_fp16)[name = tensor("input_613_cast_fp16")]; + tensor input_615_axes_0 = const()[name = tensor("input_615_axes_0"), val = tensor([-1])]; + tensor e_encoders_22_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_22_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147551296)))]; + tensor e_encoders_22_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_22_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147552384)))]; + tensor input_615_cast_fp16 = layer_norm(axes = input_615_axes_0, beta = e_encoders_22_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_22_norm2_weight_to_fp16, x = input_613_cast_fp16)[name = tensor("input_615_cast_fp16")]; + tensor e_encoders_22_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_22_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147553472)))]; + tensor e_encoders_22_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_22_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149650688)))]; + tensor linear_94_cast_fp16 = linear(bias = e_encoders_22_feed_forward_w_1_bias_to_fp16, weight = e_encoders_22_feed_forward_w_1_weight_to_fp16, x = input_615_cast_fp16)[name = tensor("linear_94_cast_fp16")]; + tensor input_619_cast_fp16 = relu(x = linear_94_cast_fp16)[name = tensor("input_619_cast_fp16")]; + tensor e_encoders_22_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_22_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149654848)))]; + tensor e_encoders_22_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_22_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151752064)))]; + tensor linear_95_cast_fp16 = linear(bias = e_encoders_22_feed_forward_w_2_bias_to_fp16, weight = e_encoders_22_feed_forward_w_2_weight_to_fp16, x = input_619_cast_fp16)[name = tensor("linear_95_cast_fp16")]; + tensor input_625_cast_fp16 = add(x = input_613_cast_fp16, y = linear_95_cast_fp16)[name = tensor("input_625_cast_fp16")]; + tensor x_245_axes_0 = const()[name = tensor("x_245_axes_0"), val = tensor([-1])]; + tensor e_encoders_23_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_23_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151753152)))]; + tensor e_encoders_23_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_23_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151754240)))]; + tensor x_245_cast_fp16 = layer_norm(axes = x_245_axes_0, beta = e_encoders_23_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_23_norm1_weight_to_fp16, x = input_625_cast_fp16)[name = tensor("x_245_cast_fp16")]; + tensor e_encoders_23_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_23_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151755328)))]; + tensor e_encoders_23_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_23_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153328256)))]; + tensor linear_96_cast_fp16 = linear(bias = e_encoders_23_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_23_self_attn_linear_q_k_v_weight_to_fp16, x = x_245_cast_fp16)[name = tensor("linear_96_cast_fp16")]; + tensor tile_24 = const()[name = tensor("tile_24"), val = tensor([512, 512, 512])]; + tensor var_2265_axis_0 = const()[name = tensor("op_2265_axis_0"), val = tensor(-1)]; + tensor var_2265_cast_fp16_0, tensor var_2265_cast_fp16_1, tensor var_2265_cast_fp16_2 = split(axis = var_2265_axis_0, split_sizes = tile_24, x = linear_96_cast_fp16)[name = tensor("op_2265_cast_fp16")]; + tensor concat_73x = const()[name = tensor("concat_73x"), val = tensor([1, -1, 4, 128])]; + tensor var_2270_cast_fp16 = reshape(shape = concat_73x, x = var_2265_cast_fp16_0)[name = tensor("op_2270_cast_fp16")]; + tensor concat_74x = const()[name = tensor("concat_74x"), val = tensor([1, -1, 4, 128])]; + tensor var_2273_cast_fp16 = reshape(shape = concat_74x, x = var_2265_cast_fp16_1)[name = tensor("op_2273_cast_fp16")]; + tensor concat_75x = const()[name = tensor("concat_75x"), val = tensor([1, -1, 4, 128])]; + tensor var_2276_cast_fp16 = reshape(shape = concat_75x, x = var_2265_cast_fp16_2)[name = tensor("op_2276_cast_fp16")]; + tensor value_49_perm_0 = const()[name = tensor("value_49_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_49_cast_fp16 = mul(x = var_2265_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_49_cast_fp16")]; + tensor input_627_perm_0 = const()[name = tensor("input_627_perm_0"), val = tensor([0, 2, 1])]; + tensor input_629_pad_0 = const()[name = tensor("input_629_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_629_mode_0 = const()[name = tensor("input_629_mode_0"), val = tensor("constant")]; + tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(0x0p+0)]; + tensor input_627_cast_fp16 = transpose(perm = input_627_perm_0, x = inputs_49_cast_fp16)[name = tensor("transpose_404")]; + tensor input_629_cast_fp16 = pad(constant_val = const_57_to_fp16, mode = input_629_mode_0, pad = input_629_pad_0, x = input_627_cast_fp16)[name = tensor("input_629_cast_fp16")]; + tensor x_247_pad_type_0 = const()[name = tensor("x_247_pad_type_0"), val = tensor("valid")]; + tensor x_247_groups_0 = const()[name = tensor("x_247_groups_0"), val = tensor(512)]; + tensor x_247_strides_0 = const()[name = tensor("x_247_strides_0"), val = tensor([1])]; + tensor x_247_pad_0 = const()[name = tensor("x_247_pad_0"), val = tensor([0, 0])]; + tensor x_247_dilations_0 = const()[name = tensor("x_247_dilations_0"), val = tensor([1])]; + tensor e_encoders_23_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_23_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153331392)))]; + tensor x_247_cast_fp16 = conv(dilations = x_247_dilations_0, groups = x_247_groups_0, pad = x_247_pad_0, pad_type = x_247_pad_type_0, strides = x_247_strides_0, weight = e_encoders_23_self_attn_fsmn_block_weight_to_fp16, x = input_629_cast_fp16)[name = tensor("x_247_cast_fp16")]; + tensor x_249_perm_0 = const()[name = tensor("x_249_perm_0"), val = tensor([0, 2, 1])]; + tensor x_249_cast_fp16 = transpose(perm = x_249_perm_0, x = x_247_cast_fp16)[name = tensor("transpose_403")]; + tensor input_631_cast_fp16 = add(x = x_249_cast_fp16, y = inputs_49_cast_fp16)[name = tensor("input_631_cast_fp16")]; + tensor fsmn_memory_49_cast_fp16 = mul(x = input_631_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_49_cast_fp16")]; + tensor var_2295_to_fp16 = const()[name = tensor("op_2295_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_99_cast_fp16 = mul(x = var_2270_cast_fp16, y = var_2295_to_fp16)[name = tensor("q_h_99_cast_fp16")]; + tensor scores_97_transpose_x_0 = const()[name = tensor("scores_97_transpose_x_0"), val = tensor(false)]; + tensor scores_97_transpose_y_0 = const()[name = tensor("scores_97_transpose_y_0"), val = tensor(false)]; + tensor transpose_198_perm_0 = const()[name = tensor("transpose_198_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_199_perm_0 = const()[name = tensor("transpose_199_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_199 = transpose(perm = transpose_199_perm_0, x = var_2273_cast_fp16)[name = tensor("transpose_401")]; + tensor transpose_198 = transpose(perm = transpose_198_perm_0, x = q_h_99_cast_fp16)[name = tensor("transpose_402")]; + tensor scores_97_cast_fp16 = matmul(transpose_x = scores_97_transpose_x_0, transpose_y = scores_97_transpose_y_0, x = transpose_198, y = transpose_199)[name = tensor("scores_97_cast_fp16")]; + tensor scores_99_cast_fp16 = select(a = var_11_to_fp16, b = scores_97_cast_fp16, cond = mask_5)[name = tensor("scores_99_cast_fp16")]; + tensor var_2303_cast_fp16 = softmax(axis = var_20, x = scores_99_cast_fp16)[name = tensor("op_2303_cast_fp16")]; + tensor input_633_cast_fp16 = select(a = var_6_to_fp16, b = var_2303_cast_fp16, cond = mask_5)[name = tensor("input_633_cast_fp16")]; + tensor x_253_transpose_x_0 = const()[name = tensor("x_253_transpose_x_0"), val = tensor(false)]; + tensor x_253_transpose_y_0 = const()[name = tensor("x_253_transpose_y_0"), val = tensor(false)]; + tensor value_49_cast_fp16 = transpose(perm = value_49_perm_0, x = var_2276_cast_fp16)[name = tensor("transpose_405")]; + tensor x_253_cast_fp16 = matmul(transpose_x = x_253_transpose_x_0, transpose_y = x_253_transpose_y_0, x = input_633_cast_fp16, y = value_49_cast_fp16)[name = tensor("x_253_cast_fp16")]; + tensor var_2307_perm_0 = const()[name = tensor("op_2307_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2309 = const()[name = tensor("op_2309"), val = tensor([1, -1, 512])]; + tensor var_2307_cast_fp16 = transpose(perm = var_2307_perm_0, x = x_253_cast_fp16)[name = tensor("transpose_400")]; + tensor input_635_cast_fp16 = reshape(shape = var_2309, x = var_2307_cast_fp16)[name = tensor("input_635_cast_fp16")]; + tensor e_encoders_23_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_23_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153342720)))]; + tensor e_encoders_23_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_23_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153867072)))]; + tensor linear_97_cast_fp16 = linear(bias = e_encoders_23_self_attn_linear_out_bias_to_fp16, weight = e_encoders_23_self_attn_linear_out_weight_to_fp16, x = input_635_cast_fp16)[name = tensor("linear_97_cast_fp16")]; + tensor input_637_cast_fp16 = add(x = linear_97_cast_fp16, y = fsmn_memory_49_cast_fp16)[name = tensor("input_637_cast_fp16")]; + tensor input_639_cast_fp16 = add(x = input_625_cast_fp16, y = input_637_cast_fp16)[name = tensor("input_639_cast_fp16")]; + tensor input_641_axes_0 = const()[name = tensor("input_641_axes_0"), val = tensor([-1])]; + tensor e_encoders_23_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_23_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153868160)))]; + tensor e_encoders_23_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_23_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153869248)))]; + tensor input_641_cast_fp16 = layer_norm(axes = input_641_axes_0, beta = e_encoders_23_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_23_norm2_weight_to_fp16, x = input_639_cast_fp16)[name = tensor("input_641_cast_fp16")]; + tensor e_encoders_23_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_23_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153870336)))]; + tensor e_encoders_23_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_23_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155967552)))]; + tensor linear_98_cast_fp16 = linear(bias = e_encoders_23_feed_forward_w_1_bias_to_fp16, weight = e_encoders_23_feed_forward_w_1_weight_to_fp16, x = input_641_cast_fp16)[name = tensor("linear_98_cast_fp16")]; + tensor input_645_cast_fp16 = relu(x = linear_98_cast_fp16)[name = tensor("input_645_cast_fp16")]; + tensor e_encoders_23_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_23_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155971712)))]; + tensor e_encoders_23_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_23_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158068928)))]; + tensor linear_99_cast_fp16 = linear(bias = e_encoders_23_feed_forward_w_2_bias_to_fp16, weight = e_encoders_23_feed_forward_w_2_weight_to_fp16, x = input_645_cast_fp16)[name = tensor("linear_99_cast_fp16")]; + tensor input_651_cast_fp16 = add(x = input_639_cast_fp16, y = linear_99_cast_fp16)[name = tensor("input_651_cast_fp16")]; + tensor x_255_axes_0 = const()[name = tensor("x_255_axes_0"), val = tensor([-1])]; + tensor e_encoders_24_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_24_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158070016)))]; + tensor e_encoders_24_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_24_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158071104)))]; + tensor x_255_cast_fp16 = layer_norm(axes = x_255_axes_0, beta = e_encoders_24_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_24_norm1_weight_to_fp16, x = input_651_cast_fp16)[name = tensor("x_255_cast_fp16")]; + tensor e_encoders_24_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_24_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158072192)))]; + tensor e_encoders_24_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_24_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159645120)))]; + tensor linear_100_cast_fp16 = linear(bias = e_encoders_24_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_24_self_attn_linear_q_k_v_weight_to_fp16, x = x_255_cast_fp16)[name = tensor("linear_100_cast_fp16")]; + tensor tile_25 = const()[name = tensor("tile_25"), val = tensor([512, 512, 512])]; + tensor var_2353_axis_0 = const()[name = tensor("op_2353_axis_0"), val = tensor(-1)]; + tensor var_2353_cast_fp16_0, tensor var_2353_cast_fp16_1, tensor var_2353_cast_fp16_2 = split(axis = var_2353_axis_0, split_sizes = tile_25, x = linear_100_cast_fp16)[name = tensor("op_2353_cast_fp16")]; + tensor concat_76x = const()[name = tensor("concat_76x"), val = tensor([1, -1, 4, 128])]; + tensor var_2358_cast_fp16 = reshape(shape = concat_76x, x = var_2353_cast_fp16_0)[name = tensor("op_2358_cast_fp16")]; + tensor concat_77x = const()[name = tensor("concat_77x"), val = tensor([1, -1, 4, 128])]; + tensor var_2361_cast_fp16 = reshape(shape = concat_77x, x = var_2353_cast_fp16_1)[name = tensor("op_2361_cast_fp16")]; + tensor concat_78x = const()[name = tensor("concat_78x"), val = tensor([1, -1, 4, 128])]; + tensor var_2364_cast_fp16 = reshape(shape = concat_78x, x = var_2353_cast_fp16_2)[name = tensor("op_2364_cast_fp16")]; + tensor value_51_perm_0 = const()[name = tensor("value_51_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_51_cast_fp16 = mul(x = var_2353_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_51_cast_fp16")]; + tensor input_653_perm_0 = const()[name = tensor("input_653_perm_0"), val = tensor([0, 2, 1])]; + tensor input_655_pad_0 = const()[name = tensor("input_655_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_655_mode_0 = const()[name = tensor("input_655_mode_0"), val = tensor("constant")]; + tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(0x0p+0)]; + tensor input_653_cast_fp16 = transpose(perm = input_653_perm_0, x = inputs_51_cast_fp16)[name = tensor("transpose_398")]; + tensor input_655_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_655_mode_0, pad = input_655_pad_0, x = input_653_cast_fp16)[name = tensor("input_655_cast_fp16")]; + tensor x_257_pad_type_0 = const()[name = tensor("x_257_pad_type_0"), val = tensor("valid")]; + tensor x_257_groups_0 = const()[name = tensor("x_257_groups_0"), val = tensor(512)]; + tensor x_257_strides_0 = const()[name = tensor("x_257_strides_0"), val = tensor([1])]; + tensor x_257_pad_0 = const()[name = tensor("x_257_pad_0"), val = tensor([0, 0])]; + tensor x_257_dilations_0 = const()[name = tensor("x_257_dilations_0"), val = tensor([1])]; + tensor e_encoders_24_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_24_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159648256)))]; + tensor x_257_cast_fp16 = conv(dilations = x_257_dilations_0, groups = x_257_groups_0, pad = x_257_pad_0, pad_type = x_257_pad_type_0, strides = x_257_strides_0, weight = e_encoders_24_self_attn_fsmn_block_weight_to_fp16, x = input_655_cast_fp16)[name = tensor("x_257_cast_fp16")]; + tensor x_259_perm_0 = const()[name = tensor("x_259_perm_0"), val = tensor([0, 2, 1])]; + tensor x_259_cast_fp16 = transpose(perm = x_259_perm_0, x = x_257_cast_fp16)[name = tensor("transpose_397")]; + tensor input_657_cast_fp16 = add(x = x_259_cast_fp16, y = inputs_51_cast_fp16)[name = tensor("input_657_cast_fp16")]; + tensor fsmn_memory_51_cast_fp16 = mul(x = input_657_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_51_cast_fp16")]; + tensor var_2383_to_fp16 = const()[name = tensor("op_2383_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_103_cast_fp16 = mul(x = var_2358_cast_fp16, y = var_2383_to_fp16)[name = tensor("q_h_103_cast_fp16")]; + tensor scores_101_transpose_x_0 = const()[name = tensor("scores_101_transpose_x_0"), val = tensor(false)]; + tensor scores_101_transpose_y_0 = const()[name = tensor("scores_101_transpose_y_0"), val = tensor(false)]; + tensor transpose_200_perm_0 = const()[name = tensor("transpose_200_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_201_perm_0 = const()[name = tensor("transpose_201_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_201 = transpose(perm = transpose_201_perm_0, x = var_2361_cast_fp16)[name = tensor("transpose_395")]; + tensor transpose_200 = transpose(perm = transpose_200_perm_0, x = q_h_103_cast_fp16)[name = tensor("transpose_396")]; + tensor scores_101_cast_fp16 = matmul(transpose_x = scores_101_transpose_x_0, transpose_y = scores_101_transpose_y_0, x = transpose_200, y = transpose_201)[name = tensor("scores_101_cast_fp16")]; + tensor scores_103_cast_fp16 = select(a = var_11_to_fp16, b = scores_101_cast_fp16, cond = mask_5)[name = tensor("scores_103_cast_fp16")]; + tensor var_2391_cast_fp16 = softmax(axis = var_20, x = scores_103_cast_fp16)[name = tensor("op_2391_cast_fp16")]; + tensor input_659_cast_fp16 = select(a = var_6_to_fp16, b = var_2391_cast_fp16, cond = mask_5)[name = tensor("input_659_cast_fp16")]; + tensor x_263_transpose_x_0 = const()[name = tensor("x_263_transpose_x_0"), val = tensor(false)]; + tensor x_263_transpose_y_0 = const()[name = tensor("x_263_transpose_y_0"), val = tensor(false)]; + tensor value_51_cast_fp16 = transpose(perm = value_51_perm_0, x = var_2364_cast_fp16)[name = tensor("transpose_399")]; + tensor x_263_cast_fp16 = matmul(transpose_x = x_263_transpose_x_0, transpose_y = x_263_transpose_y_0, x = input_659_cast_fp16, y = value_51_cast_fp16)[name = tensor("x_263_cast_fp16")]; + tensor var_2395_perm_0 = const()[name = tensor("op_2395_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2397 = const()[name = tensor("op_2397"), val = tensor([1, -1, 512])]; + tensor var_2395_cast_fp16 = transpose(perm = var_2395_perm_0, x = x_263_cast_fp16)[name = tensor("transpose_394")]; + tensor input_661_cast_fp16 = reshape(shape = var_2397, x = var_2395_cast_fp16)[name = tensor("input_661_cast_fp16")]; + tensor e_encoders_24_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_24_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159659584)))]; + tensor e_encoders_24_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_24_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160183936)))]; + tensor linear_101_cast_fp16 = linear(bias = e_encoders_24_self_attn_linear_out_bias_to_fp16, weight = e_encoders_24_self_attn_linear_out_weight_to_fp16, x = input_661_cast_fp16)[name = tensor("linear_101_cast_fp16")]; + tensor input_663_cast_fp16 = add(x = linear_101_cast_fp16, y = fsmn_memory_51_cast_fp16)[name = tensor("input_663_cast_fp16")]; + tensor input_665_cast_fp16 = add(x = input_651_cast_fp16, y = input_663_cast_fp16)[name = tensor("input_665_cast_fp16")]; + tensor input_667_axes_0 = const()[name = tensor("input_667_axes_0"), val = tensor([-1])]; + tensor e_encoders_24_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_24_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160185024)))]; + tensor e_encoders_24_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_24_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160186112)))]; + tensor input_667_cast_fp16 = layer_norm(axes = input_667_axes_0, beta = e_encoders_24_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_24_norm2_weight_to_fp16, x = input_665_cast_fp16)[name = tensor("input_667_cast_fp16")]; + tensor e_encoders_24_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_24_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160187200)))]; + tensor e_encoders_24_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_24_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162284416)))]; + tensor linear_102_cast_fp16 = linear(bias = e_encoders_24_feed_forward_w_1_bias_to_fp16, weight = e_encoders_24_feed_forward_w_1_weight_to_fp16, x = input_667_cast_fp16)[name = tensor("linear_102_cast_fp16")]; + tensor input_671_cast_fp16 = relu(x = linear_102_cast_fp16)[name = tensor("input_671_cast_fp16")]; + tensor e_encoders_24_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_24_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162288576)))]; + tensor e_encoders_24_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_24_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164385792)))]; + tensor linear_103_cast_fp16 = linear(bias = e_encoders_24_feed_forward_w_2_bias_to_fp16, weight = e_encoders_24_feed_forward_w_2_weight_to_fp16, x = input_671_cast_fp16)[name = tensor("linear_103_cast_fp16")]; + tensor input_677_cast_fp16 = add(x = input_665_cast_fp16, y = linear_103_cast_fp16)[name = tensor("input_677_cast_fp16")]; + tensor x_265_axes_0 = const()[name = tensor("x_265_axes_0"), val = tensor([-1])]; + tensor e_encoders_25_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_25_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164386880)))]; + tensor e_encoders_25_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_25_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164387968)))]; + tensor x_265_cast_fp16 = layer_norm(axes = x_265_axes_0, beta = e_encoders_25_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_25_norm1_weight_to_fp16, x = input_677_cast_fp16)[name = tensor("x_265_cast_fp16")]; + tensor e_encoders_25_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_25_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164389056)))]; + tensor e_encoders_25_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_25_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165961984)))]; + tensor linear_104_cast_fp16 = linear(bias = e_encoders_25_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_25_self_attn_linear_q_k_v_weight_to_fp16, x = x_265_cast_fp16)[name = tensor("linear_104_cast_fp16")]; + tensor tile_26 = const()[name = tensor("tile_26"), val = tensor([512, 512, 512])]; + tensor var_2441_axis_0 = const()[name = tensor("op_2441_axis_0"), val = tensor(-1)]; + tensor var_2441_cast_fp16_0, tensor var_2441_cast_fp16_1, tensor var_2441_cast_fp16_2 = split(axis = var_2441_axis_0, split_sizes = tile_26, x = linear_104_cast_fp16)[name = tensor("op_2441_cast_fp16")]; + tensor concat_79x = const()[name = tensor("concat_79x"), val = tensor([1, -1, 4, 128])]; + tensor var_2446_cast_fp16 = reshape(shape = concat_79x, x = var_2441_cast_fp16_0)[name = tensor("op_2446_cast_fp16")]; + tensor concat_80x = const()[name = tensor("concat_80x"), val = tensor([1, -1, 4, 128])]; + tensor var_2449_cast_fp16 = reshape(shape = concat_80x, x = var_2441_cast_fp16_1)[name = tensor("op_2449_cast_fp16")]; + tensor concat_81x = const()[name = tensor("concat_81x"), val = tensor([1, -1, 4, 128])]; + tensor var_2452_cast_fp16 = reshape(shape = concat_81x, x = var_2441_cast_fp16_2)[name = tensor("op_2452_cast_fp16")]; + tensor value_53_perm_0 = const()[name = tensor("value_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_53_cast_fp16 = mul(x = var_2441_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_53_cast_fp16")]; + tensor input_679_perm_0 = const()[name = tensor("input_679_perm_0"), val = tensor([0, 2, 1])]; + tensor input_681_pad_0 = const()[name = tensor("input_681_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_681_mode_0 = const()[name = tensor("input_681_mode_0"), val = tensor("constant")]; + tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(0x0p+0)]; + tensor input_679_cast_fp16 = transpose(perm = input_679_perm_0, x = inputs_53_cast_fp16)[name = tensor("transpose_392")]; + tensor input_681_cast_fp16 = pad(constant_val = const_61_to_fp16, mode = input_681_mode_0, pad = input_681_pad_0, x = input_679_cast_fp16)[name = tensor("input_681_cast_fp16")]; + tensor x_267_pad_type_0 = const()[name = tensor("x_267_pad_type_0"), val = tensor("valid")]; + tensor x_267_groups_0 = const()[name = tensor("x_267_groups_0"), val = tensor(512)]; + tensor x_267_strides_0 = const()[name = tensor("x_267_strides_0"), val = tensor([1])]; + tensor x_267_pad_0 = const()[name = tensor("x_267_pad_0"), val = tensor([0, 0])]; + tensor x_267_dilations_0 = const()[name = tensor("x_267_dilations_0"), val = tensor([1])]; + tensor e_encoders_25_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_25_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165965120)))]; + tensor x_267_cast_fp16 = conv(dilations = x_267_dilations_0, groups = x_267_groups_0, pad = x_267_pad_0, pad_type = x_267_pad_type_0, strides = x_267_strides_0, weight = e_encoders_25_self_attn_fsmn_block_weight_to_fp16, x = input_681_cast_fp16)[name = tensor("x_267_cast_fp16")]; + tensor x_269_perm_0 = const()[name = tensor("x_269_perm_0"), val = tensor([0, 2, 1])]; + tensor x_269_cast_fp16 = transpose(perm = x_269_perm_0, x = x_267_cast_fp16)[name = tensor("transpose_391")]; + tensor input_683_cast_fp16 = add(x = x_269_cast_fp16, y = inputs_53_cast_fp16)[name = tensor("input_683_cast_fp16")]; + tensor fsmn_memory_53_cast_fp16 = mul(x = input_683_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_53_cast_fp16")]; + tensor var_2471_to_fp16 = const()[name = tensor("op_2471_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_107_cast_fp16 = mul(x = var_2446_cast_fp16, y = var_2471_to_fp16)[name = tensor("q_h_107_cast_fp16")]; + tensor scores_105_transpose_x_0 = const()[name = tensor("scores_105_transpose_x_0"), val = tensor(false)]; + tensor scores_105_transpose_y_0 = const()[name = tensor("scores_105_transpose_y_0"), val = tensor(false)]; + tensor transpose_202_perm_0 = const()[name = tensor("transpose_202_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_203_perm_0 = const()[name = tensor("transpose_203_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_203 = transpose(perm = transpose_203_perm_0, x = var_2449_cast_fp16)[name = tensor("transpose_389")]; + tensor transpose_202 = transpose(perm = transpose_202_perm_0, x = q_h_107_cast_fp16)[name = tensor("transpose_390")]; + tensor scores_105_cast_fp16 = matmul(transpose_x = scores_105_transpose_x_0, transpose_y = scores_105_transpose_y_0, x = transpose_202, y = transpose_203)[name = tensor("scores_105_cast_fp16")]; + tensor scores_107_cast_fp16 = select(a = var_11_to_fp16, b = scores_105_cast_fp16, cond = mask_5)[name = tensor("scores_107_cast_fp16")]; + tensor var_2479_cast_fp16 = softmax(axis = var_20, x = scores_107_cast_fp16)[name = tensor("op_2479_cast_fp16")]; + tensor input_685_cast_fp16 = select(a = var_6_to_fp16, b = var_2479_cast_fp16, cond = mask_5)[name = tensor("input_685_cast_fp16")]; + tensor x_273_transpose_x_0 = const()[name = tensor("x_273_transpose_x_0"), val = tensor(false)]; + tensor x_273_transpose_y_0 = const()[name = tensor("x_273_transpose_y_0"), val = tensor(false)]; + tensor value_53_cast_fp16 = transpose(perm = value_53_perm_0, x = var_2452_cast_fp16)[name = tensor("transpose_393")]; + tensor x_273_cast_fp16 = matmul(transpose_x = x_273_transpose_x_0, transpose_y = x_273_transpose_y_0, x = input_685_cast_fp16, y = value_53_cast_fp16)[name = tensor("x_273_cast_fp16")]; + tensor var_2483_perm_0 = const()[name = tensor("op_2483_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2485 = const()[name = tensor("op_2485"), val = tensor([1, -1, 512])]; + tensor var_2483_cast_fp16 = transpose(perm = var_2483_perm_0, x = x_273_cast_fp16)[name = tensor("transpose_388")]; + tensor input_687_cast_fp16 = reshape(shape = var_2485, x = var_2483_cast_fp16)[name = tensor("input_687_cast_fp16")]; + tensor e_encoders_25_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_25_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165976448)))]; + tensor e_encoders_25_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_25_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166500800)))]; + tensor linear_105_cast_fp16 = linear(bias = e_encoders_25_self_attn_linear_out_bias_to_fp16, weight = e_encoders_25_self_attn_linear_out_weight_to_fp16, x = input_687_cast_fp16)[name = tensor("linear_105_cast_fp16")]; + tensor input_689_cast_fp16 = add(x = linear_105_cast_fp16, y = fsmn_memory_53_cast_fp16)[name = tensor("input_689_cast_fp16")]; + tensor input_691_cast_fp16 = add(x = input_677_cast_fp16, y = input_689_cast_fp16)[name = tensor("input_691_cast_fp16")]; + tensor input_693_axes_0 = const()[name = tensor("input_693_axes_0"), val = tensor([-1])]; + tensor e_encoders_25_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_25_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166501888)))]; + tensor e_encoders_25_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_25_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166502976)))]; + tensor input_693_cast_fp16 = layer_norm(axes = input_693_axes_0, beta = e_encoders_25_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_25_norm2_weight_to_fp16, x = input_691_cast_fp16)[name = tensor("input_693_cast_fp16")]; + tensor e_encoders_25_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_25_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166504064)))]; + tensor e_encoders_25_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_25_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168601280)))]; + tensor linear_106_cast_fp16 = linear(bias = e_encoders_25_feed_forward_w_1_bias_to_fp16, weight = e_encoders_25_feed_forward_w_1_weight_to_fp16, x = input_693_cast_fp16)[name = tensor("linear_106_cast_fp16")]; + tensor input_697_cast_fp16 = relu(x = linear_106_cast_fp16)[name = tensor("input_697_cast_fp16")]; + tensor e_encoders_25_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_25_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168605440)))]; + tensor e_encoders_25_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_25_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170702656)))]; + tensor linear_107_cast_fp16 = linear(bias = e_encoders_25_feed_forward_w_2_bias_to_fp16, weight = e_encoders_25_feed_forward_w_2_weight_to_fp16, x = input_697_cast_fp16)[name = tensor("linear_107_cast_fp16")]; + tensor input_703_cast_fp16 = add(x = input_691_cast_fp16, y = linear_107_cast_fp16)[name = tensor("input_703_cast_fp16")]; + tensor x_275_axes_0 = const()[name = tensor("x_275_axes_0"), val = tensor([-1])]; + tensor e_encoders_26_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_26_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170703744)))]; + tensor e_encoders_26_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_26_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170704832)))]; + tensor x_275_cast_fp16 = layer_norm(axes = x_275_axes_0, beta = e_encoders_26_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_26_norm1_weight_to_fp16, x = input_703_cast_fp16)[name = tensor("x_275_cast_fp16")]; + tensor e_encoders_26_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_26_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170705920)))]; + tensor e_encoders_26_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_26_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172278848)))]; + tensor linear_108_cast_fp16 = linear(bias = e_encoders_26_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_26_self_attn_linear_q_k_v_weight_to_fp16, x = x_275_cast_fp16)[name = tensor("linear_108_cast_fp16")]; + tensor tile_27 = const()[name = tensor("tile_27"), val = tensor([512, 512, 512])]; + tensor var_2529_axis_0 = const()[name = tensor("op_2529_axis_0"), val = tensor(-1)]; + tensor var_2529_cast_fp16_0, tensor var_2529_cast_fp16_1, tensor var_2529_cast_fp16_2 = split(axis = var_2529_axis_0, split_sizes = tile_27, x = linear_108_cast_fp16)[name = tensor("op_2529_cast_fp16")]; + tensor concat_82x = const()[name = tensor("concat_82x"), val = tensor([1, -1, 4, 128])]; + tensor var_2534_cast_fp16 = reshape(shape = concat_82x, x = var_2529_cast_fp16_0)[name = tensor("op_2534_cast_fp16")]; + tensor concat_83x = const()[name = tensor("concat_83x"), val = tensor([1, -1, 4, 128])]; + tensor var_2537_cast_fp16 = reshape(shape = concat_83x, x = var_2529_cast_fp16_1)[name = tensor("op_2537_cast_fp16")]; + tensor concat_84x = const()[name = tensor("concat_84x"), val = tensor([1, -1, 4, 128])]; + tensor var_2540_cast_fp16 = reshape(shape = concat_84x, x = var_2529_cast_fp16_2)[name = tensor("op_2540_cast_fp16")]; + tensor value_55_perm_0 = const()[name = tensor("value_55_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_55_cast_fp16 = mul(x = var_2529_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_55_cast_fp16")]; + tensor input_705_perm_0 = const()[name = tensor("input_705_perm_0"), val = tensor([0, 2, 1])]; + tensor input_707_pad_0 = const()[name = tensor("input_707_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_707_mode_0 = const()[name = tensor("input_707_mode_0"), val = tensor("constant")]; + tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(0x0p+0)]; + tensor input_705_cast_fp16 = transpose(perm = input_705_perm_0, x = inputs_55_cast_fp16)[name = tensor("transpose_386")]; + tensor input_707_cast_fp16 = pad(constant_val = const_63_to_fp16, mode = input_707_mode_0, pad = input_707_pad_0, x = input_705_cast_fp16)[name = tensor("input_707_cast_fp16")]; + tensor x_277_pad_type_0 = const()[name = tensor("x_277_pad_type_0"), val = tensor("valid")]; + tensor x_277_groups_0 = const()[name = tensor("x_277_groups_0"), val = tensor(512)]; + tensor x_277_strides_0 = const()[name = tensor("x_277_strides_0"), val = tensor([1])]; + tensor x_277_pad_0 = const()[name = tensor("x_277_pad_0"), val = tensor([0, 0])]; + tensor x_277_dilations_0 = const()[name = tensor("x_277_dilations_0"), val = tensor([1])]; + tensor e_encoders_26_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_26_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172281984)))]; + tensor x_277_cast_fp16 = conv(dilations = x_277_dilations_0, groups = x_277_groups_0, pad = x_277_pad_0, pad_type = x_277_pad_type_0, strides = x_277_strides_0, weight = e_encoders_26_self_attn_fsmn_block_weight_to_fp16, x = input_707_cast_fp16)[name = tensor("x_277_cast_fp16")]; + tensor x_279_perm_0 = const()[name = tensor("x_279_perm_0"), val = tensor([0, 2, 1])]; + tensor x_279_cast_fp16 = transpose(perm = x_279_perm_0, x = x_277_cast_fp16)[name = tensor("transpose_385")]; + tensor input_709_cast_fp16 = add(x = x_279_cast_fp16, y = inputs_55_cast_fp16)[name = tensor("input_709_cast_fp16")]; + tensor fsmn_memory_55_cast_fp16 = mul(x = input_709_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_55_cast_fp16")]; + tensor var_2559_to_fp16 = const()[name = tensor("op_2559_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_111_cast_fp16 = mul(x = var_2534_cast_fp16, y = var_2559_to_fp16)[name = tensor("q_h_111_cast_fp16")]; + tensor scores_109_transpose_x_0 = const()[name = tensor("scores_109_transpose_x_0"), val = tensor(false)]; + tensor scores_109_transpose_y_0 = const()[name = tensor("scores_109_transpose_y_0"), val = tensor(false)]; + tensor transpose_204_perm_0 = const()[name = tensor("transpose_204_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_205_perm_0 = const()[name = tensor("transpose_205_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_205 = transpose(perm = transpose_205_perm_0, x = var_2537_cast_fp16)[name = tensor("transpose_383")]; + tensor transpose_204 = transpose(perm = transpose_204_perm_0, x = q_h_111_cast_fp16)[name = tensor("transpose_384")]; + tensor scores_109_cast_fp16 = matmul(transpose_x = scores_109_transpose_x_0, transpose_y = scores_109_transpose_y_0, x = transpose_204, y = transpose_205)[name = tensor("scores_109_cast_fp16")]; + tensor scores_111_cast_fp16 = select(a = var_11_to_fp16, b = scores_109_cast_fp16, cond = mask_5)[name = tensor("scores_111_cast_fp16")]; + tensor var_2567_cast_fp16 = softmax(axis = var_20, x = scores_111_cast_fp16)[name = tensor("op_2567_cast_fp16")]; + tensor input_711_cast_fp16 = select(a = var_6_to_fp16, b = var_2567_cast_fp16, cond = mask_5)[name = tensor("input_711_cast_fp16")]; + tensor x_283_transpose_x_0 = const()[name = tensor("x_283_transpose_x_0"), val = tensor(false)]; + tensor x_283_transpose_y_0 = const()[name = tensor("x_283_transpose_y_0"), val = tensor(false)]; + tensor value_55_cast_fp16 = transpose(perm = value_55_perm_0, x = var_2540_cast_fp16)[name = tensor("transpose_387")]; + tensor x_283_cast_fp16 = matmul(transpose_x = x_283_transpose_x_0, transpose_y = x_283_transpose_y_0, x = input_711_cast_fp16, y = value_55_cast_fp16)[name = tensor("x_283_cast_fp16")]; + tensor var_2571_perm_0 = const()[name = tensor("op_2571_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2573 = const()[name = tensor("op_2573"), val = tensor([1, -1, 512])]; + tensor var_2571_cast_fp16 = transpose(perm = var_2571_perm_0, x = x_283_cast_fp16)[name = tensor("transpose_382")]; + tensor input_713_cast_fp16 = reshape(shape = var_2573, x = var_2571_cast_fp16)[name = tensor("input_713_cast_fp16")]; + tensor e_encoders_26_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_26_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172293312)))]; + tensor e_encoders_26_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_26_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172817664)))]; + tensor linear_109_cast_fp16 = linear(bias = e_encoders_26_self_attn_linear_out_bias_to_fp16, weight = e_encoders_26_self_attn_linear_out_weight_to_fp16, x = input_713_cast_fp16)[name = tensor("linear_109_cast_fp16")]; + tensor input_715_cast_fp16 = add(x = linear_109_cast_fp16, y = fsmn_memory_55_cast_fp16)[name = tensor("input_715_cast_fp16")]; + tensor input_717_cast_fp16 = add(x = input_703_cast_fp16, y = input_715_cast_fp16)[name = tensor("input_717_cast_fp16")]; + tensor input_719_axes_0 = const()[name = tensor("input_719_axes_0"), val = tensor([-1])]; + tensor e_encoders_26_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_26_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172818752)))]; + tensor e_encoders_26_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_26_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172819840)))]; + tensor input_719_cast_fp16 = layer_norm(axes = input_719_axes_0, beta = e_encoders_26_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_26_norm2_weight_to_fp16, x = input_717_cast_fp16)[name = tensor("input_719_cast_fp16")]; + tensor e_encoders_26_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_26_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172820928)))]; + tensor e_encoders_26_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_26_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174918144)))]; + tensor linear_110_cast_fp16 = linear(bias = e_encoders_26_feed_forward_w_1_bias_to_fp16, weight = e_encoders_26_feed_forward_w_1_weight_to_fp16, x = input_719_cast_fp16)[name = tensor("linear_110_cast_fp16")]; + tensor input_723_cast_fp16 = relu(x = linear_110_cast_fp16)[name = tensor("input_723_cast_fp16")]; + tensor e_encoders_26_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_26_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174922304)))]; + tensor e_encoders_26_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_26_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177019520)))]; + tensor linear_111_cast_fp16 = linear(bias = e_encoders_26_feed_forward_w_2_bias_to_fp16, weight = e_encoders_26_feed_forward_w_2_weight_to_fp16, x = input_723_cast_fp16)[name = tensor("linear_111_cast_fp16")]; + tensor input_729_cast_fp16 = add(x = input_717_cast_fp16, y = linear_111_cast_fp16)[name = tensor("input_729_cast_fp16")]; + tensor x_285_axes_0 = const()[name = tensor("x_285_axes_0"), val = tensor([-1])]; + tensor e_encoders_27_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_27_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177020608)))]; + tensor e_encoders_27_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_27_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177021696)))]; + tensor x_285_cast_fp16 = layer_norm(axes = x_285_axes_0, beta = e_encoders_27_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_27_norm1_weight_to_fp16, x = input_729_cast_fp16)[name = tensor("x_285_cast_fp16")]; + tensor e_encoders_27_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_27_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177022784)))]; + tensor e_encoders_27_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_27_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178595712)))]; + tensor linear_112_cast_fp16 = linear(bias = e_encoders_27_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_27_self_attn_linear_q_k_v_weight_to_fp16, x = x_285_cast_fp16)[name = tensor("linear_112_cast_fp16")]; + tensor tile_28 = const()[name = tensor("tile_28"), val = tensor([512, 512, 512])]; + tensor var_2617_axis_0 = const()[name = tensor("op_2617_axis_0"), val = tensor(-1)]; + tensor var_2617_cast_fp16_0, tensor var_2617_cast_fp16_1, tensor var_2617_cast_fp16_2 = split(axis = var_2617_axis_0, split_sizes = tile_28, x = linear_112_cast_fp16)[name = tensor("op_2617_cast_fp16")]; + tensor concat_85x = const()[name = tensor("concat_85x"), val = tensor([1, -1, 4, 128])]; + tensor var_2622_cast_fp16 = reshape(shape = concat_85x, x = var_2617_cast_fp16_0)[name = tensor("op_2622_cast_fp16")]; + tensor concat_86x = const()[name = tensor("concat_86x"), val = tensor([1, -1, 4, 128])]; + tensor var_2625_cast_fp16 = reshape(shape = concat_86x, x = var_2617_cast_fp16_1)[name = tensor("op_2625_cast_fp16")]; + tensor concat_87x = const()[name = tensor("concat_87x"), val = tensor([1, -1, 4, 128])]; + tensor var_2628_cast_fp16 = reshape(shape = concat_87x, x = var_2617_cast_fp16_2)[name = tensor("op_2628_cast_fp16")]; + tensor value_57_perm_0 = const()[name = tensor("value_57_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_57_cast_fp16 = mul(x = var_2617_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_57_cast_fp16")]; + tensor input_731_perm_0 = const()[name = tensor("input_731_perm_0"), val = tensor([0, 2, 1])]; + tensor input_733_pad_0 = const()[name = tensor("input_733_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_733_mode_0 = const()[name = tensor("input_733_mode_0"), val = tensor("constant")]; + tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(0x0p+0)]; + tensor input_731_cast_fp16 = transpose(perm = input_731_perm_0, x = inputs_57_cast_fp16)[name = tensor("transpose_380")]; + tensor input_733_cast_fp16 = pad(constant_val = const_65_to_fp16, mode = input_733_mode_0, pad = input_733_pad_0, x = input_731_cast_fp16)[name = tensor("input_733_cast_fp16")]; + tensor x_287_pad_type_0 = const()[name = tensor("x_287_pad_type_0"), val = tensor("valid")]; + tensor x_287_groups_0 = const()[name = tensor("x_287_groups_0"), val = tensor(512)]; + tensor x_287_strides_0 = const()[name = tensor("x_287_strides_0"), val = tensor([1])]; + tensor x_287_pad_0 = const()[name = tensor("x_287_pad_0"), val = tensor([0, 0])]; + tensor x_287_dilations_0 = const()[name = tensor("x_287_dilations_0"), val = tensor([1])]; + tensor e_encoders_27_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_27_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178598848)))]; + tensor x_287_cast_fp16 = conv(dilations = x_287_dilations_0, groups = x_287_groups_0, pad = x_287_pad_0, pad_type = x_287_pad_type_0, strides = x_287_strides_0, weight = e_encoders_27_self_attn_fsmn_block_weight_to_fp16, x = input_733_cast_fp16)[name = tensor("x_287_cast_fp16")]; + tensor x_289_perm_0 = const()[name = tensor("x_289_perm_0"), val = tensor([0, 2, 1])]; + tensor x_289_cast_fp16 = transpose(perm = x_289_perm_0, x = x_287_cast_fp16)[name = tensor("transpose_379")]; + tensor input_735_cast_fp16 = add(x = x_289_cast_fp16, y = inputs_57_cast_fp16)[name = tensor("input_735_cast_fp16")]; + tensor fsmn_memory_57_cast_fp16 = mul(x = input_735_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_57_cast_fp16")]; + tensor var_2647_to_fp16 = const()[name = tensor("op_2647_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_115_cast_fp16 = mul(x = var_2622_cast_fp16, y = var_2647_to_fp16)[name = tensor("q_h_115_cast_fp16")]; + tensor scores_113_transpose_x_0 = const()[name = tensor("scores_113_transpose_x_0"), val = tensor(false)]; + tensor scores_113_transpose_y_0 = const()[name = tensor("scores_113_transpose_y_0"), val = tensor(false)]; + tensor transpose_206_perm_0 = const()[name = tensor("transpose_206_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_207_perm_0 = const()[name = tensor("transpose_207_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_207 = transpose(perm = transpose_207_perm_0, x = var_2625_cast_fp16)[name = tensor("transpose_377")]; + tensor transpose_206 = transpose(perm = transpose_206_perm_0, x = q_h_115_cast_fp16)[name = tensor("transpose_378")]; + tensor scores_113_cast_fp16 = matmul(transpose_x = scores_113_transpose_x_0, transpose_y = scores_113_transpose_y_0, x = transpose_206, y = transpose_207)[name = tensor("scores_113_cast_fp16")]; + tensor scores_115_cast_fp16 = select(a = var_11_to_fp16, b = scores_113_cast_fp16, cond = mask_5)[name = tensor("scores_115_cast_fp16")]; + tensor var_2655_cast_fp16 = softmax(axis = var_20, x = scores_115_cast_fp16)[name = tensor("op_2655_cast_fp16")]; + tensor input_737_cast_fp16 = select(a = var_6_to_fp16, b = var_2655_cast_fp16, cond = mask_5)[name = tensor("input_737_cast_fp16")]; + tensor x_293_transpose_x_0 = const()[name = tensor("x_293_transpose_x_0"), val = tensor(false)]; + tensor x_293_transpose_y_0 = const()[name = tensor("x_293_transpose_y_0"), val = tensor(false)]; + tensor value_57_cast_fp16 = transpose(perm = value_57_perm_0, x = var_2628_cast_fp16)[name = tensor("transpose_381")]; + tensor x_293_cast_fp16 = matmul(transpose_x = x_293_transpose_x_0, transpose_y = x_293_transpose_y_0, x = input_737_cast_fp16, y = value_57_cast_fp16)[name = tensor("x_293_cast_fp16")]; + tensor var_2659_perm_0 = const()[name = tensor("op_2659_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2661 = const()[name = tensor("op_2661"), val = tensor([1, -1, 512])]; + tensor var_2659_cast_fp16 = transpose(perm = var_2659_perm_0, x = x_293_cast_fp16)[name = tensor("transpose_376")]; + tensor input_739_cast_fp16 = reshape(shape = var_2661, x = var_2659_cast_fp16)[name = tensor("input_739_cast_fp16")]; + tensor e_encoders_27_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_27_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178610176)))]; + tensor e_encoders_27_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_27_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179134528)))]; + tensor linear_113_cast_fp16 = linear(bias = e_encoders_27_self_attn_linear_out_bias_to_fp16, weight = e_encoders_27_self_attn_linear_out_weight_to_fp16, x = input_739_cast_fp16)[name = tensor("linear_113_cast_fp16")]; + tensor input_741_cast_fp16 = add(x = linear_113_cast_fp16, y = fsmn_memory_57_cast_fp16)[name = tensor("input_741_cast_fp16")]; + tensor input_743_cast_fp16 = add(x = input_729_cast_fp16, y = input_741_cast_fp16)[name = tensor("input_743_cast_fp16")]; + tensor input_745_axes_0 = const()[name = tensor("input_745_axes_0"), val = tensor([-1])]; + tensor e_encoders_27_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_27_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179135616)))]; + tensor e_encoders_27_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_27_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179136704)))]; + tensor input_745_cast_fp16 = layer_norm(axes = input_745_axes_0, beta = e_encoders_27_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_27_norm2_weight_to_fp16, x = input_743_cast_fp16)[name = tensor("input_745_cast_fp16")]; + tensor e_encoders_27_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_27_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179137792)))]; + tensor e_encoders_27_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_27_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181235008)))]; + tensor linear_114_cast_fp16 = linear(bias = e_encoders_27_feed_forward_w_1_bias_to_fp16, weight = e_encoders_27_feed_forward_w_1_weight_to_fp16, x = input_745_cast_fp16)[name = tensor("linear_114_cast_fp16")]; + tensor input_749_cast_fp16 = relu(x = linear_114_cast_fp16)[name = tensor("input_749_cast_fp16")]; + tensor e_encoders_27_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_27_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181239168)))]; + tensor e_encoders_27_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_27_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183336384)))]; + tensor linear_115_cast_fp16 = linear(bias = e_encoders_27_feed_forward_w_2_bias_to_fp16, weight = e_encoders_27_feed_forward_w_2_weight_to_fp16, x = input_749_cast_fp16)[name = tensor("linear_115_cast_fp16")]; + tensor input_755_cast_fp16 = add(x = input_743_cast_fp16, y = linear_115_cast_fp16)[name = tensor("input_755_cast_fp16")]; + tensor x_295_axes_0 = const()[name = tensor("x_295_axes_0"), val = tensor([-1])]; + tensor e_encoders_28_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_28_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183337472)))]; + tensor e_encoders_28_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_28_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183338560)))]; + tensor x_295_cast_fp16 = layer_norm(axes = x_295_axes_0, beta = e_encoders_28_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_28_norm1_weight_to_fp16, x = input_755_cast_fp16)[name = tensor("x_295_cast_fp16")]; + tensor e_encoders_28_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_28_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183339648)))]; + tensor e_encoders_28_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_28_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184912576)))]; + tensor linear_116_cast_fp16 = linear(bias = e_encoders_28_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_28_self_attn_linear_q_k_v_weight_to_fp16, x = x_295_cast_fp16)[name = tensor("linear_116_cast_fp16")]; + tensor tile_29 = const()[name = tensor("tile_29"), val = tensor([512, 512, 512])]; + tensor var_2705_axis_0 = const()[name = tensor("op_2705_axis_0"), val = tensor(-1)]; + tensor var_2705_cast_fp16_0, tensor var_2705_cast_fp16_1, tensor var_2705_cast_fp16_2 = split(axis = var_2705_axis_0, split_sizes = tile_29, x = linear_116_cast_fp16)[name = tensor("op_2705_cast_fp16")]; + tensor concat_88x = const()[name = tensor("concat_88x"), val = tensor([1, -1, 4, 128])]; + tensor var_2710_cast_fp16 = reshape(shape = concat_88x, x = var_2705_cast_fp16_0)[name = tensor("op_2710_cast_fp16")]; + tensor concat_89x = const()[name = tensor("concat_89x"), val = tensor([1, -1, 4, 128])]; + tensor var_2713_cast_fp16 = reshape(shape = concat_89x, x = var_2705_cast_fp16_1)[name = tensor("op_2713_cast_fp16")]; + tensor concat_90x = const()[name = tensor("concat_90x"), val = tensor([1, -1, 4, 128])]; + tensor var_2716_cast_fp16 = reshape(shape = concat_90x, x = var_2705_cast_fp16_2)[name = tensor("op_2716_cast_fp16")]; + tensor value_59_perm_0 = const()[name = tensor("value_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_59_cast_fp16 = mul(x = var_2705_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_59_cast_fp16")]; + tensor input_757_perm_0 = const()[name = tensor("input_757_perm_0"), val = tensor([0, 2, 1])]; + tensor input_759_pad_0 = const()[name = tensor("input_759_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_759_mode_0 = const()[name = tensor("input_759_mode_0"), val = tensor("constant")]; + tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(0x0p+0)]; + tensor input_757_cast_fp16 = transpose(perm = input_757_perm_0, x = inputs_59_cast_fp16)[name = tensor("transpose_374")]; + tensor input_759_cast_fp16 = pad(constant_val = const_67_to_fp16, mode = input_759_mode_0, pad = input_759_pad_0, x = input_757_cast_fp16)[name = tensor("input_759_cast_fp16")]; + tensor x_297_pad_type_0 = const()[name = tensor("x_297_pad_type_0"), val = tensor("valid")]; + tensor x_297_groups_0 = const()[name = tensor("x_297_groups_0"), val = tensor(512)]; + tensor x_297_strides_0 = const()[name = tensor("x_297_strides_0"), val = tensor([1])]; + tensor x_297_pad_0 = const()[name = tensor("x_297_pad_0"), val = tensor([0, 0])]; + tensor x_297_dilations_0 = const()[name = tensor("x_297_dilations_0"), val = tensor([1])]; + tensor e_encoders_28_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_28_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184915712)))]; + tensor x_297_cast_fp16 = conv(dilations = x_297_dilations_0, groups = x_297_groups_0, pad = x_297_pad_0, pad_type = x_297_pad_type_0, strides = x_297_strides_0, weight = e_encoders_28_self_attn_fsmn_block_weight_to_fp16, x = input_759_cast_fp16)[name = tensor("x_297_cast_fp16")]; + tensor x_299_perm_0 = const()[name = tensor("x_299_perm_0"), val = tensor([0, 2, 1])]; + tensor x_299_cast_fp16 = transpose(perm = x_299_perm_0, x = x_297_cast_fp16)[name = tensor("transpose_373")]; + tensor input_761_cast_fp16 = add(x = x_299_cast_fp16, y = inputs_59_cast_fp16)[name = tensor("input_761_cast_fp16")]; + tensor fsmn_memory_59_cast_fp16 = mul(x = input_761_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_59_cast_fp16")]; + tensor var_2735_to_fp16 = const()[name = tensor("op_2735_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_119_cast_fp16 = mul(x = var_2710_cast_fp16, y = var_2735_to_fp16)[name = tensor("q_h_119_cast_fp16")]; + tensor scores_117_transpose_x_0 = const()[name = tensor("scores_117_transpose_x_0"), val = tensor(false)]; + tensor scores_117_transpose_y_0 = const()[name = tensor("scores_117_transpose_y_0"), val = tensor(false)]; + tensor transpose_208_perm_0 = const()[name = tensor("transpose_208_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_209_perm_0 = const()[name = tensor("transpose_209_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_209 = transpose(perm = transpose_209_perm_0, x = var_2713_cast_fp16)[name = tensor("transpose_371")]; + tensor transpose_208 = transpose(perm = transpose_208_perm_0, x = q_h_119_cast_fp16)[name = tensor("transpose_372")]; + tensor scores_117_cast_fp16 = matmul(transpose_x = scores_117_transpose_x_0, transpose_y = scores_117_transpose_y_0, x = transpose_208, y = transpose_209)[name = tensor("scores_117_cast_fp16")]; + tensor scores_119_cast_fp16 = select(a = var_11_to_fp16, b = scores_117_cast_fp16, cond = mask_5)[name = tensor("scores_119_cast_fp16")]; + tensor var_2743_cast_fp16 = softmax(axis = var_20, x = scores_119_cast_fp16)[name = tensor("op_2743_cast_fp16")]; + tensor input_763_cast_fp16 = select(a = var_6_to_fp16, b = var_2743_cast_fp16, cond = mask_5)[name = tensor("input_763_cast_fp16")]; + tensor x_303_transpose_x_0 = const()[name = tensor("x_303_transpose_x_0"), val = tensor(false)]; + tensor x_303_transpose_y_0 = const()[name = tensor("x_303_transpose_y_0"), val = tensor(false)]; + tensor value_59_cast_fp16 = transpose(perm = value_59_perm_0, x = var_2716_cast_fp16)[name = tensor("transpose_375")]; + tensor x_303_cast_fp16 = matmul(transpose_x = x_303_transpose_x_0, transpose_y = x_303_transpose_y_0, x = input_763_cast_fp16, y = value_59_cast_fp16)[name = tensor("x_303_cast_fp16")]; + tensor var_2747_perm_0 = const()[name = tensor("op_2747_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2749 = const()[name = tensor("op_2749"), val = tensor([1, -1, 512])]; + tensor var_2747_cast_fp16 = transpose(perm = var_2747_perm_0, x = x_303_cast_fp16)[name = tensor("transpose_370")]; + tensor input_765_cast_fp16 = reshape(shape = var_2749, x = var_2747_cast_fp16)[name = tensor("input_765_cast_fp16")]; + tensor e_encoders_28_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_28_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184927040)))]; + tensor e_encoders_28_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_28_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185451392)))]; + tensor linear_117_cast_fp16 = linear(bias = e_encoders_28_self_attn_linear_out_bias_to_fp16, weight = e_encoders_28_self_attn_linear_out_weight_to_fp16, x = input_765_cast_fp16)[name = tensor("linear_117_cast_fp16")]; + tensor input_767_cast_fp16 = add(x = linear_117_cast_fp16, y = fsmn_memory_59_cast_fp16)[name = tensor("input_767_cast_fp16")]; + tensor input_769_cast_fp16 = add(x = input_755_cast_fp16, y = input_767_cast_fp16)[name = tensor("input_769_cast_fp16")]; + tensor input_771_axes_0 = const()[name = tensor("input_771_axes_0"), val = tensor([-1])]; + tensor e_encoders_28_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_28_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185452480)))]; + tensor e_encoders_28_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_28_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185453568)))]; + tensor input_771_cast_fp16 = layer_norm(axes = input_771_axes_0, beta = e_encoders_28_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_28_norm2_weight_to_fp16, x = input_769_cast_fp16)[name = tensor("input_771_cast_fp16")]; + tensor e_encoders_28_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_28_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185454656)))]; + tensor e_encoders_28_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_28_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187551872)))]; + tensor linear_118_cast_fp16 = linear(bias = e_encoders_28_feed_forward_w_1_bias_to_fp16, weight = e_encoders_28_feed_forward_w_1_weight_to_fp16, x = input_771_cast_fp16)[name = tensor("linear_118_cast_fp16")]; + tensor input_775_cast_fp16 = relu(x = linear_118_cast_fp16)[name = tensor("input_775_cast_fp16")]; + tensor e_encoders_28_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_28_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187556032)))]; + tensor e_encoders_28_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_28_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189653248)))]; + tensor linear_119_cast_fp16 = linear(bias = e_encoders_28_feed_forward_w_2_bias_to_fp16, weight = e_encoders_28_feed_forward_w_2_weight_to_fp16, x = input_775_cast_fp16)[name = tensor("linear_119_cast_fp16")]; + tensor input_781_cast_fp16 = add(x = input_769_cast_fp16, y = linear_119_cast_fp16)[name = tensor("input_781_cast_fp16")]; + tensor x_305_axes_0 = const()[name = tensor("x_305_axes_0"), val = tensor([-1])]; + tensor e_encoders_29_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_29_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189654336)))]; + tensor e_encoders_29_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_29_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189655424)))]; + tensor x_305_cast_fp16 = layer_norm(axes = x_305_axes_0, beta = e_encoders_29_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_29_norm1_weight_to_fp16, x = input_781_cast_fp16)[name = tensor("x_305_cast_fp16")]; + tensor e_encoders_29_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_29_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189656512)))]; + tensor e_encoders_29_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_29_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191229440)))]; + tensor linear_120_cast_fp16 = linear(bias = e_encoders_29_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_29_self_attn_linear_q_k_v_weight_to_fp16, x = x_305_cast_fp16)[name = tensor("linear_120_cast_fp16")]; + tensor tile_30 = const()[name = tensor("tile_30"), val = tensor([512, 512, 512])]; + tensor var_2793_axis_0 = const()[name = tensor("op_2793_axis_0"), val = tensor(-1)]; + tensor var_2793_cast_fp16_0, tensor var_2793_cast_fp16_1, tensor var_2793_cast_fp16_2 = split(axis = var_2793_axis_0, split_sizes = tile_30, x = linear_120_cast_fp16)[name = tensor("op_2793_cast_fp16")]; + tensor concat_91x = const()[name = tensor("concat_91x"), val = tensor([1, -1, 4, 128])]; + tensor var_2798_cast_fp16 = reshape(shape = concat_91x, x = var_2793_cast_fp16_0)[name = tensor("op_2798_cast_fp16")]; + tensor concat_92x = const()[name = tensor("concat_92x"), val = tensor([1, -1, 4, 128])]; + tensor var_2801_cast_fp16 = reshape(shape = concat_92x, x = var_2793_cast_fp16_1)[name = tensor("op_2801_cast_fp16")]; + tensor concat_93x = const()[name = tensor("concat_93x"), val = tensor([1, -1, 4, 128])]; + tensor var_2804_cast_fp16 = reshape(shape = concat_93x, x = var_2793_cast_fp16_2)[name = tensor("op_2804_cast_fp16")]; + tensor value_61_perm_0 = const()[name = tensor("value_61_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_61_cast_fp16 = mul(x = var_2793_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_61_cast_fp16")]; + tensor input_783_perm_0 = const()[name = tensor("input_783_perm_0"), val = tensor([0, 2, 1])]; + tensor input_785_pad_0 = const()[name = tensor("input_785_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_785_mode_0 = const()[name = tensor("input_785_mode_0"), val = tensor("constant")]; + tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(0x0p+0)]; + tensor input_783_cast_fp16 = transpose(perm = input_783_perm_0, x = inputs_61_cast_fp16)[name = tensor("transpose_368")]; + tensor input_785_cast_fp16 = pad(constant_val = const_69_to_fp16, mode = input_785_mode_0, pad = input_785_pad_0, x = input_783_cast_fp16)[name = tensor("input_785_cast_fp16")]; + tensor x_307_pad_type_0 = const()[name = tensor("x_307_pad_type_0"), val = tensor("valid")]; + tensor x_307_groups_0 = const()[name = tensor("x_307_groups_0"), val = tensor(512)]; + tensor x_307_strides_0 = const()[name = tensor("x_307_strides_0"), val = tensor([1])]; + tensor x_307_pad_0 = const()[name = tensor("x_307_pad_0"), val = tensor([0, 0])]; + tensor x_307_dilations_0 = const()[name = tensor("x_307_dilations_0"), val = tensor([1])]; + tensor e_encoders_29_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_29_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191232576)))]; + tensor x_307_cast_fp16 = conv(dilations = x_307_dilations_0, groups = x_307_groups_0, pad = x_307_pad_0, pad_type = x_307_pad_type_0, strides = x_307_strides_0, weight = e_encoders_29_self_attn_fsmn_block_weight_to_fp16, x = input_785_cast_fp16)[name = tensor("x_307_cast_fp16")]; + tensor x_309_perm_0 = const()[name = tensor("x_309_perm_0"), val = tensor([0, 2, 1])]; + tensor x_309_cast_fp16 = transpose(perm = x_309_perm_0, x = x_307_cast_fp16)[name = tensor("transpose_367")]; + tensor input_787_cast_fp16 = add(x = x_309_cast_fp16, y = inputs_61_cast_fp16)[name = tensor("input_787_cast_fp16")]; + tensor fsmn_memory_61_cast_fp16 = mul(x = input_787_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_61_cast_fp16")]; + tensor var_2823_to_fp16 = const()[name = tensor("op_2823_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_123_cast_fp16 = mul(x = var_2798_cast_fp16, y = var_2823_to_fp16)[name = tensor("q_h_123_cast_fp16")]; + tensor scores_121_transpose_x_0 = const()[name = tensor("scores_121_transpose_x_0"), val = tensor(false)]; + tensor scores_121_transpose_y_0 = const()[name = tensor("scores_121_transpose_y_0"), val = tensor(false)]; + tensor transpose_210_perm_0 = const()[name = tensor("transpose_210_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_211_perm_0 = const()[name = tensor("transpose_211_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_211 = transpose(perm = transpose_211_perm_0, x = var_2801_cast_fp16)[name = tensor("transpose_365")]; + tensor transpose_210 = transpose(perm = transpose_210_perm_0, x = q_h_123_cast_fp16)[name = tensor("transpose_366")]; + tensor scores_121_cast_fp16 = matmul(transpose_x = scores_121_transpose_x_0, transpose_y = scores_121_transpose_y_0, x = transpose_210, y = transpose_211)[name = tensor("scores_121_cast_fp16")]; + tensor scores_123_cast_fp16 = select(a = var_11_to_fp16, b = scores_121_cast_fp16, cond = mask_5)[name = tensor("scores_123_cast_fp16")]; + tensor var_2831_cast_fp16 = softmax(axis = var_20, x = scores_123_cast_fp16)[name = tensor("op_2831_cast_fp16")]; + tensor input_789_cast_fp16 = select(a = var_6_to_fp16, b = var_2831_cast_fp16, cond = mask_5)[name = tensor("input_789_cast_fp16")]; + tensor x_313_transpose_x_0 = const()[name = tensor("x_313_transpose_x_0"), val = tensor(false)]; + tensor x_313_transpose_y_0 = const()[name = tensor("x_313_transpose_y_0"), val = tensor(false)]; + tensor value_61_cast_fp16 = transpose(perm = value_61_perm_0, x = var_2804_cast_fp16)[name = tensor("transpose_369")]; + tensor x_313_cast_fp16 = matmul(transpose_x = x_313_transpose_x_0, transpose_y = x_313_transpose_y_0, x = input_789_cast_fp16, y = value_61_cast_fp16)[name = tensor("x_313_cast_fp16")]; + tensor var_2835_perm_0 = const()[name = tensor("op_2835_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2837 = const()[name = tensor("op_2837"), val = tensor([1, -1, 512])]; + tensor var_2835_cast_fp16 = transpose(perm = var_2835_perm_0, x = x_313_cast_fp16)[name = tensor("transpose_364")]; + tensor input_791_cast_fp16 = reshape(shape = var_2837, x = var_2835_cast_fp16)[name = tensor("input_791_cast_fp16")]; + tensor e_encoders_29_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_29_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191243904)))]; + tensor e_encoders_29_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_29_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191768256)))]; + tensor linear_121_cast_fp16 = linear(bias = e_encoders_29_self_attn_linear_out_bias_to_fp16, weight = e_encoders_29_self_attn_linear_out_weight_to_fp16, x = input_791_cast_fp16)[name = tensor("linear_121_cast_fp16")]; + tensor input_793_cast_fp16 = add(x = linear_121_cast_fp16, y = fsmn_memory_61_cast_fp16)[name = tensor("input_793_cast_fp16")]; + tensor input_795_cast_fp16 = add(x = input_781_cast_fp16, y = input_793_cast_fp16)[name = tensor("input_795_cast_fp16")]; + tensor input_797_axes_0 = const()[name = tensor("input_797_axes_0"), val = tensor([-1])]; + tensor e_encoders_29_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_29_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191769344)))]; + tensor e_encoders_29_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_29_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191770432)))]; + tensor input_797_cast_fp16 = layer_norm(axes = input_797_axes_0, beta = e_encoders_29_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_29_norm2_weight_to_fp16, x = input_795_cast_fp16)[name = tensor("input_797_cast_fp16")]; + tensor e_encoders_29_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_29_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191771520)))]; + tensor e_encoders_29_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_29_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193868736)))]; + tensor linear_122_cast_fp16 = linear(bias = e_encoders_29_feed_forward_w_1_bias_to_fp16, weight = e_encoders_29_feed_forward_w_1_weight_to_fp16, x = input_797_cast_fp16)[name = tensor("linear_122_cast_fp16")]; + tensor input_801_cast_fp16 = relu(x = linear_122_cast_fp16)[name = tensor("input_801_cast_fp16")]; + tensor e_encoders_29_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_29_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193872896)))]; + tensor e_encoders_29_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_29_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195970112)))]; + tensor linear_123_cast_fp16 = linear(bias = e_encoders_29_feed_forward_w_2_bias_to_fp16, weight = e_encoders_29_feed_forward_w_2_weight_to_fp16, x = input_801_cast_fp16)[name = tensor("linear_123_cast_fp16")]; + tensor input_807_cast_fp16 = add(x = input_795_cast_fp16, y = linear_123_cast_fp16)[name = tensor("input_807_cast_fp16")]; + tensor x_315_axes_0 = const()[name = tensor("x_315_axes_0"), val = tensor([-1])]; + tensor e_encoders_30_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_30_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195971200)))]; + tensor e_encoders_30_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_30_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195972288)))]; + tensor x_315_cast_fp16 = layer_norm(axes = x_315_axes_0, beta = e_encoders_30_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_30_norm1_weight_to_fp16, x = input_807_cast_fp16)[name = tensor("x_315_cast_fp16")]; + tensor e_encoders_30_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_30_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195973376)))]; + tensor e_encoders_30_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_30_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197546304)))]; + tensor linear_124_cast_fp16 = linear(bias = e_encoders_30_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_30_self_attn_linear_q_k_v_weight_to_fp16, x = x_315_cast_fp16)[name = tensor("linear_124_cast_fp16")]; + tensor tile_31 = const()[name = tensor("tile_31"), val = tensor([512, 512, 512])]; + tensor var_2881_axis_0 = const()[name = tensor("op_2881_axis_0"), val = tensor(-1)]; + tensor var_2881_cast_fp16_0, tensor var_2881_cast_fp16_1, tensor var_2881_cast_fp16_2 = split(axis = var_2881_axis_0, split_sizes = tile_31, x = linear_124_cast_fp16)[name = tensor("op_2881_cast_fp16")]; + tensor concat_94x = const()[name = tensor("concat_94x"), val = tensor([1, -1, 4, 128])]; + tensor var_2886_cast_fp16 = reshape(shape = concat_94x, x = var_2881_cast_fp16_0)[name = tensor("op_2886_cast_fp16")]; + tensor concat_95x = const()[name = tensor("concat_95x"), val = tensor([1, -1, 4, 128])]; + tensor var_2889_cast_fp16 = reshape(shape = concat_95x, x = var_2881_cast_fp16_1)[name = tensor("op_2889_cast_fp16")]; + tensor concat_96x = const()[name = tensor("concat_96x"), val = tensor([1, -1, 4, 128])]; + tensor var_2892_cast_fp16 = reshape(shape = concat_96x, x = var_2881_cast_fp16_2)[name = tensor("op_2892_cast_fp16")]; + tensor value_63_perm_0 = const()[name = tensor("value_63_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_63_cast_fp16 = mul(x = var_2881_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_63_cast_fp16")]; + tensor input_809_perm_0 = const()[name = tensor("input_809_perm_0"), val = tensor([0, 2, 1])]; + tensor input_811_pad_0 = const()[name = tensor("input_811_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_811_mode_0 = const()[name = tensor("input_811_mode_0"), val = tensor("constant")]; + tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(0x0p+0)]; + tensor input_809_cast_fp16 = transpose(perm = input_809_perm_0, x = inputs_63_cast_fp16)[name = tensor("transpose_362")]; + tensor input_811_cast_fp16 = pad(constant_val = const_71_to_fp16, mode = input_811_mode_0, pad = input_811_pad_0, x = input_809_cast_fp16)[name = tensor("input_811_cast_fp16")]; + tensor x_317_pad_type_0 = const()[name = tensor("x_317_pad_type_0"), val = tensor("valid")]; + tensor x_317_groups_0 = const()[name = tensor("x_317_groups_0"), val = tensor(512)]; + tensor x_317_strides_0 = const()[name = tensor("x_317_strides_0"), val = tensor([1])]; + tensor x_317_pad_0 = const()[name = tensor("x_317_pad_0"), val = tensor([0, 0])]; + tensor x_317_dilations_0 = const()[name = tensor("x_317_dilations_0"), val = tensor([1])]; + tensor e_encoders_30_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_30_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197549440)))]; + tensor x_317_cast_fp16 = conv(dilations = x_317_dilations_0, groups = x_317_groups_0, pad = x_317_pad_0, pad_type = x_317_pad_type_0, strides = x_317_strides_0, weight = e_encoders_30_self_attn_fsmn_block_weight_to_fp16, x = input_811_cast_fp16)[name = tensor("x_317_cast_fp16")]; + tensor x_319_perm_0 = const()[name = tensor("x_319_perm_0"), val = tensor([0, 2, 1])]; + tensor x_319_cast_fp16 = transpose(perm = x_319_perm_0, x = x_317_cast_fp16)[name = tensor("transpose_361")]; + tensor input_813_cast_fp16 = add(x = x_319_cast_fp16, y = inputs_63_cast_fp16)[name = tensor("input_813_cast_fp16")]; + tensor fsmn_memory_63_cast_fp16 = mul(x = input_813_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_63_cast_fp16")]; + tensor var_2911_to_fp16 = const()[name = tensor("op_2911_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_127_cast_fp16 = mul(x = var_2886_cast_fp16, y = var_2911_to_fp16)[name = tensor("q_h_127_cast_fp16")]; + tensor scores_125_transpose_x_0 = const()[name = tensor("scores_125_transpose_x_0"), val = tensor(false)]; + tensor scores_125_transpose_y_0 = const()[name = tensor("scores_125_transpose_y_0"), val = tensor(false)]; + tensor transpose_212_perm_0 = const()[name = tensor("transpose_212_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_213_perm_0 = const()[name = tensor("transpose_213_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_213 = transpose(perm = transpose_213_perm_0, x = var_2889_cast_fp16)[name = tensor("transpose_359")]; + tensor transpose_212 = transpose(perm = transpose_212_perm_0, x = q_h_127_cast_fp16)[name = tensor("transpose_360")]; + tensor scores_125_cast_fp16 = matmul(transpose_x = scores_125_transpose_x_0, transpose_y = scores_125_transpose_y_0, x = transpose_212, y = transpose_213)[name = tensor("scores_125_cast_fp16")]; + tensor scores_127_cast_fp16 = select(a = var_11_to_fp16, b = scores_125_cast_fp16, cond = mask_5)[name = tensor("scores_127_cast_fp16")]; + tensor var_2919_cast_fp16 = softmax(axis = var_20, x = scores_127_cast_fp16)[name = tensor("op_2919_cast_fp16")]; + tensor input_815_cast_fp16 = select(a = var_6_to_fp16, b = var_2919_cast_fp16, cond = mask_5)[name = tensor("input_815_cast_fp16")]; + tensor x_323_transpose_x_0 = const()[name = tensor("x_323_transpose_x_0"), val = tensor(false)]; + tensor x_323_transpose_y_0 = const()[name = tensor("x_323_transpose_y_0"), val = tensor(false)]; + tensor value_63_cast_fp16 = transpose(perm = value_63_perm_0, x = var_2892_cast_fp16)[name = tensor("transpose_363")]; + tensor x_323_cast_fp16 = matmul(transpose_x = x_323_transpose_x_0, transpose_y = x_323_transpose_y_0, x = input_815_cast_fp16, y = value_63_cast_fp16)[name = tensor("x_323_cast_fp16")]; + tensor var_2923_perm_0 = const()[name = tensor("op_2923_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2925 = const()[name = tensor("op_2925"), val = tensor([1, -1, 512])]; + tensor var_2923_cast_fp16 = transpose(perm = var_2923_perm_0, x = x_323_cast_fp16)[name = tensor("transpose_358")]; + tensor input_817_cast_fp16 = reshape(shape = var_2925, x = var_2923_cast_fp16)[name = tensor("input_817_cast_fp16")]; + tensor e_encoders_30_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_30_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197560768)))]; + tensor e_encoders_30_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_30_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198085120)))]; + tensor linear_125_cast_fp16 = linear(bias = e_encoders_30_self_attn_linear_out_bias_to_fp16, weight = e_encoders_30_self_attn_linear_out_weight_to_fp16, x = input_817_cast_fp16)[name = tensor("linear_125_cast_fp16")]; + tensor input_819_cast_fp16 = add(x = linear_125_cast_fp16, y = fsmn_memory_63_cast_fp16)[name = tensor("input_819_cast_fp16")]; + tensor input_821_cast_fp16 = add(x = input_807_cast_fp16, y = input_819_cast_fp16)[name = tensor("input_821_cast_fp16")]; + tensor input_823_axes_0 = const()[name = tensor("input_823_axes_0"), val = tensor([-1])]; + tensor e_encoders_30_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_30_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198086208)))]; + tensor e_encoders_30_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_30_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198087296)))]; + tensor input_823_cast_fp16 = layer_norm(axes = input_823_axes_0, beta = e_encoders_30_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_30_norm2_weight_to_fp16, x = input_821_cast_fp16)[name = tensor("input_823_cast_fp16")]; + tensor e_encoders_30_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_30_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198088384)))]; + tensor e_encoders_30_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_30_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200185600)))]; + tensor linear_126_cast_fp16 = linear(bias = e_encoders_30_feed_forward_w_1_bias_to_fp16, weight = e_encoders_30_feed_forward_w_1_weight_to_fp16, x = input_823_cast_fp16)[name = tensor("linear_126_cast_fp16")]; + tensor input_827_cast_fp16 = relu(x = linear_126_cast_fp16)[name = tensor("input_827_cast_fp16")]; + tensor e_encoders_30_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_30_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200189760)))]; + tensor e_encoders_30_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_30_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202286976)))]; + tensor linear_127_cast_fp16 = linear(bias = e_encoders_30_feed_forward_w_2_bias_to_fp16, weight = e_encoders_30_feed_forward_w_2_weight_to_fp16, x = input_827_cast_fp16)[name = tensor("linear_127_cast_fp16")]; + tensor input_833_cast_fp16 = add(x = input_821_cast_fp16, y = linear_127_cast_fp16)[name = tensor("input_833_cast_fp16")]; + tensor x_325_axes_0 = const()[name = tensor("x_325_axes_0"), val = tensor([-1])]; + tensor e_encoders_31_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_31_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202288064)))]; + tensor e_encoders_31_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_31_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202289152)))]; + tensor x_325_cast_fp16 = layer_norm(axes = x_325_axes_0, beta = e_encoders_31_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_31_norm1_weight_to_fp16, x = input_833_cast_fp16)[name = tensor("x_325_cast_fp16")]; + tensor e_encoders_31_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_31_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202290240)))]; + tensor e_encoders_31_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_31_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203863168)))]; + tensor linear_128_cast_fp16 = linear(bias = e_encoders_31_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_31_self_attn_linear_q_k_v_weight_to_fp16, x = x_325_cast_fp16)[name = tensor("linear_128_cast_fp16")]; + tensor tile_32 = const()[name = tensor("tile_32"), val = tensor([512, 512, 512])]; + tensor var_2969_axis_0 = const()[name = tensor("op_2969_axis_0"), val = tensor(-1)]; + tensor var_2969_cast_fp16_0, tensor var_2969_cast_fp16_1, tensor var_2969_cast_fp16_2 = split(axis = var_2969_axis_0, split_sizes = tile_32, x = linear_128_cast_fp16)[name = tensor("op_2969_cast_fp16")]; + tensor concat_97x = const()[name = tensor("concat_97x"), val = tensor([1, -1, 4, 128])]; + tensor var_2974_cast_fp16 = reshape(shape = concat_97x, x = var_2969_cast_fp16_0)[name = tensor("op_2974_cast_fp16")]; + tensor concat_98x = const()[name = tensor("concat_98x"), val = tensor([1, -1, 4, 128])]; + tensor var_2977_cast_fp16 = reshape(shape = concat_98x, x = var_2969_cast_fp16_1)[name = tensor("op_2977_cast_fp16")]; + tensor concat_99x = const()[name = tensor("concat_99x"), val = tensor([1, -1, 4, 128])]; + tensor var_2980_cast_fp16 = reshape(shape = concat_99x, x = var_2969_cast_fp16_2)[name = tensor("op_2980_cast_fp16")]; + tensor value_65_perm_0 = const()[name = tensor("value_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_65_cast_fp16 = mul(x = var_2969_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_65_cast_fp16")]; + tensor input_835_perm_0 = const()[name = tensor("input_835_perm_0"), val = tensor([0, 2, 1])]; + tensor input_837_pad_0 = const()[name = tensor("input_837_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_837_mode_0 = const()[name = tensor("input_837_mode_0"), val = tensor("constant")]; + tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(0x0p+0)]; + tensor input_835_cast_fp16 = transpose(perm = input_835_perm_0, x = inputs_65_cast_fp16)[name = tensor("transpose_356")]; + tensor input_837_cast_fp16 = pad(constant_val = const_73_to_fp16, mode = input_837_mode_0, pad = input_837_pad_0, x = input_835_cast_fp16)[name = tensor("input_837_cast_fp16")]; + tensor x_327_pad_type_0 = const()[name = tensor("x_327_pad_type_0"), val = tensor("valid")]; + tensor x_327_groups_0 = const()[name = tensor("x_327_groups_0"), val = tensor(512)]; + tensor x_327_strides_0 = const()[name = tensor("x_327_strides_0"), val = tensor([1])]; + tensor x_327_pad_0 = const()[name = tensor("x_327_pad_0"), val = tensor([0, 0])]; + tensor x_327_dilations_0 = const()[name = tensor("x_327_dilations_0"), val = tensor([1])]; + tensor e_encoders_31_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_31_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203866304)))]; + tensor x_327_cast_fp16 = conv(dilations = x_327_dilations_0, groups = x_327_groups_0, pad = x_327_pad_0, pad_type = x_327_pad_type_0, strides = x_327_strides_0, weight = e_encoders_31_self_attn_fsmn_block_weight_to_fp16, x = input_837_cast_fp16)[name = tensor("x_327_cast_fp16")]; + tensor x_329_perm_0 = const()[name = tensor("x_329_perm_0"), val = tensor([0, 2, 1])]; + tensor x_329_cast_fp16 = transpose(perm = x_329_perm_0, x = x_327_cast_fp16)[name = tensor("transpose_355")]; + tensor input_839_cast_fp16 = add(x = x_329_cast_fp16, y = inputs_65_cast_fp16)[name = tensor("input_839_cast_fp16")]; + tensor fsmn_memory_65_cast_fp16 = mul(x = input_839_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_65_cast_fp16")]; + tensor var_2999_to_fp16 = const()[name = tensor("op_2999_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_131_cast_fp16 = mul(x = var_2974_cast_fp16, y = var_2999_to_fp16)[name = tensor("q_h_131_cast_fp16")]; + tensor scores_129_transpose_x_0 = const()[name = tensor("scores_129_transpose_x_0"), val = tensor(false)]; + tensor scores_129_transpose_y_0 = const()[name = tensor("scores_129_transpose_y_0"), val = tensor(false)]; + tensor transpose_214_perm_0 = const()[name = tensor("transpose_214_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_215_perm_0 = const()[name = tensor("transpose_215_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_215 = transpose(perm = transpose_215_perm_0, x = var_2977_cast_fp16)[name = tensor("transpose_353")]; + tensor transpose_214 = transpose(perm = transpose_214_perm_0, x = q_h_131_cast_fp16)[name = tensor("transpose_354")]; + tensor scores_129_cast_fp16 = matmul(transpose_x = scores_129_transpose_x_0, transpose_y = scores_129_transpose_y_0, x = transpose_214, y = transpose_215)[name = tensor("scores_129_cast_fp16")]; + tensor scores_131_cast_fp16 = select(a = var_11_to_fp16, b = scores_129_cast_fp16, cond = mask_5)[name = tensor("scores_131_cast_fp16")]; + tensor var_3007_cast_fp16 = softmax(axis = var_20, x = scores_131_cast_fp16)[name = tensor("op_3007_cast_fp16")]; + tensor input_841_cast_fp16 = select(a = var_6_to_fp16, b = var_3007_cast_fp16, cond = mask_5)[name = tensor("input_841_cast_fp16")]; + tensor x_333_transpose_x_0 = const()[name = tensor("x_333_transpose_x_0"), val = tensor(false)]; + tensor x_333_transpose_y_0 = const()[name = tensor("x_333_transpose_y_0"), val = tensor(false)]; + tensor value_65_cast_fp16 = transpose(perm = value_65_perm_0, x = var_2980_cast_fp16)[name = tensor("transpose_357")]; + tensor x_333_cast_fp16 = matmul(transpose_x = x_333_transpose_x_0, transpose_y = x_333_transpose_y_0, x = input_841_cast_fp16, y = value_65_cast_fp16)[name = tensor("x_333_cast_fp16")]; + tensor var_3011_perm_0 = const()[name = tensor("op_3011_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3013 = const()[name = tensor("op_3013"), val = tensor([1, -1, 512])]; + tensor var_3011_cast_fp16 = transpose(perm = var_3011_perm_0, x = x_333_cast_fp16)[name = tensor("transpose_352")]; + tensor input_843_cast_fp16 = reshape(shape = var_3013, x = var_3011_cast_fp16)[name = tensor("input_843_cast_fp16")]; + tensor e_encoders_31_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_31_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203877632)))]; + tensor e_encoders_31_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_31_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204401984)))]; + tensor linear_129_cast_fp16 = linear(bias = e_encoders_31_self_attn_linear_out_bias_to_fp16, weight = e_encoders_31_self_attn_linear_out_weight_to_fp16, x = input_843_cast_fp16)[name = tensor("linear_129_cast_fp16")]; + tensor input_845_cast_fp16 = add(x = linear_129_cast_fp16, y = fsmn_memory_65_cast_fp16)[name = tensor("input_845_cast_fp16")]; + tensor input_847_cast_fp16 = add(x = input_833_cast_fp16, y = input_845_cast_fp16)[name = tensor("input_847_cast_fp16")]; + tensor input_849_axes_0 = const()[name = tensor("input_849_axes_0"), val = tensor([-1])]; + tensor e_encoders_31_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_31_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204403072)))]; + tensor e_encoders_31_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_31_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204404160)))]; + tensor input_849_cast_fp16 = layer_norm(axes = input_849_axes_0, beta = e_encoders_31_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_31_norm2_weight_to_fp16, x = input_847_cast_fp16)[name = tensor("input_849_cast_fp16")]; + tensor e_encoders_31_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_31_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204405248)))]; + tensor e_encoders_31_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_31_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206502464)))]; + tensor linear_130_cast_fp16 = linear(bias = e_encoders_31_feed_forward_w_1_bias_to_fp16, weight = e_encoders_31_feed_forward_w_1_weight_to_fp16, x = input_849_cast_fp16)[name = tensor("linear_130_cast_fp16")]; + tensor input_853_cast_fp16 = relu(x = linear_130_cast_fp16)[name = tensor("input_853_cast_fp16")]; + tensor e_encoders_31_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_31_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206506624)))]; + tensor e_encoders_31_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_31_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208603840)))]; + tensor linear_131_cast_fp16 = linear(bias = e_encoders_31_feed_forward_w_2_bias_to_fp16, weight = e_encoders_31_feed_forward_w_2_weight_to_fp16, x = input_853_cast_fp16)[name = tensor("linear_131_cast_fp16")]; + tensor input_859_cast_fp16 = add(x = input_847_cast_fp16, y = linear_131_cast_fp16)[name = tensor("input_859_cast_fp16")]; + tensor x_335_axes_0 = const()[name = tensor("x_335_axes_0"), val = tensor([-1])]; + tensor e_encoders_32_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_32_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208604928)))]; + tensor e_encoders_32_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_32_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208606016)))]; + tensor x_335_cast_fp16 = layer_norm(axes = x_335_axes_0, beta = e_encoders_32_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_32_norm1_weight_to_fp16, x = input_859_cast_fp16)[name = tensor("x_335_cast_fp16")]; + tensor e_encoders_32_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_32_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208607104)))]; + tensor e_encoders_32_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_32_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210180032)))]; + tensor linear_132_cast_fp16 = linear(bias = e_encoders_32_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_32_self_attn_linear_q_k_v_weight_to_fp16, x = x_335_cast_fp16)[name = tensor("linear_132_cast_fp16")]; + tensor tile_33 = const()[name = tensor("tile_33"), val = tensor([512, 512, 512])]; + tensor var_3057_axis_0 = const()[name = tensor("op_3057_axis_0"), val = tensor(-1)]; + tensor var_3057_cast_fp16_0, tensor var_3057_cast_fp16_1, tensor var_3057_cast_fp16_2 = split(axis = var_3057_axis_0, split_sizes = tile_33, x = linear_132_cast_fp16)[name = tensor("op_3057_cast_fp16")]; + tensor concat_100x = const()[name = tensor("concat_100x"), val = tensor([1, -1, 4, 128])]; + tensor var_3062_cast_fp16 = reshape(shape = concat_100x, x = var_3057_cast_fp16_0)[name = tensor("op_3062_cast_fp16")]; + tensor concat_101x = const()[name = tensor("concat_101x"), val = tensor([1, -1, 4, 128])]; + tensor var_3065_cast_fp16 = reshape(shape = concat_101x, x = var_3057_cast_fp16_1)[name = tensor("op_3065_cast_fp16")]; + tensor concat_102x = const()[name = tensor("concat_102x"), val = tensor([1, -1, 4, 128])]; + tensor var_3068_cast_fp16 = reshape(shape = concat_102x, x = var_3057_cast_fp16_2)[name = tensor("op_3068_cast_fp16")]; + tensor value_67_perm_0 = const()[name = tensor("value_67_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_67_cast_fp16 = mul(x = var_3057_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_67_cast_fp16")]; + tensor input_861_perm_0 = const()[name = tensor("input_861_perm_0"), val = tensor([0, 2, 1])]; + tensor input_863_pad_0 = const()[name = tensor("input_863_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_863_mode_0 = const()[name = tensor("input_863_mode_0"), val = tensor("constant")]; + tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(0x0p+0)]; + tensor input_861_cast_fp16 = transpose(perm = input_861_perm_0, x = inputs_67_cast_fp16)[name = tensor("transpose_350")]; + tensor input_863_cast_fp16 = pad(constant_val = const_75_to_fp16, mode = input_863_mode_0, pad = input_863_pad_0, x = input_861_cast_fp16)[name = tensor("input_863_cast_fp16")]; + tensor x_337_pad_type_0 = const()[name = tensor("x_337_pad_type_0"), val = tensor("valid")]; + tensor x_337_groups_0 = const()[name = tensor("x_337_groups_0"), val = tensor(512)]; + tensor x_337_strides_0 = const()[name = tensor("x_337_strides_0"), val = tensor([1])]; + tensor x_337_pad_0 = const()[name = tensor("x_337_pad_0"), val = tensor([0, 0])]; + tensor x_337_dilations_0 = const()[name = tensor("x_337_dilations_0"), val = tensor([1])]; + tensor e_encoders_32_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_32_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210183168)))]; + tensor x_337_cast_fp16 = conv(dilations = x_337_dilations_0, groups = x_337_groups_0, pad = x_337_pad_0, pad_type = x_337_pad_type_0, strides = x_337_strides_0, weight = e_encoders_32_self_attn_fsmn_block_weight_to_fp16, x = input_863_cast_fp16)[name = tensor("x_337_cast_fp16")]; + tensor x_339_perm_0 = const()[name = tensor("x_339_perm_0"), val = tensor([0, 2, 1])]; + tensor x_339_cast_fp16 = transpose(perm = x_339_perm_0, x = x_337_cast_fp16)[name = tensor("transpose_349")]; + tensor input_865_cast_fp16 = add(x = x_339_cast_fp16, y = inputs_67_cast_fp16)[name = tensor("input_865_cast_fp16")]; + tensor fsmn_memory_67_cast_fp16 = mul(x = input_865_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_67_cast_fp16")]; + tensor var_3087_to_fp16 = const()[name = tensor("op_3087_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_135_cast_fp16 = mul(x = var_3062_cast_fp16, y = var_3087_to_fp16)[name = tensor("q_h_135_cast_fp16")]; + tensor scores_133_transpose_x_0 = const()[name = tensor("scores_133_transpose_x_0"), val = tensor(false)]; + tensor scores_133_transpose_y_0 = const()[name = tensor("scores_133_transpose_y_0"), val = tensor(false)]; + tensor transpose_216_perm_0 = const()[name = tensor("transpose_216_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_217_perm_0 = const()[name = tensor("transpose_217_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_217 = transpose(perm = transpose_217_perm_0, x = var_3065_cast_fp16)[name = tensor("transpose_347")]; + tensor transpose_216 = transpose(perm = transpose_216_perm_0, x = q_h_135_cast_fp16)[name = tensor("transpose_348")]; + tensor scores_133_cast_fp16 = matmul(transpose_x = scores_133_transpose_x_0, transpose_y = scores_133_transpose_y_0, x = transpose_216, y = transpose_217)[name = tensor("scores_133_cast_fp16")]; + tensor scores_135_cast_fp16 = select(a = var_11_to_fp16, b = scores_133_cast_fp16, cond = mask_5)[name = tensor("scores_135_cast_fp16")]; + tensor var_3095_cast_fp16 = softmax(axis = var_20, x = scores_135_cast_fp16)[name = tensor("op_3095_cast_fp16")]; + tensor input_867_cast_fp16 = select(a = var_6_to_fp16, b = var_3095_cast_fp16, cond = mask_5)[name = tensor("input_867_cast_fp16")]; + tensor x_343_transpose_x_0 = const()[name = tensor("x_343_transpose_x_0"), val = tensor(false)]; + tensor x_343_transpose_y_0 = const()[name = tensor("x_343_transpose_y_0"), val = tensor(false)]; + tensor value_67_cast_fp16 = transpose(perm = value_67_perm_0, x = var_3068_cast_fp16)[name = tensor("transpose_351")]; + tensor x_343_cast_fp16 = matmul(transpose_x = x_343_transpose_x_0, transpose_y = x_343_transpose_y_0, x = input_867_cast_fp16, y = value_67_cast_fp16)[name = tensor("x_343_cast_fp16")]; + tensor var_3099_perm_0 = const()[name = tensor("op_3099_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3101 = const()[name = tensor("op_3101"), val = tensor([1, -1, 512])]; + tensor var_3099_cast_fp16 = transpose(perm = var_3099_perm_0, x = x_343_cast_fp16)[name = tensor("transpose_346")]; + tensor input_869_cast_fp16 = reshape(shape = var_3101, x = var_3099_cast_fp16)[name = tensor("input_869_cast_fp16")]; + tensor e_encoders_32_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_32_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210194496)))]; + tensor e_encoders_32_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_32_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210718848)))]; + tensor linear_133_cast_fp16 = linear(bias = e_encoders_32_self_attn_linear_out_bias_to_fp16, weight = e_encoders_32_self_attn_linear_out_weight_to_fp16, x = input_869_cast_fp16)[name = tensor("linear_133_cast_fp16")]; + tensor input_871_cast_fp16 = add(x = linear_133_cast_fp16, y = fsmn_memory_67_cast_fp16)[name = tensor("input_871_cast_fp16")]; + tensor input_873_cast_fp16 = add(x = input_859_cast_fp16, y = input_871_cast_fp16)[name = tensor("input_873_cast_fp16")]; + tensor input_875_axes_0 = const()[name = tensor("input_875_axes_0"), val = tensor([-1])]; + tensor e_encoders_32_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_32_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210719936)))]; + tensor e_encoders_32_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_32_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210721024)))]; + tensor input_875_cast_fp16 = layer_norm(axes = input_875_axes_0, beta = e_encoders_32_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_32_norm2_weight_to_fp16, x = input_873_cast_fp16)[name = tensor("input_875_cast_fp16")]; + tensor e_encoders_32_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_32_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210722112)))]; + tensor e_encoders_32_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_32_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212819328)))]; + tensor linear_134_cast_fp16 = linear(bias = e_encoders_32_feed_forward_w_1_bias_to_fp16, weight = e_encoders_32_feed_forward_w_1_weight_to_fp16, x = input_875_cast_fp16)[name = tensor("linear_134_cast_fp16")]; + tensor input_879_cast_fp16 = relu(x = linear_134_cast_fp16)[name = tensor("input_879_cast_fp16")]; + tensor e_encoders_32_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_32_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212823488)))]; + tensor e_encoders_32_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_32_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214920704)))]; + tensor linear_135_cast_fp16 = linear(bias = e_encoders_32_feed_forward_w_2_bias_to_fp16, weight = e_encoders_32_feed_forward_w_2_weight_to_fp16, x = input_879_cast_fp16)[name = tensor("linear_135_cast_fp16")]; + tensor input_885_cast_fp16 = add(x = input_873_cast_fp16, y = linear_135_cast_fp16)[name = tensor("input_885_cast_fp16")]; + tensor x_345_axes_0 = const()[name = tensor("x_345_axes_0"), val = tensor([-1])]; + tensor e_encoders_33_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_33_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214921792)))]; + tensor e_encoders_33_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_33_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214922880)))]; + tensor x_345_cast_fp16 = layer_norm(axes = x_345_axes_0, beta = e_encoders_33_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_33_norm1_weight_to_fp16, x = input_885_cast_fp16)[name = tensor("x_345_cast_fp16")]; + tensor e_encoders_33_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_33_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214923968)))]; + tensor e_encoders_33_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_33_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216496896)))]; + tensor linear_136_cast_fp16 = linear(bias = e_encoders_33_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_33_self_attn_linear_q_k_v_weight_to_fp16, x = x_345_cast_fp16)[name = tensor("linear_136_cast_fp16")]; + tensor tile_34 = const()[name = tensor("tile_34"), val = tensor([512, 512, 512])]; + tensor var_3145_axis_0 = const()[name = tensor("op_3145_axis_0"), val = tensor(-1)]; + tensor var_3145_cast_fp16_0, tensor var_3145_cast_fp16_1, tensor var_3145_cast_fp16_2 = split(axis = var_3145_axis_0, split_sizes = tile_34, x = linear_136_cast_fp16)[name = tensor("op_3145_cast_fp16")]; + tensor concat_103x = const()[name = tensor("concat_103x"), val = tensor([1, -1, 4, 128])]; + tensor var_3150_cast_fp16 = reshape(shape = concat_103x, x = var_3145_cast_fp16_0)[name = tensor("op_3150_cast_fp16")]; + tensor concat_104x = const()[name = tensor("concat_104x"), val = tensor([1, -1, 4, 128])]; + tensor var_3153_cast_fp16 = reshape(shape = concat_104x, x = var_3145_cast_fp16_1)[name = tensor("op_3153_cast_fp16")]; + tensor concat_105x = const()[name = tensor("concat_105x"), val = tensor([1, -1, 4, 128])]; + tensor var_3156_cast_fp16 = reshape(shape = concat_105x, x = var_3145_cast_fp16_2)[name = tensor("op_3156_cast_fp16")]; + tensor value_69_perm_0 = const()[name = tensor("value_69_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_69_cast_fp16 = mul(x = var_3145_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_69_cast_fp16")]; + tensor input_887_perm_0 = const()[name = tensor("input_887_perm_0"), val = tensor([0, 2, 1])]; + tensor input_889_pad_0 = const()[name = tensor("input_889_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_889_mode_0 = const()[name = tensor("input_889_mode_0"), val = tensor("constant")]; + tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(0x0p+0)]; + tensor input_887_cast_fp16 = transpose(perm = input_887_perm_0, x = inputs_69_cast_fp16)[name = tensor("transpose_344")]; + tensor input_889_cast_fp16 = pad(constant_val = const_77_to_fp16, mode = input_889_mode_0, pad = input_889_pad_0, x = input_887_cast_fp16)[name = tensor("input_889_cast_fp16")]; + tensor x_347_pad_type_0 = const()[name = tensor("x_347_pad_type_0"), val = tensor("valid")]; + tensor x_347_groups_0 = const()[name = tensor("x_347_groups_0"), val = tensor(512)]; + tensor x_347_strides_0 = const()[name = tensor("x_347_strides_0"), val = tensor([1])]; + tensor x_347_pad_0 = const()[name = tensor("x_347_pad_0"), val = tensor([0, 0])]; + tensor x_347_dilations_0 = const()[name = tensor("x_347_dilations_0"), val = tensor([1])]; + tensor e_encoders_33_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_33_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216500032)))]; + tensor x_347_cast_fp16 = conv(dilations = x_347_dilations_0, groups = x_347_groups_0, pad = x_347_pad_0, pad_type = x_347_pad_type_0, strides = x_347_strides_0, weight = e_encoders_33_self_attn_fsmn_block_weight_to_fp16, x = input_889_cast_fp16)[name = tensor("x_347_cast_fp16")]; + tensor x_349_perm_0 = const()[name = tensor("x_349_perm_0"), val = tensor([0, 2, 1])]; + tensor x_349_cast_fp16 = transpose(perm = x_349_perm_0, x = x_347_cast_fp16)[name = tensor("transpose_343")]; + tensor input_891_cast_fp16 = add(x = x_349_cast_fp16, y = inputs_69_cast_fp16)[name = tensor("input_891_cast_fp16")]; + tensor fsmn_memory_69_cast_fp16 = mul(x = input_891_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_69_cast_fp16")]; + tensor var_3175_to_fp16 = const()[name = tensor("op_3175_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_139_cast_fp16 = mul(x = var_3150_cast_fp16, y = var_3175_to_fp16)[name = tensor("q_h_139_cast_fp16")]; + tensor scores_137_transpose_x_0 = const()[name = tensor("scores_137_transpose_x_0"), val = tensor(false)]; + tensor scores_137_transpose_y_0 = const()[name = tensor("scores_137_transpose_y_0"), val = tensor(false)]; + tensor transpose_218_perm_0 = const()[name = tensor("transpose_218_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_219_perm_0 = const()[name = tensor("transpose_219_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_219 = transpose(perm = transpose_219_perm_0, x = var_3153_cast_fp16)[name = tensor("transpose_341")]; + tensor transpose_218 = transpose(perm = transpose_218_perm_0, x = q_h_139_cast_fp16)[name = tensor("transpose_342")]; + tensor scores_137_cast_fp16 = matmul(transpose_x = scores_137_transpose_x_0, transpose_y = scores_137_transpose_y_0, x = transpose_218, y = transpose_219)[name = tensor("scores_137_cast_fp16")]; + tensor scores_139_cast_fp16 = select(a = var_11_to_fp16, b = scores_137_cast_fp16, cond = mask_5)[name = tensor("scores_139_cast_fp16")]; + tensor var_3183_cast_fp16 = softmax(axis = var_20, x = scores_139_cast_fp16)[name = tensor("op_3183_cast_fp16")]; + tensor input_893_cast_fp16 = select(a = var_6_to_fp16, b = var_3183_cast_fp16, cond = mask_5)[name = tensor("input_893_cast_fp16")]; + tensor x_353_transpose_x_0 = const()[name = tensor("x_353_transpose_x_0"), val = tensor(false)]; + tensor x_353_transpose_y_0 = const()[name = tensor("x_353_transpose_y_0"), val = tensor(false)]; + tensor value_69_cast_fp16 = transpose(perm = value_69_perm_0, x = var_3156_cast_fp16)[name = tensor("transpose_345")]; + tensor x_353_cast_fp16 = matmul(transpose_x = x_353_transpose_x_0, transpose_y = x_353_transpose_y_0, x = input_893_cast_fp16, y = value_69_cast_fp16)[name = tensor("x_353_cast_fp16")]; + tensor var_3187_perm_0 = const()[name = tensor("op_3187_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3189 = const()[name = tensor("op_3189"), val = tensor([1, -1, 512])]; + tensor var_3187_cast_fp16 = transpose(perm = var_3187_perm_0, x = x_353_cast_fp16)[name = tensor("transpose_340")]; + tensor input_895_cast_fp16 = reshape(shape = var_3189, x = var_3187_cast_fp16)[name = tensor("input_895_cast_fp16")]; + tensor e_encoders_33_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_33_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216511360)))]; + tensor e_encoders_33_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_33_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217035712)))]; + tensor linear_137_cast_fp16 = linear(bias = e_encoders_33_self_attn_linear_out_bias_to_fp16, weight = e_encoders_33_self_attn_linear_out_weight_to_fp16, x = input_895_cast_fp16)[name = tensor("linear_137_cast_fp16")]; + tensor input_897_cast_fp16 = add(x = linear_137_cast_fp16, y = fsmn_memory_69_cast_fp16)[name = tensor("input_897_cast_fp16")]; + tensor input_899_cast_fp16 = add(x = input_885_cast_fp16, y = input_897_cast_fp16)[name = tensor("input_899_cast_fp16")]; + tensor input_901_axes_0 = const()[name = tensor("input_901_axes_0"), val = tensor([-1])]; + tensor e_encoders_33_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_33_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217036800)))]; + tensor e_encoders_33_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_33_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217037888)))]; + tensor input_901_cast_fp16 = layer_norm(axes = input_901_axes_0, beta = e_encoders_33_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_33_norm2_weight_to_fp16, x = input_899_cast_fp16)[name = tensor("input_901_cast_fp16")]; + tensor e_encoders_33_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_33_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217038976)))]; + tensor e_encoders_33_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_33_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219136192)))]; + tensor linear_138_cast_fp16 = linear(bias = e_encoders_33_feed_forward_w_1_bias_to_fp16, weight = e_encoders_33_feed_forward_w_1_weight_to_fp16, x = input_901_cast_fp16)[name = tensor("linear_138_cast_fp16")]; + tensor input_905_cast_fp16 = relu(x = linear_138_cast_fp16)[name = tensor("input_905_cast_fp16")]; + tensor e_encoders_33_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_33_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219140352)))]; + tensor e_encoders_33_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_33_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221237568)))]; + tensor linear_139_cast_fp16 = linear(bias = e_encoders_33_feed_forward_w_2_bias_to_fp16, weight = e_encoders_33_feed_forward_w_2_weight_to_fp16, x = input_905_cast_fp16)[name = tensor("linear_139_cast_fp16")]; + tensor input_911_cast_fp16 = add(x = input_899_cast_fp16, y = linear_139_cast_fp16)[name = tensor("input_911_cast_fp16")]; + tensor x_355_axes_0 = const()[name = tensor("x_355_axes_0"), val = tensor([-1])]; + tensor e_encoders_34_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_34_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221238656)))]; + tensor e_encoders_34_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_34_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221239744)))]; + tensor x_355_cast_fp16 = layer_norm(axes = x_355_axes_0, beta = e_encoders_34_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_34_norm1_weight_to_fp16, x = input_911_cast_fp16)[name = tensor("x_355_cast_fp16")]; + tensor e_encoders_34_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_34_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221240832)))]; + tensor e_encoders_34_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_34_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222813760)))]; + tensor linear_140_cast_fp16 = linear(bias = e_encoders_34_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_34_self_attn_linear_q_k_v_weight_to_fp16, x = x_355_cast_fp16)[name = tensor("linear_140_cast_fp16")]; + tensor tile_35 = const()[name = tensor("tile_35"), val = tensor([512, 512, 512])]; + tensor var_3233_axis_0 = const()[name = tensor("op_3233_axis_0"), val = tensor(-1)]; + tensor var_3233_cast_fp16_0, tensor var_3233_cast_fp16_1, tensor var_3233_cast_fp16_2 = split(axis = var_3233_axis_0, split_sizes = tile_35, x = linear_140_cast_fp16)[name = tensor("op_3233_cast_fp16")]; + tensor concat_106x = const()[name = tensor("concat_106x"), val = tensor([1, -1, 4, 128])]; + tensor var_3238_cast_fp16 = reshape(shape = concat_106x, x = var_3233_cast_fp16_0)[name = tensor("op_3238_cast_fp16")]; + tensor concat_107x = const()[name = tensor("concat_107x"), val = tensor([1, -1, 4, 128])]; + tensor var_3241_cast_fp16 = reshape(shape = concat_107x, x = var_3233_cast_fp16_1)[name = tensor("op_3241_cast_fp16")]; + tensor concat_108x = const()[name = tensor("concat_108x"), val = tensor([1, -1, 4, 128])]; + tensor var_3244_cast_fp16 = reshape(shape = concat_108x, x = var_3233_cast_fp16_2)[name = tensor("op_3244_cast_fp16")]; + tensor value_71_perm_0 = const()[name = tensor("value_71_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_71_cast_fp16 = mul(x = var_3233_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_71_cast_fp16")]; + tensor input_913_perm_0 = const()[name = tensor("input_913_perm_0"), val = tensor([0, 2, 1])]; + tensor input_915_pad_0 = const()[name = tensor("input_915_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_915_mode_0 = const()[name = tensor("input_915_mode_0"), val = tensor("constant")]; + tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(0x0p+0)]; + tensor input_913_cast_fp16 = transpose(perm = input_913_perm_0, x = inputs_71_cast_fp16)[name = tensor("transpose_338")]; + tensor input_915_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_915_mode_0, pad = input_915_pad_0, x = input_913_cast_fp16)[name = tensor("input_915_cast_fp16")]; + tensor x_357_pad_type_0 = const()[name = tensor("x_357_pad_type_0"), val = tensor("valid")]; + tensor x_357_groups_0 = const()[name = tensor("x_357_groups_0"), val = tensor(512)]; + tensor x_357_strides_0 = const()[name = tensor("x_357_strides_0"), val = tensor([1])]; + tensor x_357_pad_0 = const()[name = tensor("x_357_pad_0"), val = tensor([0, 0])]; + tensor x_357_dilations_0 = const()[name = tensor("x_357_dilations_0"), val = tensor([1])]; + tensor e_encoders_34_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_34_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222816896)))]; + tensor x_357_cast_fp16 = conv(dilations = x_357_dilations_0, groups = x_357_groups_0, pad = x_357_pad_0, pad_type = x_357_pad_type_0, strides = x_357_strides_0, weight = e_encoders_34_self_attn_fsmn_block_weight_to_fp16, x = input_915_cast_fp16)[name = tensor("x_357_cast_fp16")]; + tensor x_359_perm_0 = const()[name = tensor("x_359_perm_0"), val = tensor([0, 2, 1])]; + tensor x_359_cast_fp16 = transpose(perm = x_359_perm_0, x = x_357_cast_fp16)[name = tensor("transpose_337")]; + tensor input_917_cast_fp16 = add(x = x_359_cast_fp16, y = inputs_71_cast_fp16)[name = tensor("input_917_cast_fp16")]; + tensor fsmn_memory_71_cast_fp16 = mul(x = input_917_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_71_cast_fp16")]; + tensor var_3263_to_fp16 = const()[name = tensor("op_3263_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_143_cast_fp16 = mul(x = var_3238_cast_fp16, y = var_3263_to_fp16)[name = tensor("q_h_143_cast_fp16")]; + tensor scores_141_transpose_x_0 = const()[name = tensor("scores_141_transpose_x_0"), val = tensor(false)]; + tensor scores_141_transpose_y_0 = const()[name = tensor("scores_141_transpose_y_0"), val = tensor(false)]; + tensor transpose_220_perm_0 = const()[name = tensor("transpose_220_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_221_perm_0 = const()[name = tensor("transpose_221_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_221 = transpose(perm = transpose_221_perm_0, x = var_3241_cast_fp16)[name = tensor("transpose_335")]; + tensor transpose_220 = transpose(perm = transpose_220_perm_0, x = q_h_143_cast_fp16)[name = tensor("transpose_336")]; + tensor scores_141_cast_fp16 = matmul(transpose_x = scores_141_transpose_x_0, transpose_y = scores_141_transpose_y_0, x = transpose_220, y = transpose_221)[name = tensor("scores_141_cast_fp16")]; + tensor scores_143_cast_fp16 = select(a = var_11_to_fp16, b = scores_141_cast_fp16, cond = mask_5)[name = tensor("scores_143_cast_fp16")]; + tensor var_3271_cast_fp16 = softmax(axis = var_20, x = scores_143_cast_fp16)[name = tensor("op_3271_cast_fp16")]; + tensor input_919_cast_fp16 = select(a = var_6_to_fp16, b = var_3271_cast_fp16, cond = mask_5)[name = tensor("input_919_cast_fp16")]; + tensor x_363_transpose_x_0 = const()[name = tensor("x_363_transpose_x_0"), val = tensor(false)]; + tensor x_363_transpose_y_0 = const()[name = tensor("x_363_transpose_y_0"), val = tensor(false)]; + tensor value_71_cast_fp16 = transpose(perm = value_71_perm_0, x = var_3244_cast_fp16)[name = tensor("transpose_339")]; + tensor x_363_cast_fp16 = matmul(transpose_x = x_363_transpose_x_0, transpose_y = x_363_transpose_y_0, x = input_919_cast_fp16, y = value_71_cast_fp16)[name = tensor("x_363_cast_fp16")]; + tensor var_3275_perm_0 = const()[name = tensor("op_3275_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3277 = const()[name = tensor("op_3277"), val = tensor([1, -1, 512])]; + tensor var_3275_cast_fp16 = transpose(perm = var_3275_perm_0, x = x_363_cast_fp16)[name = tensor("transpose_334")]; + tensor input_921_cast_fp16 = reshape(shape = var_3277, x = var_3275_cast_fp16)[name = tensor("input_921_cast_fp16")]; + tensor e_encoders_34_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_34_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222828224)))]; + tensor e_encoders_34_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_34_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223352576)))]; + tensor linear_141_cast_fp16 = linear(bias = e_encoders_34_self_attn_linear_out_bias_to_fp16, weight = e_encoders_34_self_attn_linear_out_weight_to_fp16, x = input_921_cast_fp16)[name = tensor("linear_141_cast_fp16")]; + tensor input_923_cast_fp16 = add(x = linear_141_cast_fp16, y = fsmn_memory_71_cast_fp16)[name = tensor("input_923_cast_fp16")]; + tensor input_925_cast_fp16 = add(x = input_911_cast_fp16, y = input_923_cast_fp16)[name = tensor("input_925_cast_fp16")]; + tensor input_927_axes_0 = const()[name = tensor("input_927_axes_0"), val = tensor([-1])]; + tensor e_encoders_34_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_34_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223353664)))]; + tensor e_encoders_34_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_34_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223354752)))]; + tensor input_927_cast_fp16 = layer_norm(axes = input_927_axes_0, beta = e_encoders_34_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_34_norm2_weight_to_fp16, x = input_925_cast_fp16)[name = tensor("input_927_cast_fp16")]; + tensor e_encoders_34_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_34_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223355840)))]; + tensor e_encoders_34_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_34_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225453056)))]; + tensor linear_142_cast_fp16 = linear(bias = e_encoders_34_feed_forward_w_1_bias_to_fp16, weight = e_encoders_34_feed_forward_w_1_weight_to_fp16, x = input_927_cast_fp16)[name = tensor("linear_142_cast_fp16")]; + tensor input_931_cast_fp16 = relu(x = linear_142_cast_fp16)[name = tensor("input_931_cast_fp16")]; + tensor e_encoders_34_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_34_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225457216)))]; + tensor e_encoders_34_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_34_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227554432)))]; + tensor linear_143_cast_fp16 = linear(bias = e_encoders_34_feed_forward_w_2_bias_to_fp16, weight = e_encoders_34_feed_forward_w_2_weight_to_fp16, x = input_931_cast_fp16)[name = tensor("linear_143_cast_fp16")]; + tensor input_937_cast_fp16 = add(x = input_925_cast_fp16, y = linear_143_cast_fp16)[name = tensor("input_937_cast_fp16")]; + tensor x_365_axes_0 = const()[name = tensor("x_365_axes_0"), val = tensor([-1])]; + tensor e_encoders_35_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_35_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227555520)))]; + tensor e_encoders_35_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_35_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227556608)))]; + tensor x_365_cast_fp16 = layer_norm(axes = x_365_axes_0, beta = e_encoders_35_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_35_norm1_weight_to_fp16, x = input_937_cast_fp16)[name = tensor("x_365_cast_fp16")]; + tensor e_encoders_35_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_35_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227557696)))]; + tensor e_encoders_35_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_35_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229130624)))]; + tensor linear_144_cast_fp16 = linear(bias = e_encoders_35_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_35_self_attn_linear_q_k_v_weight_to_fp16, x = x_365_cast_fp16)[name = tensor("linear_144_cast_fp16")]; + tensor tile_36 = const()[name = tensor("tile_36"), val = tensor([512, 512, 512])]; + tensor var_3321_axis_0 = const()[name = tensor("op_3321_axis_0"), val = tensor(-1)]; + tensor var_3321_cast_fp16_0, tensor var_3321_cast_fp16_1, tensor var_3321_cast_fp16_2 = split(axis = var_3321_axis_0, split_sizes = tile_36, x = linear_144_cast_fp16)[name = tensor("op_3321_cast_fp16")]; + tensor concat_109x = const()[name = tensor("concat_109x"), val = tensor([1, -1, 4, 128])]; + tensor var_3326_cast_fp16 = reshape(shape = concat_109x, x = var_3321_cast_fp16_0)[name = tensor("op_3326_cast_fp16")]; + tensor concat_110x = const()[name = tensor("concat_110x"), val = tensor([1, -1, 4, 128])]; + tensor var_3329_cast_fp16 = reshape(shape = concat_110x, x = var_3321_cast_fp16_1)[name = tensor("op_3329_cast_fp16")]; + tensor concat_111x = const()[name = tensor("concat_111x"), val = tensor([1, -1, 4, 128])]; + tensor var_3332_cast_fp16 = reshape(shape = concat_111x, x = var_3321_cast_fp16_2)[name = tensor("op_3332_cast_fp16")]; + tensor value_73_perm_0 = const()[name = tensor("value_73_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_73_cast_fp16 = mul(x = var_3321_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_73_cast_fp16")]; + tensor input_939_perm_0 = const()[name = tensor("input_939_perm_0"), val = tensor([0, 2, 1])]; + tensor input_941_pad_0 = const()[name = tensor("input_941_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_941_mode_0 = const()[name = tensor("input_941_mode_0"), val = tensor("constant")]; + tensor const_81_to_fp16 = const()[name = tensor("const_81_to_fp16"), val = tensor(0x0p+0)]; + tensor input_939_cast_fp16 = transpose(perm = input_939_perm_0, x = inputs_73_cast_fp16)[name = tensor("transpose_332")]; + tensor input_941_cast_fp16 = pad(constant_val = const_81_to_fp16, mode = input_941_mode_0, pad = input_941_pad_0, x = input_939_cast_fp16)[name = tensor("input_941_cast_fp16")]; + tensor x_367_pad_type_0 = const()[name = tensor("x_367_pad_type_0"), val = tensor("valid")]; + tensor x_367_groups_0 = const()[name = tensor("x_367_groups_0"), val = tensor(512)]; + tensor x_367_strides_0 = const()[name = tensor("x_367_strides_0"), val = tensor([1])]; + tensor x_367_pad_0 = const()[name = tensor("x_367_pad_0"), val = tensor([0, 0])]; + tensor x_367_dilations_0 = const()[name = tensor("x_367_dilations_0"), val = tensor([1])]; + tensor e_encoders_35_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_35_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229133760)))]; + tensor x_367_cast_fp16 = conv(dilations = x_367_dilations_0, groups = x_367_groups_0, pad = x_367_pad_0, pad_type = x_367_pad_type_0, strides = x_367_strides_0, weight = e_encoders_35_self_attn_fsmn_block_weight_to_fp16, x = input_941_cast_fp16)[name = tensor("x_367_cast_fp16")]; + tensor x_369_perm_0 = const()[name = tensor("x_369_perm_0"), val = tensor([0, 2, 1])]; + tensor x_369_cast_fp16 = transpose(perm = x_369_perm_0, x = x_367_cast_fp16)[name = tensor("transpose_331")]; + tensor input_943_cast_fp16 = add(x = x_369_cast_fp16, y = inputs_73_cast_fp16)[name = tensor("input_943_cast_fp16")]; + tensor fsmn_memory_73_cast_fp16 = mul(x = input_943_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_73_cast_fp16")]; + tensor var_3351_to_fp16 = const()[name = tensor("op_3351_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_147_cast_fp16 = mul(x = var_3326_cast_fp16, y = var_3351_to_fp16)[name = tensor("q_h_147_cast_fp16")]; + tensor scores_145_transpose_x_0 = const()[name = tensor("scores_145_transpose_x_0"), val = tensor(false)]; + tensor scores_145_transpose_y_0 = const()[name = tensor("scores_145_transpose_y_0"), val = tensor(false)]; + tensor transpose_222_perm_0 = const()[name = tensor("transpose_222_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_223_perm_0 = const()[name = tensor("transpose_223_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_223 = transpose(perm = transpose_223_perm_0, x = var_3329_cast_fp16)[name = tensor("transpose_329")]; + tensor transpose_222 = transpose(perm = transpose_222_perm_0, x = q_h_147_cast_fp16)[name = tensor("transpose_330")]; + tensor scores_145_cast_fp16 = matmul(transpose_x = scores_145_transpose_x_0, transpose_y = scores_145_transpose_y_0, x = transpose_222, y = transpose_223)[name = tensor("scores_145_cast_fp16")]; + tensor scores_147_cast_fp16 = select(a = var_11_to_fp16, b = scores_145_cast_fp16, cond = mask_5)[name = tensor("scores_147_cast_fp16")]; + tensor var_3359_cast_fp16 = softmax(axis = var_20, x = scores_147_cast_fp16)[name = tensor("op_3359_cast_fp16")]; + tensor input_945_cast_fp16 = select(a = var_6_to_fp16, b = var_3359_cast_fp16, cond = mask_5)[name = tensor("input_945_cast_fp16")]; + tensor x_373_transpose_x_0 = const()[name = tensor("x_373_transpose_x_0"), val = tensor(false)]; + tensor x_373_transpose_y_0 = const()[name = tensor("x_373_transpose_y_0"), val = tensor(false)]; + tensor value_73_cast_fp16 = transpose(perm = value_73_perm_0, x = var_3332_cast_fp16)[name = tensor("transpose_333")]; + tensor x_373_cast_fp16 = matmul(transpose_x = x_373_transpose_x_0, transpose_y = x_373_transpose_y_0, x = input_945_cast_fp16, y = value_73_cast_fp16)[name = tensor("x_373_cast_fp16")]; + tensor var_3363_perm_0 = const()[name = tensor("op_3363_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3365 = const()[name = tensor("op_3365"), val = tensor([1, -1, 512])]; + tensor var_3363_cast_fp16 = transpose(perm = var_3363_perm_0, x = x_373_cast_fp16)[name = tensor("transpose_328")]; + tensor input_947_cast_fp16 = reshape(shape = var_3365, x = var_3363_cast_fp16)[name = tensor("input_947_cast_fp16")]; + tensor e_encoders_35_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_35_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229145088)))]; + tensor e_encoders_35_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_35_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229669440)))]; + tensor linear_145_cast_fp16 = linear(bias = e_encoders_35_self_attn_linear_out_bias_to_fp16, weight = e_encoders_35_self_attn_linear_out_weight_to_fp16, x = input_947_cast_fp16)[name = tensor("linear_145_cast_fp16")]; + tensor input_949_cast_fp16 = add(x = linear_145_cast_fp16, y = fsmn_memory_73_cast_fp16)[name = tensor("input_949_cast_fp16")]; + tensor input_951_cast_fp16 = add(x = input_937_cast_fp16, y = input_949_cast_fp16)[name = tensor("input_951_cast_fp16")]; + tensor input_953_axes_0 = const()[name = tensor("input_953_axes_0"), val = tensor([-1])]; + tensor e_encoders_35_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_35_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229670528)))]; + tensor e_encoders_35_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_35_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229671616)))]; + tensor input_953_cast_fp16 = layer_norm(axes = input_953_axes_0, beta = e_encoders_35_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_35_norm2_weight_to_fp16, x = input_951_cast_fp16)[name = tensor("input_953_cast_fp16")]; + tensor e_encoders_35_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_35_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229672704)))]; + tensor e_encoders_35_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_35_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231769920)))]; + tensor linear_146_cast_fp16 = linear(bias = e_encoders_35_feed_forward_w_1_bias_to_fp16, weight = e_encoders_35_feed_forward_w_1_weight_to_fp16, x = input_953_cast_fp16)[name = tensor("linear_146_cast_fp16")]; + tensor input_957_cast_fp16 = relu(x = linear_146_cast_fp16)[name = tensor("input_957_cast_fp16")]; + tensor e_encoders_35_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_35_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231774080)))]; + tensor e_encoders_35_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_35_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233871296)))]; + tensor linear_147_cast_fp16 = linear(bias = e_encoders_35_feed_forward_w_2_bias_to_fp16, weight = e_encoders_35_feed_forward_w_2_weight_to_fp16, x = input_957_cast_fp16)[name = tensor("linear_147_cast_fp16")]; + tensor input_963_cast_fp16 = add(x = input_951_cast_fp16, y = linear_147_cast_fp16)[name = tensor("input_963_cast_fp16")]; + tensor x_375_axes_0 = const()[name = tensor("x_375_axes_0"), val = tensor([-1])]; + tensor e_encoders_36_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_36_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233872384)))]; + tensor e_encoders_36_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_36_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233873472)))]; + tensor x_375_cast_fp16 = layer_norm(axes = x_375_axes_0, beta = e_encoders_36_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_36_norm1_weight_to_fp16, x = input_963_cast_fp16)[name = tensor("x_375_cast_fp16")]; + tensor e_encoders_36_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_36_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233874560)))]; + tensor e_encoders_36_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_36_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235447488)))]; + tensor linear_148_cast_fp16 = linear(bias = e_encoders_36_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_36_self_attn_linear_q_k_v_weight_to_fp16, x = x_375_cast_fp16)[name = tensor("linear_148_cast_fp16")]; + tensor tile_37 = const()[name = tensor("tile_37"), val = tensor([512, 512, 512])]; + tensor var_3409_axis_0 = const()[name = tensor("op_3409_axis_0"), val = tensor(-1)]; + tensor var_3409_cast_fp16_0, tensor var_3409_cast_fp16_1, tensor var_3409_cast_fp16_2 = split(axis = var_3409_axis_0, split_sizes = tile_37, x = linear_148_cast_fp16)[name = tensor("op_3409_cast_fp16")]; + tensor concat_112x = const()[name = tensor("concat_112x"), val = tensor([1, -1, 4, 128])]; + tensor var_3414_cast_fp16 = reshape(shape = concat_112x, x = var_3409_cast_fp16_0)[name = tensor("op_3414_cast_fp16")]; + tensor concat_113x = const()[name = tensor("concat_113x"), val = tensor([1, -1, 4, 128])]; + tensor var_3417_cast_fp16 = reshape(shape = concat_113x, x = var_3409_cast_fp16_1)[name = tensor("op_3417_cast_fp16")]; + tensor concat_114x = const()[name = tensor("concat_114x"), val = tensor([1, -1, 4, 128])]; + tensor var_3420_cast_fp16 = reshape(shape = concat_114x, x = var_3409_cast_fp16_2)[name = tensor("op_3420_cast_fp16")]; + tensor value_75_perm_0 = const()[name = tensor("value_75_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_75_cast_fp16 = mul(x = var_3409_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_75_cast_fp16")]; + tensor input_965_perm_0 = const()[name = tensor("input_965_perm_0"), val = tensor([0, 2, 1])]; + tensor input_967_pad_0 = const()[name = tensor("input_967_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_967_mode_0 = const()[name = tensor("input_967_mode_0"), val = tensor("constant")]; + tensor const_83_to_fp16 = const()[name = tensor("const_83_to_fp16"), val = tensor(0x0p+0)]; + tensor input_965_cast_fp16 = transpose(perm = input_965_perm_0, x = inputs_75_cast_fp16)[name = tensor("transpose_326")]; + tensor input_967_cast_fp16 = pad(constant_val = const_83_to_fp16, mode = input_967_mode_0, pad = input_967_pad_0, x = input_965_cast_fp16)[name = tensor("input_967_cast_fp16")]; + tensor x_377_pad_type_0 = const()[name = tensor("x_377_pad_type_0"), val = tensor("valid")]; + tensor x_377_groups_0 = const()[name = tensor("x_377_groups_0"), val = tensor(512)]; + tensor x_377_strides_0 = const()[name = tensor("x_377_strides_0"), val = tensor([1])]; + tensor x_377_pad_0 = const()[name = tensor("x_377_pad_0"), val = tensor([0, 0])]; + tensor x_377_dilations_0 = const()[name = tensor("x_377_dilations_0"), val = tensor([1])]; + tensor e_encoders_36_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_36_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235450624)))]; + tensor x_377_cast_fp16 = conv(dilations = x_377_dilations_0, groups = x_377_groups_0, pad = x_377_pad_0, pad_type = x_377_pad_type_0, strides = x_377_strides_0, weight = e_encoders_36_self_attn_fsmn_block_weight_to_fp16, x = input_967_cast_fp16)[name = tensor("x_377_cast_fp16")]; + tensor x_379_perm_0 = const()[name = tensor("x_379_perm_0"), val = tensor([0, 2, 1])]; + tensor x_379_cast_fp16 = transpose(perm = x_379_perm_0, x = x_377_cast_fp16)[name = tensor("transpose_325")]; + tensor input_969_cast_fp16 = add(x = x_379_cast_fp16, y = inputs_75_cast_fp16)[name = tensor("input_969_cast_fp16")]; + tensor fsmn_memory_75_cast_fp16 = mul(x = input_969_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_75_cast_fp16")]; + tensor var_3439_to_fp16 = const()[name = tensor("op_3439_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_151_cast_fp16 = mul(x = var_3414_cast_fp16, y = var_3439_to_fp16)[name = tensor("q_h_151_cast_fp16")]; + tensor scores_149_transpose_x_0 = const()[name = tensor("scores_149_transpose_x_0"), val = tensor(false)]; + tensor scores_149_transpose_y_0 = const()[name = tensor("scores_149_transpose_y_0"), val = tensor(false)]; + tensor transpose_224_perm_0 = const()[name = tensor("transpose_224_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_225_perm_0 = const()[name = tensor("transpose_225_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_225 = transpose(perm = transpose_225_perm_0, x = var_3417_cast_fp16)[name = tensor("transpose_323")]; + tensor transpose_224 = transpose(perm = transpose_224_perm_0, x = q_h_151_cast_fp16)[name = tensor("transpose_324")]; + tensor scores_149_cast_fp16 = matmul(transpose_x = scores_149_transpose_x_0, transpose_y = scores_149_transpose_y_0, x = transpose_224, y = transpose_225)[name = tensor("scores_149_cast_fp16")]; + tensor scores_151_cast_fp16 = select(a = var_11_to_fp16, b = scores_149_cast_fp16, cond = mask_5)[name = tensor("scores_151_cast_fp16")]; + tensor var_3447_cast_fp16 = softmax(axis = var_20, x = scores_151_cast_fp16)[name = tensor("op_3447_cast_fp16")]; + tensor input_971_cast_fp16 = select(a = var_6_to_fp16, b = var_3447_cast_fp16, cond = mask_5)[name = tensor("input_971_cast_fp16")]; + tensor x_383_transpose_x_0 = const()[name = tensor("x_383_transpose_x_0"), val = tensor(false)]; + tensor x_383_transpose_y_0 = const()[name = tensor("x_383_transpose_y_0"), val = tensor(false)]; + tensor value_75_cast_fp16 = transpose(perm = value_75_perm_0, x = var_3420_cast_fp16)[name = tensor("transpose_327")]; + tensor x_383_cast_fp16 = matmul(transpose_x = x_383_transpose_x_0, transpose_y = x_383_transpose_y_0, x = input_971_cast_fp16, y = value_75_cast_fp16)[name = tensor("x_383_cast_fp16")]; + tensor var_3451_perm_0 = const()[name = tensor("op_3451_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3453 = const()[name = tensor("op_3453"), val = tensor([1, -1, 512])]; + tensor var_3451_cast_fp16 = transpose(perm = var_3451_perm_0, x = x_383_cast_fp16)[name = tensor("transpose_322")]; + tensor input_973_cast_fp16 = reshape(shape = var_3453, x = var_3451_cast_fp16)[name = tensor("input_973_cast_fp16")]; + tensor e_encoders_36_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_36_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235461952)))]; + tensor e_encoders_36_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_36_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235986304)))]; + tensor linear_149_cast_fp16 = linear(bias = e_encoders_36_self_attn_linear_out_bias_to_fp16, weight = e_encoders_36_self_attn_linear_out_weight_to_fp16, x = input_973_cast_fp16)[name = tensor("linear_149_cast_fp16")]; + tensor input_975_cast_fp16 = add(x = linear_149_cast_fp16, y = fsmn_memory_75_cast_fp16)[name = tensor("input_975_cast_fp16")]; + tensor input_977_cast_fp16 = add(x = input_963_cast_fp16, y = input_975_cast_fp16)[name = tensor("input_977_cast_fp16")]; + tensor input_979_axes_0 = const()[name = tensor("input_979_axes_0"), val = tensor([-1])]; + tensor e_encoders_36_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_36_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235987392)))]; + tensor e_encoders_36_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_36_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235988480)))]; + tensor input_979_cast_fp16 = layer_norm(axes = input_979_axes_0, beta = e_encoders_36_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_36_norm2_weight_to_fp16, x = input_977_cast_fp16)[name = tensor("input_979_cast_fp16")]; + tensor e_encoders_36_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_36_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235989568)))]; + tensor e_encoders_36_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_36_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238086784)))]; + tensor linear_150_cast_fp16 = linear(bias = e_encoders_36_feed_forward_w_1_bias_to_fp16, weight = e_encoders_36_feed_forward_w_1_weight_to_fp16, x = input_979_cast_fp16)[name = tensor("linear_150_cast_fp16")]; + tensor input_983_cast_fp16 = relu(x = linear_150_cast_fp16)[name = tensor("input_983_cast_fp16")]; + tensor e_encoders_36_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_36_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238090944)))]; + tensor e_encoders_36_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_36_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240188160)))]; + tensor linear_151_cast_fp16 = linear(bias = e_encoders_36_feed_forward_w_2_bias_to_fp16, weight = e_encoders_36_feed_forward_w_2_weight_to_fp16, x = input_983_cast_fp16)[name = tensor("linear_151_cast_fp16")]; + tensor input_989_cast_fp16 = add(x = input_977_cast_fp16, y = linear_151_cast_fp16)[name = tensor("input_989_cast_fp16")]; + tensor x_385_axes_0 = const()[name = tensor("x_385_axes_0"), val = tensor([-1])]; + tensor e_encoders_37_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_37_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240189248)))]; + tensor e_encoders_37_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_37_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240190336)))]; + tensor x_385_cast_fp16 = layer_norm(axes = x_385_axes_0, beta = e_encoders_37_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_37_norm1_weight_to_fp16, x = input_989_cast_fp16)[name = tensor("x_385_cast_fp16")]; + tensor e_encoders_37_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_37_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240191424)))]; + tensor e_encoders_37_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_37_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241764352)))]; + tensor linear_152_cast_fp16 = linear(bias = e_encoders_37_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_37_self_attn_linear_q_k_v_weight_to_fp16, x = x_385_cast_fp16)[name = tensor("linear_152_cast_fp16")]; + tensor tile_38 = const()[name = tensor("tile_38"), val = tensor([512, 512, 512])]; + tensor var_3497_axis_0 = const()[name = tensor("op_3497_axis_0"), val = tensor(-1)]; + tensor var_3497_cast_fp16_0, tensor var_3497_cast_fp16_1, tensor var_3497_cast_fp16_2 = split(axis = var_3497_axis_0, split_sizes = tile_38, x = linear_152_cast_fp16)[name = tensor("op_3497_cast_fp16")]; + tensor concat_115x = const()[name = tensor("concat_115x"), val = tensor([1, -1, 4, 128])]; + tensor var_3502_cast_fp16 = reshape(shape = concat_115x, x = var_3497_cast_fp16_0)[name = tensor("op_3502_cast_fp16")]; + tensor concat_116x = const()[name = tensor("concat_116x"), val = tensor([1, -1, 4, 128])]; + tensor var_3505_cast_fp16 = reshape(shape = concat_116x, x = var_3497_cast_fp16_1)[name = tensor("op_3505_cast_fp16")]; + tensor concat_117x = const()[name = tensor("concat_117x"), val = tensor([1, -1, 4, 128])]; + tensor var_3508_cast_fp16 = reshape(shape = concat_117x, x = var_3497_cast_fp16_2)[name = tensor("op_3508_cast_fp16")]; + tensor value_77_perm_0 = const()[name = tensor("value_77_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_77_cast_fp16 = mul(x = var_3497_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_77_cast_fp16")]; + tensor input_991_perm_0 = const()[name = tensor("input_991_perm_0"), val = tensor([0, 2, 1])]; + tensor input_993_pad_0 = const()[name = tensor("input_993_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_993_mode_0 = const()[name = tensor("input_993_mode_0"), val = tensor("constant")]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(0x0p+0)]; + tensor input_991_cast_fp16 = transpose(perm = input_991_perm_0, x = inputs_77_cast_fp16)[name = tensor("transpose_320")]; + tensor input_993_cast_fp16 = pad(constant_val = const_85_to_fp16, mode = input_993_mode_0, pad = input_993_pad_0, x = input_991_cast_fp16)[name = tensor("input_993_cast_fp16")]; + tensor x_387_pad_type_0 = const()[name = tensor("x_387_pad_type_0"), val = tensor("valid")]; + tensor x_387_groups_0 = const()[name = tensor("x_387_groups_0"), val = tensor(512)]; + tensor x_387_strides_0 = const()[name = tensor("x_387_strides_0"), val = tensor([1])]; + tensor x_387_pad_0 = const()[name = tensor("x_387_pad_0"), val = tensor([0, 0])]; + tensor x_387_dilations_0 = const()[name = tensor("x_387_dilations_0"), val = tensor([1])]; + tensor e_encoders_37_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_37_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241767488)))]; + tensor x_387_cast_fp16 = conv(dilations = x_387_dilations_0, groups = x_387_groups_0, pad = x_387_pad_0, pad_type = x_387_pad_type_0, strides = x_387_strides_0, weight = e_encoders_37_self_attn_fsmn_block_weight_to_fp16, x = input_993_cast_fp16)[name = tensor("x_387_cast_fp16")]; + tensor x_389_perm_0 = const()[name = tensor("x_389_perm_0"), val = tensor([0, 2, 1])]; + tensor x_389_cast_fp16 = transpose(perm = x_389_perm_0, x = x_387_cast_fp16)[name = tensor("transpose_319")]; + tensor input_995_cast_fp16 = add(x = x_389_cast_fp16, y = inputs_77_cast_fp16)[name = tensor("input_995_cast_fp16")]; + tensor fsmn_memory_77_cast_fp16 = mul(x = input_995_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_77_cast_fp16")]; + tensor var_3527_to_fp16 = const()[name = tensor("op_3527_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_155_cast_fp16 = mul(x = var_3502_cast_fp16, y = var_3527_to_fp16)[name = tensor("q_h_155_cast_fp16")]; + tensor scores_153_transpose_x_0 = const()[name = tensor("scores_153_transpose_x_0"), val = tensor(false)]; + tensor scores_153_transpose_y_0 = const()[name = tensor("scores_153_transpose_y_0"), val = tensor(false)]; + tensor transpose_226_perm_0 = const()[name = tensor("transpose_226_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_227_perm_0 = const()[name = tensor("transpose_227_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_227 = transpose(perm = transpose_227_perm_0, x = var_3505_cast_fp16)[name = tensor("transpose_317")]; + tensor transpose_226 = transpose(perm = transpose_226_perm_0, x = q_h_155_cast_fp16)[name = tensor("transpose_318")]; + tensor scores_153_cast_fp16 = matmul(transpose_x = scores_153_transpose_x_0, transpose_y = scores_153_transpose_y_0, x = transpose_226, y = transpose_227)[name = tensor("scores_153_cast_fp16")]; + tensor scores_155_cast_fp16 = select(a = var_11_to_fp16, b = scores_153_cast_fp16, cond = mask_5)[name = tensor("scores_155_cast_fp16")]; + tensor var_3535_cast_fp16 = softmax(axis = var_20, x = scores_155_cast_fp16)[name = tensor("op_3535_cast_fp16")]; + tensor input_997_cast_fp16 = select(a = var_6_to_fp16, b = var_3535_cast_fp16, cond = mask_5)[name = tensor("input_997_cast_fp16")]; + tensor x_393_transpose_x_0 = const()[name = tensor("x_393_transpose_x_0"), val = tensor(false)]; + tensor x_393_transpose_y_0 = const()[name = tensor("x_393_transpose_y_0"), val = tensor(false)]; + tensor value_77_cast_fp16 = transpose(perm = value_77_perm_0, x = var_3508_cast_fp16)[name = tensor("transpose_321")]; + tensor x_393_cast_fp16 = matmul(transpose_x = x_393_transpose_x_0, transpose_y = x_393_transpose_y_0, x = input_997_cast_fp16, y = value_77_cast_fp16)[name = tensor("x_393_cast_fp16")]; + tensor var_3539_perm_0 = const()[name = tensor("op_3539_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3541 = const()[name = tensor("op_3541"), val = tensor([1, -1, 512])]; + tensor var_3539_cast_fp16 = transpose(perm = var_3539_perm_0, x = x_393_cast_fp16)[name = tensor("transpose_316")]; + tensor input_999_cast_fp16 = reshape(shape = var_3541, x = var_3539_cast_fp16)[name = tensor("input_999_cast_fp16")]; + tensor e_encoders_37_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_37_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241778816)))]; + tensor e_encoders_37_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_37_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242303168)))]; + tensor linear_153_cast_fp16 = linear(bias = e_encoders_37_self_attn_linear_out_bias_to_fp16, weight = e_encoders_37_self_attn_linear_out_weight_to_fp16, x = input_999_cast_fp16)[name = tensor("linear_153_cast_fp16")]; + tensor input_1001_cast_fp16 = add(x = linear_153_cast_fp16, y = fsmn_memory_77_cast_fp16)[name = tensor("input_1001_cast_fp16")]; + tensor input_1003_cast_fp16 = add(x = input_989_cast_fp16, y = input_1001_cast_fp16)[name = tensor("input_1003_cast_fp16")]; + tensor input_1005_axes_0 = const()[name = tensor("input_1005_axes_0"), val = tensor([-1])]; + tensor e_encoders_37_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_37_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242304256)))]; + tensor e_encoders_37_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_37_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242305344)))]; + tensor input_1005_cast_fp16 = layer_norm(axes = input_1005_axes_0, beta = e_encoders_37_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_37_norm2_weight_to_fp16, x = input_1003_cast_fp16)[name = tensor("input_1005_cast_fp16")]; + tensor e_encoders_37_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_37_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242306432)))]; + tensor e_encoders_37_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_37_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244403648)))]; + tensor linear_154_cast_fp16 = linear(bias = e_encoders_37_feed_forward_w_1_bias_to_fp16, weight = e_encoders_37_feed_forward_w_1_weight_to_fp16, x = input_1005_cast_fp16)[name = tensor("linear_154_cast_fp16")]; + tensor input_1009_cast_fp16 = relu(x = linear_154_cast_fp16)[name = tensor("input_1009_cast_fp16")]; + tensor e_encoders_37_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_37_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244407808)))]; + tensor e_encoders_37_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_37_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246505024)))]; + tensor linear_155_cast_fp16 = linear(bias = e_encoders_37_feed_forward_w_2_bias_to_fp16, weight = e_encoders_37_feed_forward_w_2_weight_to_fp16, x = input_1009_cast_fp16)[name = tensor("linear_155_cast_fp16")]; + tensor input_1015_cast_fp16 = add(x = input_1003_cast_fp16, y = linear_155_cast_fp16)[name = tensor("input_1015_cast_fp16")]; + tensor x_395_axes_0 = const()[name = tensor("x_395_axes_0"), val = tensor([-1])]; + tensor e_encoders_38_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_38_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246506112)))]; + tensor e_encoders_38_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_38_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246507200)))]; + tensor x_395_cast_fp16 = layer_norm(axes = x_395_axes_0, beta = e_encoders_38_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_38_norm1_weight_to_fp16, x = input_1015_cast_fp16)[name = tensor("x_395_cast_fp16")]; + tensor e_encoders_38_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_38_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246508288)))]; + tensor e_encoders_38_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_38_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248081216)))]; + tensor linear_156_cast_fp16 = linear(bias = e_encoders_38_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_38_self_attn_linear_q_k_v_weight_to_fp16, x = x_395_cast_fp16)[name = tensor("linear_156_cast_fp16")]; + tensor tile_39 = const()[name = tensor("tile_39"), val = tensor([512, 512, 512])]; + tensor var_3585_axis_0 = const()[name = tensor("op_3585_axis_0"), val = tensor(-1)]; + tensor var_3585_cast_fp16_0, tensor var_3585_cast_fp16_1, tensor var_3585_cast_fp16_2 = split(axis = var_3585_axis_0, split_sizes = tile_39, x = linear_156_cast_fp16)[name = tensor("op_3585_cast_fp16")]; + tensor concat_118x = const()[name = tensor("concat_118x"), val = tensor([1, -1, 4, 128])]; + tensor var_3590_cast_fp16 = reshape(shape = concat_118x, x = var_3585_cast_fp16_0)[name = tensor("op_3590_cast_fp16")]; + tensor concat_119x = const()[name = tensor("concat_119x"), val = tensor([1, -1, 4, 128])]; + tensor var_3593_cast_fp16 = reshape(shape = concat_119x, x = var_3585_cast_fp16_1)[name = tensor("op_3593_cast_fp16")]; + tensor concat_120x = const()[name = tensor("concat_120x"), val = tensor([1, -1, 4, 128])]; + tensor var_3596_cast_fp16 = reshape(shape = concat_120x, x = var_3585_cast_fp16_2)[name = tensor("op_3596_cast_fp16")]; + tensor value_79_perm_0 = const()[name = tensor("value_79_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_79_cast_fp16 = mul(x = var_3585_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_79_cast_fp16")]; + tensor input_1017_perm_0 = const()[name = tensor("input_1017_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1019_pad_0 = const()[name = tensor("input_1019_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1019_mode_0 = const()[name = tensor("input_1019_mode_0"), val = tensor("constant")]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1017_cast_fp16 = transpose(perm = input_1017_perm_0, x = inputs_79_cast_fp16)[name = tensor("transpose_314")]; + tensor input_1019_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_1019_mode_0, pad = input_1019_pad_0, x = input_1017_cast_fp16)[name = tensor("input_1019_cast_fp16")]; + tensor x_397_pad_type_0 = const()[name = tensor("x_397_pad_type_0"), val = tensor("valid")]; + tensor x_397_groups_0 = const()[name = tensor("x_397_groups_0"), val = tensor(512)]; + tensor x_397_strides_0 = const()[name = tensor("x_397_strides_0"), val = tensor([1])]; + tensor x_397_pad_0 = const()[name = tensor("x_397_pad_0"), val = tensor([0, 0])]; + tensor x_397_dilations_0 = const()[name = tensor("x_397_dilations_0"), val = tensor([1])]; + tensor e_encoders_38_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_38_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248084352)))]; + tensor x_397_cast_fp16 = conv(dilations = x_397_dilations_0, groups = x_397_groups_0, pad = x_397_pad_0, pad_type = x_397_pad_type_0, strides = x_397_strides_0, weight = e_encoders_38_self_attn_fsmn_block_weight_to_fp16, x = input_1019_cast_fp16)[name = tensor("x_397_cast_fp16")]; + tensor x_399_perm_0 = const()[name = tensor("x_399_perm_0"), val = tensor([0, 2, 1])]; + tensor x_399_cast_fp16 = transpose(perm = x_399_perm_0, x = x_397_cast_fp16)[name = tensor("transpose_313")]; + tensor input_1021_cast_fp16 = add(x = x_399_cast_fp16, y = inputs_79_cast_fp16)[name = tensor("input_1021_cast_fp16")]; + tensor fsmn_memory_79_cast_fp16 = mul(x = input_1021_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_79_cast_fp16")]; + tensor var_3615_to_fp16 = const()[name = tensor("op_3615_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_159_cast_fp16 = mul(x = var_3590_cast_fp16, y = var_3615_to_fp16)[name = tensor("q_h_159_cast_fp16")]; + tensor scores_157_transpose_x_0 = const()[name = tensor("scores_157_transpose_x_0"), val = tensor(false)]; + tensor scores_157_transpose_y_0 = const()[name = tensor("scores_157_transpose_y_0"), val = tensor(false)]; + tensor transpose_228_perm_0 = const()[name = tensor("transpose_228_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_229_perm_0 = const()[name = tensor("transpose_229_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_229 = transpose(perm = transpose_229_perm_0, x = var_3593_cast_fp16)[name = tensor("transpose_311")]; + tensor transpose_228 = transpose(perm = transpose_228_perm_0, x = q_h_159_cast_fp16)[name = tensor("transpose_312")]; + tensor scores_157_cast_fp16 = matmul(transpose_x = scores_157_transpose_x_0, transpose_y = scores_157_transpose_y_0, x = transpose_228, y = transpose_229)[name = tensor("scores_157_cast_fp16")]; + tensor scores_159_cast_fp16 = select(a = var_11_to_fp16, b = scores_157_cast_fp16, cond = mask_5)[name = tensor("scores_159_cast_fp16")]; + tensor var_3623_cast_fp16 = softmax(axis = var_20, x = scores_159_cast_fp16)[name = tensor("op_3623_cast_fp16")]; + tensor input_1023_cast_fp16 = select(a = var_6_to_fp16, b = var_3623_cast_fp16, cond = mask_5)[name = tensor("input_1023_cast_fp16")]; + tensor x_403_transpose_x_0 = const()[name = tensor("x_403_transpose_x_0"), val = tensor(false)]; + tensor x_403_transpose_y_0 = const()[name = tensor("x_403_transpose_y_0"), val = tensor(false)]; + tensor value_79_cast_fp16 = transpose(perm = value_79_perm_0, x = var_3596_cast_fp16)[name = tensor("transpose_315")]; + tensor x_403_cast_fp16 = matmul(transpose_x = x_403_transpose_x_0, transpose_y = x_403_transpose_y_0, x = input_1023_cast_fp16, y = value_79_cast_fp16)[name = tensor("x_403_cast_fp16")]; + tensor var_3627_perm_0 = const()[name = tensor("op_3627_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3629 = const()[name = tensor("op_3629"), val = tensor([1, -1, 512])]; + tensor var_3627_cast_fp16 = transpose(perm = var_3627_perm_0, x = x_403_cast_fp16)[name = tensor("transpose_310")]; + tensor input_1025_cast_fp16 = reshape(shape = var_3629, x = var_3627_cast_fp16)[name = tensor("input_1025_cast_fp16")]; + tensor e_encoders_38_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_38_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248095680)))]; + tensor e_encoders_38_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_38_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248620032)))]; + tensor linear_157_cast_fp16 = linear(bias = e_encoders_38_self_attn_linear_out_bias_to_fp16, weight = e_encoders_38_self_attn_linear_out_weight_to_fp16, x = input_1025_cast_fp16)[name = tensor("linear_157_cast_fp16")]; + tensor input_1027_cast_fp16 = add(x = linear_157_cast_fp16, y = fsmn_memory_79_cast_fp16)[name = tensor("input_1027_cast_fp16")]; + tensor input_1029_cast_fp16 = add(x = input_1015_cast_fp16, y = input_1027_cast_fp16)[name = tensor("input_1029_cast_fp16")]; + tensor input_1031_axes_0 = const()[name = tensor("input_1031_axes_0"), val = tensor([-1])]; + tensor e_encoders_38_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_38_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248621120)))]; + tensor e_encoders_38_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_38_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248622208)))]; + tensor input_1031_cast_fp16 = layer_norm(axes = input_1031_axes_0, beta = e_encoders_38_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_38_norm2_weight_to_fp16, x = input_1029_cast_fp16)[name = tensor("input_1031_cast_fp16")]; + tensor e_encoders_38_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_38_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248623296)))]; + tensor e_encoders_38_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_38_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250720512)))]; + tensor linear_158_cast_fp16 = linear(bias = e_encoders_38_feed_forward_w_1_bias_to_fp16, weight = e_encoders_38_feed_forward_w_1_weight_to_fp16, x = input_1031_cast_fp16)[name = tensor("linear_158_cast_fp16")]; + tensor input_1035_cast_fp16 = relu(x = linear_158_cast_fp16)[name = tensor("input_1035_cast_fp16")]; + tensor e_encoders_38_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_38_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250724672)))]; + tensor e_encoders_38_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_38_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252821888)))]; + tensor linear_159_cast_fp16 = linear(bias = e_encoders_38_feed_forward_w_2_bias_to_fp16, weight = e_encoders_38_feed_forward_w_2_weight_to_fp16, x = input_1035_cast_fp16)[name = tensor("linear_159_cast_fp16")]; + tensor input_1041_cast_fp16 = add(x = input_1029_cast_fp16, y = linear_159_cast_fp16)[name = tensor("input_1041_cast_fp16")]; + tensor x_405_axes_0 = const()[name = tensor("x_405_axes_0"), val = tensor([-1])]; + tensor e_encoders_39_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_39_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252822976)))]; + tensor e_encoders_39_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_39_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252824064)))]; + tensor x_405_cast_fp16 = layer_norm(axes = x_405_axes_0, beta = e_encoders_39_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_39_norm1_weight_to_fp16, x = input_1041_cast_fp16)[name = tensor("x_405_cast_fp16")]; + tensor e_encoders_39_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_39_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252825152)))]; + tensor e_encoders_39_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_39_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254398080)))]; + tensor linear_160_cast_fp16 = linear(bias = e_encoders_39_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_39_self_attn_linear_q_k_v_weight_to_fp16, x = x_405_cast_fp16)[name = tensor("linear_160_cast_fp16")]; + tensor tile_40 = const()[name = tensor("tile_40"), val = tensor([512, 512, 512])]; + tensor var_3673_axis_0 = const()[name = tensor("op_3673_axis_0"), val = tensor(-1)]; + tensor var_3673_cast_fp16_0, tensor var_3673_cast_fp16_1, tensor var_3673_cast_fp16_2 = split(axis = var_3673_axis_0, split_sizes = tile_40, x = linear_160_cast_fp16)[name = tensor("op_3673_cast_fp16")]; + tensor concat_121x = const()[name = tensor("concat_121x"), val = tensor([1, -1, 4, 128])]; + tensor var_3678_cast_fp16 = reshape(shape = concat_121x, x = var_3673_cast_fp16_0)[name = tensor("op_3678_cast_fp16")]; + tensor concat_122x = const()[name = tensor("concat_122x"), val = tensor([1, -1, 4, 128])]; + tensor var_3681_cast_fp16 = reshape(shape = concat_122x, x = var_3673_cast_fp16_1)[name = tensor("op_3681_cast_fp16")]; + tensor concat_123x = const()[name = tensor("concat_123x"), val = tensor([1, -1, 4, 128])]; + tensor var_3684_cast_fp16 = reshape(shape = concat_123x, x = var_3673_cast_fp16_2)[name = tensor("op_3684_cast_fp16")]; + tensor value_81_perm_0 = const()[name = tensor("value_81_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_81_cast_fp16 = mul(x = var_3673_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_81_cast_fp16")]; + tensor input_1043_perm_0 = const()[name = tensor("input_1043_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1045_pad_0 = const()[name = tensor("input_1045_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1045_mode_0 = const()[name = tensor("input_1045_mode_0"), val = tensor("constant")]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1043_cast_fp16 = transpose(perm = input_1043_perm_0, x = inputs_81_cast_fp16)[name = tensor("transpose_308")]; + tensor input_1045_cast_fp16 = pad(constant_val = const_89_to_fp16, mode = input_1045_mode_0, pad = input_1045_pad_0, x = input_1043_cast_fp16)[name = tensor("input_1045_cast_fp16")]; + tensor x_407_pad_type_0 = const()[name = tensor("x_407_pad_type_0"), val = tensor("valid")]; + tensor x_407_groups_0 = const()[name = tensor("x_407_groups_0"), val = tensor(512)]; + tensor x_407_strides_0 = const()[name = tensor("x_407_strides_0"), val = tensor([1])]; + tensor x_407_pad_0 = const()[name = tensor("x_407_pad_0"), val = tensor([0, 0])]; + tensor x_407_dilations_0 = const()[name = tensor("x_407_dilations_0"), val = tensor([1])]; + tensor e_encoders_39_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_39_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254401216)))]; + tensor x_407_cast_fp16 = conv(dilations = x_407_dilations_0, groups = x_407_groups_0, pad = x_407_pad_0, pad_type = x_407_pad_type_0, strides = x_407_strides_0, weight = e_encoders_39_self_attn_fsmn_block_weight_to_fp16, x = input_1045_cast_fp16)[name = tensor("x_407_cast_fp16")]; + tensor x_409_perm_0 = const()[name = tensor("x_409_perm_0"), val = tensor([0, 2, 1])]; + tensor x_409_cast_fp16 = transpose(perm = x_409_perm_0, x = x_407_cast_fp16)[name = tensor("transpose_307")]; + tensor input_1047_cast_fp16 = add(x = x_409_cast_fp16, y = inputs_81_cast_fp16)[name = tensor("input_1047_cast_fp16")]; + tensor fsmn_memory_81_cast_fp16 = mul(x = input_1047_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_81_cast_fp16")]; + tensor var_3703_to_fp16 = const()[name = tensor("op_3703_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_163_cast_fp16 = mul(x = var_3678_cast_fp16, y = var_3703_to_fp16)[name = tensor("q_h_163_cast_fp16")]; + tensor scores_161_transpose_x_0 = const()[name = tensor("scores_161_transpose_x_0"), val = tensor(false)]; + tensor scores_161_transpose_y_0 = const()[name = tensor("scores_161_transpose_y_0"), val = tensor(false)]; + tensor transpose_230_perm_0 = const()[name = tensor("transpose_230_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_231_perm_0 = const()[name = tensor("transpose_231_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_231 = transpose(perm = transpose_231_perm_0, x = var_3681_cast_fp16)[name = tensor("transpose_305")]; + tensor transpose_230 = transpose(perm = transpose_230_perm_0, x = q_h_163_cast_fp16)[name = tensor("transpose_306")]; + tensor scores_161_cast_fp16 = matmul(transpose_x = scores_161_transpose_x_0, transpose_y = scores_161_transpose_y_0, x = transpose_230, y = transpose_231)[name = tensor("scores_161_cast_fp16")]; + tensor scores_163_cast_fp16 = select(a = var_11_to_fp16, b = scores_161_cast_fp16, cond = mask_5)[name = tensor("scores_163_cast_fp16")]; + tensor var_3711_cast_fp16 = softmax(axis = var_20, x = scores_163_cast_fp16)[name = tensor("op_3711_cast_fp16")]; + tensor input_1049_cast_fp16 = select(a = var_6_to_fp16, b = var_3711_cast_fp16, cond = mask_5)[name = tensor("input_1049_cast_fp16")]; + tensor x_413_transpose_x_0 = const()[name = tensor("x_413_transpose_x_0"), val = tensor(false)]; + tensor x_413_transpose_y_0 = const()[name = tensor("x_413_transpose_y_0"), val = tensor(false)]; + tensor value_81_cast_fp16 = transpose(perm = value_81_perm_0, x = var_3684_cast_fp16)[name = tensor("transpose_309")]; + tensor x_413_cast_fp16 = matmul(transpose_x = x_413_transpose_x_0, transpose_y = x_413_transpose_y_0, x = input_1049_cast_fp16, y = value_81_cast_fp16)[name = tensor("x_413_cast_fp16")]; + tensor var_3715_perm_0 = const()[name = tensor("op_3715_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3717 = const()[name = tensor("op_3717"), val = tensor([1, -1, 512])]; + tensor var_3715_cast_fp16 = transpose(perm = var_3715_perm_0, x = x_413_cast_fp16)[name = tensor("transpose_304")]; + tensor input_1051_cast_fp16 = reshape(shape = var_3717, x = var_3715_cast_fp16)[name = tensor("input_1051_cast_fp16")]; + tensor e_encoders_39_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_39_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254412544)))]; + tensor e_encoders_39_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_39_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254936896)))]; + tensor linear_161_cast_fp16 = linear(bias = e_encoders_39_self_attn_linear_out_bias_to_fp16, weight = e_encoders_39_self_attn_linear_out_weight_to_fp16, x = input_1051_cast_fp16)[name = tensor("linear_161_cast_fp16")]; + tensor input_1053_cast_fp16 = add(x = linear_161_cast_fp16, y = fsmn_memory_81_cast_fp16)[name = tensor("input_1053_cast_fp16")]; + tensor input_1055_cast_fp16 = add(x = input_1041_cast_fp16, y = input_1053_cast_fp16)[name = tensor("input_1055_cast_fp16")]; + tensor input_1057_axes_0 = const()[name = tensor("input_1057_axes_0"), val = tensor([-1])]; + tensor e_encoders_39_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_39_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254937984)))]; + tensor e_encoders_39_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_39_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254939072)))]; + tensor input_1057_cast_fp16 = layer_norm(axes = input_1057_axes_0, beta = e_encoders_39_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_39_norm2_weight_to_fp16, x = input_1055_cast_fp16)[name = tensor("input_1057_cast_fp16")]; + tensor e_encoders_39_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_39_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254940160)))]; + tensor e_encoders_39_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_39_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257037376)))]; + tensor linear_162_cast_fp16 = linear(bias = e_encoders_39_feed_forward_w_1_bias_to_fp16, weight = e_encoders_39_feed_forward_w_1_weight_to_fp16, x = input_1057_cast_fp16)[name = tensor("linear_162_cast_fp16")]; + tensor input_1061_cast_fp16 = relu(x = linear_162_cast_fp16)[name = tensor("input_1061_cast_fp16")]; + tensor e_encoders_39_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_39_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257041536)))]; + tensor e_encoders_39_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_39_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259138752)))]; + tensor linear_163_cast_fp16 = linear(bias = e_encoders_39_feed_forward_w_2_bias_to_fp16, weight = e_encoders_39_feed_forward_w_2_weight_to_fp16, x = input_1061_cast_fp16)[name = tensor("linear_163_cast_fp16")]; + tensor input_1067_cast_fp16 = add(x = input_1055_cast_fp16, y = linear_163_cast_fp16)[name = tensor("input_1067_cast_fp16")]; + tensor x_415_axes_0 = const()[name = tensor("x_415_axes_0"), val = tensor([-1])]; + tensor e_encoders_40_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_40_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259139840)))]; + tensor e_encoders_40_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_40_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259140928)))]; + tensor x_415_cast_fp16 = layer_norm(axes = x_415_axes_0, beta = e_encoders_40_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_40_norm1_weight_to_fp16, x = input_1067_cast_fp16)[name = tensor("x_415_cast_fp16")]; + tensor e_encoders_40_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_40_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259142016)))]; + tensor e_encoders_40_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_40_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260714944)))]; + tensor linear_164_cast_fp16 = linear(bias = e_encoders_40_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_40_self_attn_linear_q_k_v_weight_to_fp16, x = x_415_cast_fp16)[name = tensor("linear_164_cast_fp16")]; + tensor tile_41 = const()[name = tensor("tile_41"), val = tensor([512, 512, 512])]; + tensor var_3761_axis_0 = const()[name = tensor("op_3761_axis_0"), val = tensor(-1)]; + tensor var_3761_cast_fp16_0, tensor var_3761_cast_fp16_1, tensor var_3761_cast_fp16_2 = split(axis = var_3761_axis_0, split_sizes = tile_41, x = linear_164_cast_fp16)[name = tensor("op_3761_cast_fp16")]; + tensor concat_124x = const()[name = tensor("concat_124x"), val = tensor([1, -1, 4, 128])]; + tensor var_3766_cast_fp16 = reshape(shape = concat_124x, x = var_3761_cast_fp16_0)[name = tensor("op_3766_cast_fp16")]; + tensor concat_125x = const()[name = tensor("concat_125x"), val = tensor([1, -1, 4, 128])]; + tensor var_3769_cast_fp16 = reshape(shape = concat_125x, x = var_3761_cast_fp16_1)[name = tensor("op_3769_cast_fp16")]; + tensor concat_126x = const()[name = tensor("concat_126x"), val = tensor([1, -1, 4, 128])]; + tensor var_3772_cast_fp16 = reshape(shape = concat_126x, x = var_3761_cast_fp16_2)[name = tensor("op_3772_cast_fp16")]; + tensor value_83_perm_0 = const()[name = tensor("value_83_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_83_cast_fp16 = mul(x = var_3761_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_83_cast_fp16")]; + tensor input_1069_perm_0 = const()[name = tensor("input_1069_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1071_pad_0 = const()[name = tensor("input_1071_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1071_mode_0 = const()[name = tensor("input_1071_mode_0"), val = tensor("constant")]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1069_cast_fp16 = transpose(perm = input_1069_perm_0, x = inputs_83_cast_fp16)[name = tensor("transpose_302")]; + tensor input_1071_cast_fp16 = pad(constant_val = const_91_to_fp16, mode = input_1071_mode_0, pad = input_1071_pad_0, x = input_1069_cast_fp16)[name = tensor("input_1071_cast_fp16")]; + tensor x_417_pad_type_0 = const()[name = tensor("x_417_pad_type_0"), val = tensor("valid")]; + tensor x_417_groups_0 = const()[name = tensor("x_417_groups_0"), val = tensor(512)]; + tensor x_417_strides_0 = const()[name = tensor("x_417_strides_0"), val = tensor([1])]; + tensor x_417_pad_0 = const()[name = tensor("x_417_pad_0"), val = tensor([0, 0])]; + tensor x_417_dilations_0 = const()[name = tensor("x_417_dilations_0"), val = tensor([1])]; + tensor e_encoders_40_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_40_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260718080)))]; + tensor x_417_cast_fp16 = conv(dilations = x_417_dilations_0, groups = x_417_groups_0, pad = x_417_pad_0, pad_type = x_417_pad_type_0, strides = x_417_strides_0, weight = e_encoders_40_self_attn_fsmn_block_weight_to_fp16, x = input_1071_cast_fp16)[name = tensor("x_417_cast_fp16")]; + tensor x_419_perm_0 = const()[name = tensor("x_419_perm_0"), val = tensor([0, 2, 1])]; + tensor x_419_cast_fp16 = transpose(perm = x_419_perm_0, x = x_417_cast_fp16)[name = tensor("transpose_301")]; + tensor input_1073_cast_fp16 = add(x = x_419_cast_fp16, y = inputs_83_cast_fp16)[name = tensor("input_1073_cast_fp16")]; + tensor fsmn_memory_83_cast_fp16 = mul(x = input_1073_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_83_cast_fp16")]; + tensor var_3791_to_fp16 = const()[name = tensor("op_3791_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_167_cast_fp16 = mul(x = var_3766_cast_fp16, y = var_3791_to_fp16)[name = tensor("q_h_167_cast_fp16")]; + tensor scores_165_transpose_x_0 = const()[name = tensor("scores_165_transpose_x_0"), val = tensor(false)]; + tensor scores_165_transpose_y_0 = const()[name = tensor("scores_165_transpose_y_0"), val = tensor(false)]; + tensor transpose_232_perm_0 = const()[name = tensor("transpose_232_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_233_perm_0 = const()[name = tensor("transpose_233_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_233 = transpose(perm = transpose_233_perm_0, x = var_3769_cast_fp16)[name = tensor("transpose_299")]; + tensor transpose_232 = transpose(perm = transpose_232_perm_0, x = q_h_167_cast_fp16)[name = tensor("transpose_300")]; + tensor scores_165_cast_fp16 = matmul(transpose_x = scores_165_transpose_x_0, transpose_y = scores_165_transpose_y_0, x = transpose_232, y = transpose_233)[name = tensor("scores_165_cast_fp16")]; + tensor scores_167_cast_fp16 = select(a = var_11_to_fp16, b = scores_165_cast_fp16, cond = mask_5)[name = tensor("scores_167_cast_fp16")]; + tensor var_3799_cast_fp16 = softmax(axis = var_20, x = scores_167_cast_fp16)[name = tensor("op_3799_cast_fp16")]; + tensor input_1075_cast_fp16 = select(a = var_6_to_fp16, b = var_3799_cast_fp16, cond = mask_5)[name = tensor("input_1075_cast_fp16")]; + tensor x_423_transpose_x_0 = const()[name = tensor("x_423_transpose_x_0"), val = tensor(false)]; + tensor x_423_transpose_y_0 = const()[name = tensor("x_423_transpose_y_0"), val = tensor(false)]; + tensor value_83_cast_fp16 = transpose(perm = value_83_perm_0, x = var_3772_cast_fp16)[name = tensor("transpose_303")]; + tensor x_423_cast_fp16 = matmul(transpose_x = x_423_transpose_x_0, transpose_y = x_423_transpose_y_0, x = input_1075_cast_fp16, y = value_83_cast_fp16)[name = tensor("x_423_cast_fp16")]; + tensor var_3803_perm_0 = const()[name = tensor("op_3803_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3805 = const()[name = tensor("op_3805"), val = tensor([1, -1, 512])]; + tensor var_3803_cast_fp16 = transpose(perm = var_3803_perm_0, x = x_423_cast_fp16)[name = tensor("transpose_298")]; + tensor input_1077_cast_fp16 = reshape(shape = var_3805, x = var_3803_cast_fp16)[name = tensor("input_1077_cast_fp16")]; + tensor e_encoders_40_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_40_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260729408)))]; + tensor e_encoders_40_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_40_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261253760)))]; + tensor linear_165_cast_fp16 = linear(bias = e_encoders_40_self_attn_linear_out_bias_to_fp16, weight = e_encoders_40_self_attn_linear_out_weight_to_fp16, x = input_1077_cast_fp16)[name = tensor("linear_165_cast_fp16")]; + tensor input_1079_cast_fp16 = add(x = linear_165_cast_fp16, y = fsmn_memory_83_cast_fp16)[name = tensor("input_1079_cast_fp16")]; + tensor input_1081_cast_fp16 = add(x = input_1067_cast_fp16, y = input_1079_cast_fp16)[name = tensor("input_1081_cast_fp16")]; + tensor input_1083_axes_0 = const()[name = tensor("input_1083_axes_0"), val = tensor([-1])]; + tensor e_encoders_40_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_40_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261254848)))]; + tensor e_encoders_40_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_40_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261255936)))]; + tensor input_1083_cast_fp16 = layer_norm(axes = input_1083_axes_0, beta = e_encoders_40_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_40_norm2_weight_to_fp16, x = input_1081_cast_fp16)[name = tensor("input_1083_cast_fp16")]; + tensor e_encoders_40_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_40_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261257024)))]; + tensor e_encoders_40_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_40_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263354240)))]; + tensor linear_166_cast_fp16 = linear(bias = e_encoders_40_feed_forward_w_1_bias_to_fp16, weight = e_encoders_40_feed_forward_w_1_weight_to_fp16, x = input_1083_cast_fp16)[name = tensor("linear_166_cast_fp16")]; + tensor input_1087_cast_fp16 = relu(x = linear_166_cast_fp16)[name = tensor("input_1087_cast_fp16")]; + tensor e_encoders_40_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_40_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263358400)))]; + tensor e_encoders_40_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_40_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265455616)))]; + tensor linear_167_cast_fp16 = linear(bias = e_encoders_40_feed_forward_w_2_bias_to_fp16, weight = e_encoders_40_feed_forward_w_2_weight_to_fp16, x = input_1087_cast_fp16)[name = tensor("linear_167_cast_fp16")]; + tensor input_1093_cast_fp16 = add(x = input_1081_cast_fp16, y = linear_167_cast_fp16)[name = tensor("input_1093_cast_fp16")]; + tensor x_425_axes_0 = const()[name = tensor("x_425_axes_0"), val = tensor([-1])]; + tensor e_encoders_41_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_41_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265456704)))]; + tensor e_encoders_41_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_41_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265457792)))]; + tensor x_425_cast_fp16 = layer_norm(axes = x_425_axes_0, beta = e_encoders_41_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_41_norm1_weight_to_fp16, x = input_1093_cast_fp16)[name = tensor("x_425_cast_fp16")]; + tensor e_encoders_41_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_41_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265458880)))]; + tensor e_encoders_41_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_41_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267031808)))]; + tensor linear_168_cast_fp16 = linear(bias = e_encoders_41_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_41_self_attn_linear_q_k_v_weight_to_fp16, x = x_425_cast_fp16)[name = tensor("linear_168_cast_fp16")]; + tensor tile_42 = const()[name = tensor("tile_42"), val = tensor([512, 512, 512])]; + tensor var_3849_axis_0 = const()[name = tensor("op_3849_axis_0"), val = tensor(-1)]; + tensor var_3849_cast_fp16_0, tensor var_3849_cast_fp16_1, tensor var_3849_cast_fp16_2 = split(axis = var_3849_axis_0, split_sizes = tile_42, x = linear_168_cast_fp16)[name = tensor("op_3849_cast_fp16")]; + tensor concat_127x = const()[name = tensor("concat_127x"), val = tensor([1, -1, 4, 128])]; + tensor var_3854_cast_fp16 = reshape(shape = concat_127x, x = var_3849_cast_fp16_0)[name = tensor("op_3854_cast_fp16")]; + tensor concat_128x = const()[name = tensor("concat_128x"), val = tensor([1, -1, 4, 128])]; + tensor var_3857_cast_fp16 = reshape(shape = concat_128x, x = var_3849_cast_fp16_1)[name = tensor("op_3857_cast_fp16")]; + tensor concat_129x = const()[name = tensor("concat_129x"), val = tensor([1, -1, 4, 128])]; + tensor var_3860_cast_fp16 = reshape(shape = concat_129x, x = var_3849_cast_fp16_2)[name = tensor("op_3860_cast_fp16")]; + tensor value_85_perm_0 = const()[name = tensor("value_85_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_85_cast_fp16 = mul(x = var_3849_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_85_cast_fp16")]; + tensor input_1095_perm_0 = const()[name = tensor("input_1095_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1097_pad_0 = const()[name = tensor("input_1097_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1097_mode_0 = const()[name = tensor("input_1097_mode_0"), val = tensor("constant")]; + tensor const_93_to_fp16 = const()[name = tensor("const_93_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1095_cast_fp16 = transpose(perm = input_1095_perm_0, x = inputs_85_cast_fp16)[name = tensor("transpose_296")]; + tensor input_1097_cast_fp16 = pad(constant_val = const_93_to_fp16, mode = input_1097_mode_0, pad = input_1097_pad_0, x = input_1095_cast_fp16)[name = tensor("input_1097_cast_fp16")]; + tensor x_427_pad_type_0 = const()[name = tensor("x_427_pad_type_0"), val = tensor("valid")]; + tensor x_427_groups_0 = const()[name = tensor("x_427_groups_0"), val = tensor(512)]; + tensor x_427_strides_0 = const()[name = tensor("x_427_strides_0"), val = tensor([1])]; + tensor x_427_pad_0 = const()[name = tensor("x_427_pad_0"), val = tensor([0, 0])]; + tensor x_427_dilations_0 = const()[name = tensor("x_427_dilations_0"), val = tensor([1])]; + tensor e_encoders_41_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_41_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267034944)))]; + tensor x_427_cast_fp16 = conv(dilations = x_427_dilations_0, groups = x_427_groups_0, pad = x_427_pad_0, pad_type = x_427_pad_type_0, strides = x_427_strides_0, weight = e_encoders_41_self_attn_fsmn_block_weight_to_fp16, x = input_1097_cast_fp16)[name = tensor("x_427_cast_fp16")]; + tensor x_429_perm_0 = const()[name = tensor("x_429_perm_0"), val = tensor([0, 2, 1])]; + tensor x_429_cast_fp16 = transpose(perm = x_429_perm_0, x = x_427_cast_fp16)[name = tensor("transpose_295")]; + tensor input_1099_cast_fp16 = add(x = x_429_cast_fp16, y = inputs_85_cast_fp16)[name = tensor("input_1099_cast_fp16")]; + tensor fsmn_memory_85_cast_fp16 = mul(x = input_1099_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_85_cast_fp16")]; + tensor var_3879_to_fp16 = const()[name = tensor("op_3879_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_171_cast_fp16 = mul(x = var_3854_cast_fp16, y = var_3879_to_fp16)[name = tensor("q_h_171_cast_fp16")]; + tensor scores_169_transpose_x_0 = const()[name = tensor("scores_169_transpose_x_0"), val = tensor(false)]; + tensor scores_169_transpose_y_0 = const()[name = tensor("scores_169_transpose_y_0"), val = tensor(false)]; + tensor transpose_234_perm_0 = const()[name = tensor("transpose_234_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_235_perm_0 = const()[name = tensor("transpose_235_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_235 = transpose(perm = transpose_235_perm_0, x = var_3857_cast_fp16)[name = tensor("transpose_293")]; + tensor transpose_234 = transpose(perm = transpose_234_perm_0, x = q_h_171_cast_fp16)[name = tensor("transpose_294")]; + tensor scores_169_cast_fp16 = matmul(transpose_x = scores_169_transpose_x_0, transpose_y = scores_169_transpose_y_0, x = transpose_234, y = transpose_235)[name = tensor("scores_169_cast_fp16")]; + tensor scores_171_cast_fp16 = select(a = var_11_to_fp16, b = scores_169_cast_fp16, cond = mask_5)[name = tensor("scores_171_cast_fp16")]; + tensor var_3887_cast_fp16 = softmax(axis = var_20, x = scores_171_cast_fp16)[name = tensor("op_3887_cast_fp16")]; + tensor input_1101_cast_fp16 = select(a = var_6_to_fp16, b = var_3887_cast_fp16, cond = mask_5)[name = tensor("input_1101_cast_fp16")]; + tensor x_433_transpose_x_0 = const()[name = tensor("x_433_transpose_x_0"), val = tensor(false)]; + tensor x_433_transpose_y_0 = const()[name = tensor("x_433_transpose_y_0"), val = tensor(false)]; + tensor value_85_cast_fp16 = transpose(perm = value_85_perm_0, x = var_3860_cast_fp16)[name = tensor("transpose_297")]; + tensor x_433_cast_fp16 = matmul(transpose_x = x_433_transpose_x_0, transpose_y = x_433_transpose_y_0, x = input_1101_cast_fp16, y = value_85_cast_fp16)[name = tensor("x_433_cast_fp16")]; + tensor var_3891_perm_0 = const()[name = tensor("op_3891_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3893 = const()[name = tensor("op_3893"), val = tensor([1, -1, 512])]; + tensor var_3891_cast_fp16 = transpose(perm = var_3891_perm_0, x = x_433_cast_fp16)[name = tensor("transpose_292")]; + tensor input_1103_cast_fp16 = reshape(shape = var_3893, x = var_3891_cast_fp16)[name = tensor("input_1103_cast_fp16")]; + tensor e_encoders_41_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_41_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267046272)))]; + tensor e_encoders_41_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_41_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267570624)))]; + tensor linear_169_cast_fp16 = linear(bias = e_encoders_41_self_attn_linear_out_bias_to_fp16, weight = e_encoders_41_self_attn_linear_out_weight_to_fp16, x = input_1103_cast_fp16)[name = tensor("linear_169_cast_fp16")]; + tensor input_1105_cast_fp16 = add(x = linear_169_cast_fp16, y = fsmn_memory_85_cast_fp16)[name = tensor("input_1105_cast_fp16")]; + tensor input_1107_cast_fp16 = add(x = input_1093_cast_fp16, y = input_1105_cast_fp16)[name = tensor("input_1107_cast_fp16")]; + tensor input_1109_axes_0 = const()[name = tensor("input_1109_axes_0"), val = tensor([-1])]; + tensor e_encoders_41_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_41_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267571712)))]; + tensor e_encoders_41_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_41_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267572800)))]; + tensor input_1109_cast_fp16 = layer_norm(axes = input_1109_axes_0, beta = e_encoders_41_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_41_norm2_weight_to_fp16, x = input_1107_cast_fp16)[name = tensor("input_1109_cast_fp16")]; + tensor e_encoders_41_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_41_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267573888)))]; + tensor e_encoders_41_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_41_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269671104)))]; + tensor linear_170_cast_fp16 = linear(bias = e_encoders_41_feed_forward_w_1_bias_to_fp16, weight = e_encoders_41_feed_forward_w_1_weight_to_fp16, x = input_1109_cast_fp16)[name = tensor("linear_170_cast_fp16")]; + tensor input_1113_cast_fp16 = relu(x = linear_170_cast_fp16)[name = tensor("input_1113_cast_fp16")]; + tensor e_encoders_41_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_41_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269675264)))]; + tensor e_encoders_41_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_41_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271772480)))]; + tensor linear_171_cast_fp16 = linear(bias = e_encoders_41_feed_forward_w_2_bias_to_fp16, weight = e_encoders_41_feed_forward_w_2_weight_to_fp16, x = input_1113_cast_fp16)[name = tensor("linear_171_cast_fp16")]; + tensor input_1119_cast_fp16 = add(x = input_1107_cast_fp16, y = linear_171_cast_fp16)[name = tensor("input_1119_cast_fp16")]; + tensor x_435_axes_0 = const()[name = tensor("x_435_axes_0"), val = tensor([-1])]; + tensor e_encoders_42_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_42_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271773568)))]; + tensor e_encoders_42_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_42_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271774656)))]; + tensor x_435_cast_fp16 = layer_norm(axes = x_435_axes_0, beta = e_encoders_42_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_42_norm1_weight_to_fp16, x = input_1119_cast_fp16)[name = tensor("x_435_cast_fp16")]; + tensor e_encoders_42_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_42_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271775744)))]; + tensor e_encoders_42_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_42_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273348672)))]; + tensor linear_172_cast_fp16 = linear(bias = e_encoders_42_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_42_self_attn_linear_q_k_v_weight_to_fp16, x = x_435_cast_fp16)[name = tensor("linear_172_cast_fp16")]; + tensor tile_43 = const()[name = tensor("tile_43"), val = tensor([512, 512, 512])]; + tensor var_3937_axis_0 = const()[name = tensor("op_3937_axis_0"), val = tensor(-1)]; + tensor var_3937_cast_fp16_0, tensor var_3937_cast_fp16_1, tensor var_3937_cast_fp16_2 = split(axis = var_3937_axis_0, split_sizes = tile_43, x = linear_172_cast_fp16)[name = tensor("op_3937_cast_fp16")]; + tensor concat_130x = const()[name = tensor("concat_130x"), val = tensor([1, -1, 4, 128])]; + tensor var_3942_cast_fp16 = reshape(shape = concat_130x, x = var_3937_cast_fp16_0)[name = tensor("op_3942_cast_fp16")]; + tensor concat_131x = const()[name = tensor("concat_131x"), val = tensor([1, -1, 4, 128])]; + tensor var_3945_cast_fp16 = reshape(shape = concat_131x, x = var_3937_cast_fp16_1)[name = tensor("op_3945_cast_fp16")]; + tensor concat_132x = const()[name = tensor("concat_132x"), val = tensor([1, -1, 4, 128])]; + tensor var_3948_cast_fp16 = reshape(shape = concat_132x, x = var_3937_cast_fp16_2)[name = tensor("op_3948_cast_fp16")]; + tensor value_87_perm_0 = const()[name = tensor("value_87_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_87_cast_fp16 = mul(x = var_3937_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_87_cast_fp16")]; + tensor input_1121_perm_0 = const()[name = tensor("input_1121_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1123_pad_0 = const()[name = tensor("input_1123_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1123_mode_0 = const()[name = tensor("input_1123_mode_0"), val = tensor("constant")]; + tensor const_95_to_fp16 = const()[name = tensor("const_95_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1121_cast_fp16 = transpose(perm = input_1121_perm_0, x = inputs_87_cast_fp16)[name = tensor("transpose_290")]; + tensor input_1123_cast_fp16 = pad(constant_val = const_95_to_fp16, mode = input_1123_mode_0, pad = input_1123_pad_0, x = input_1121_cast_fp16)[name = tensor("input_1123_cast_fp16")]; + tensor x_437_pad_type_0 = const()[name = tensor("x_437_pad_type_0"), val = tensor("valid")]; + tensor x_437_groups_0 = const()[name = tensor("x_437_groups_0"), val = tensor(512)]; + tensor x_437_strides_0 = const()[name = tensor("x_437_strides_0"), val = tensor([1])]; + tensor x_437_pad_0 = const()[name = tensor("x_437_pad_0"), val = tensor([0, 0])]; + tensor x_437_dilations_0 = const()[name = tensor("x_437_dilations_0"), val = tensor([1])]; + tensor e_encoders_42_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_42_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273351808)))]; + tensor x_437_cast_fp16 = conv(dilations = x_437_dilations_0, groups = x_437_groups_0, pad = x_437_pad_0, pad_type = x_437_pad_type_0, strides = x_437_strides_0, weight = e_encoders_42_self_attn_fsmn_block_weight_to_fp16, x = input_1123_cast_fp16)[name = tensor("x_437_cast_fp16")]; + tensor x_439_perm_0 = const()[name = tensor("x_439_perm_0"), val = tensor([0, 2, 1])]; + tensor x_439_cast_fp16 = transpose(perm = x_439_perm_0, x = x_437_cast_fp16)[name = tensor("transpose_289")]; + tensor input_1125_cast_fp16 = add(x = x_439_cast_fp16, y = inputs_87_cast_fp16)[name = tensor("input_1125_cast_fp16")]; + tensor fsmn_memory_87_cast_fp16 = mul(x = input_1125_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_87_cast_fp16")]; + tensor var_3967_to_fp16 = const()[name = tensor("op_3967_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_175_cast_fp16 = mul(x = var_3942_cast_fp16, y = var_3967_to_fp16)[name = tensor("q_h_175_cast_fp16")]; + tensor scores_173_transpose_x_0 = const()[name = tensor("scores_173_transpose_x_0"), val = tensor(false)]; + tensor scores_173_transpose_y_0 = const()[name = tensor("scores_173_transpose_y_0"), val = tensor(false)]; + tensor transpose_236_perm_0 = const()[name = tensor("transpose_236_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_237_perm_0 = const()[name = tensor("transpose_237_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_237 = transpose(perm = transpose_237_perm_0, x = var_3945_cast_fp16)[name = tensor("transpose_287")]; + tensor transpose_236 = transpose(perm = transpose_236_perm_0, x = q_h_175_cast_fp16)[name = tensor("transpose_288")]; + tensor scores_173_cast_fp16 = matmul(transpose_x = scores_173_transpose_x_0, transpose_y = scores_173_transpose_y_0, x = transpose_236, y = transpose_237)[name = tensor("scores_173_cast_fp16")]; + tensor scores_175_cast_fp16 = select(a = var_11_to_fp16, b = scores_173_cast_fp16, cond = mask_5)[name = tensor("scores_175_cast_fp16")]; + tensor var_3975_cast_fp16 = softmax(axis = var_20, x = scores_175_cast_fp16)[name = tensor("op_3975_cast_fp16")]; + tensor input_1127_cast_fp16 = select(a = var_6_to_fp16, b = var_3975_cast_fp16, cond = mask_5)[name = tensor("input_1127_cast_fp16")]; + tensor x_443_transpose_x_0 = const()[name = tensor("x_443_transpose_x_0"), val = tensor(false)]; + tensor x_443_transpose_y_0 = const()[name = tensor("x_443_transpose_y_0"), val = tensor(false)]; + tensor value_87_cast_fp16 = transpose(perm = value_87_perm_0, x = var_3948_cast_fp16)[name = tensor("transpose_291")]; + tensor x_443_cast_fp16 = matmul(transpose_x = x_443_transpose_x_0, transpose_y = x_443_transpose_y_0, x = input_1127_cast_fp16, y = value_87_cast_fp16)[name = tensor("x_443_cast_fp16")]; + tensor var_3979_perm_0 = const()[name = tensor("op_3979_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3981 = const()[name = tensor("op_3981"), val = tensor([1, -1, 512])]; + tensor var_3979_cast_fp16 = transpose(perm = var_3979_perm_0, x = x_443_cast_fp16)[name = tensor("transpose_286")]; + tensor input_1129_cast_fp16 = reshape(shape = var_3981, x = var_3979_cast_fp16)[name = tensor("input_1129_cast_fp16")]; + tensor e_encoders_42_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_42_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273363136)))]; + tensor e_encoders_42_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_42_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273887488)))]; + tensor linear_173_cast_fp16 = linear(bias = e_encoders_42_self_attn_linear_out_bias_to_fp16, weight = e_encoders_42_self_attn_linear_out_weight_to_fp16, x = input_1129_cast_fp16)[name = tensor("linear_173_cast_fp16")]; + tensor input_1131_cast_fp16 = add(x = linear_173_cast_fp16, y = fsmn_memory_87_cast_fp16)[name = tensor("input_1131_cast_fp16")]; + tensor input_1133_cast_fp16 = add(x = input_1119_cast_fp16, y = input_1131_cast_fp16)[name = tensor("input_1133_cast_fp16")]; + tensor input_1135_axes_0 = const()[name = tensor("input_1135_axes_0"), val = tensor([-1])]; + tensor e_encoders_42_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_42_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273888576)))]; + tensor e_encoders_42_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_42_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273889664)))]; + tensor input_1135_cast_fp16 = layer_norm(axes = input_1135_axes_0, beta = e_encoders_42_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_42_norm2_weight_to_fp16, x = input_1133_cast_fp16)[name = tensor("input_1135_cast_fp16")]; + tensor e_encoders_42_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_42_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273890752)))]; + tensor e_encoders_42_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_42_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275987968)))]; + tensor linear_174_cast_fp16 = linear(bias = e_encoders_42_feed_forward_w_1_bias_to_fp16, weight = e_encoders_42_feed_forward_w_1_weight_to_fp16, x = input_1135_cast_fp16)[name = tensor("linear_174_cast_fp16")]; + tensor input_1139_cast_fp16 = relu(x = linear_174_cast_fp16)[name = tensor("input_1139_cast_fp16")]; + tensor e_encoders_42_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_42_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275992128)))]; + tensor e_encoders_42_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_42_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278089344)))]; + tensor linear_175_cast_fp16 = linear(bias = e_encoders_42_feed_forward_w_2_bias_to_fp16, weight = e_encoders_42_feed_forward_w_2_weight_to_fp16, x = input_1139_cast_fp16)[name = tensor("linear_175_cast_fp16")]; + tensor input_1145_cast_fp16 = add(x = input_1133_cast_fp16, y = linear_175_cast_fp16)[name = tensor("input_1145_cast_fp16")]; + tensor x_445_axes_0 = const()[name = tensor("x_445_axes_0"), val = tensor([-1])]; + tensor e_encoders_43_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_43_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278090432)))]; + tensor e_encoders_43_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_43_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278091520)))]; + tensor x_445_cast_fp16 = layer_norm(axes = x_445_axes_0, beta = e_encoders_43_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_43_norm1_weight_to_fp16, x = input_1145_cast_fp16)[name = tensor("x_445_cast_fp16")]; + tensor e_encoders_43_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_43_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278092608)))]; + tensor e_encoders_43_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_43_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279665536)))]; + tensor linear_176_cast_fp16 = linear(bias = e_encoders_43_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_43_self_attn_linear_q_k_v_weight_to_fp16, x = x_445_cast_fp16)[name = tensor("linear_176_cast_fp16")]; + tensor tile_44 = const()[name = tensor("tile_44"), val = tensor([512, 512, 512])]; + tensor var_4025_axis_0 = const()[name = tensor("op_4025_axis_0"), val = tensor(-1)]; + tensor var_4025_cast_fp16_0, tensor var_4025_cast_fp16_1, tensor var_4025_cast_fp16_2 = split(axis = var_4025_axis_0, split_sizes = tile_44, x = linear_176_cast_fp16)[name = tensor("op_4025_cast_fp16")]; + tensor concat_133x = const()[name = tensor("concat_133x"), val = tensor([1, -1, 4, 128])]; + tensor var_4030_cast_fp16 = reshape(shape = concat_133x, x = var_4025_cast_fp16_0)[name = tensor("op_4030_cast_fp16")]; + tensor concat_134x = const()[name = tensor("concat_134x"), val = tensor([1, -1, 4, 128])]; + tensor var_4033_cast_fp16 = reshape(shape = concat_134x, x = var_4025_cast_fp16_1)[name = tensor("op_4033_cast_fp16")]; + tensor concat_135x = const()[name = tensor("concat_135x"), val = tensor([1, -1, 4, 128])]; + tensor var_4036_cast_fp16 = reshape(shape = concat_135x, x = var_4025_cast_fp16_2)[name = tensor("op_4036_cast_fp16")]; + tensor value_89_perm_0 = const()[name = tensor("value_89_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_89_cast_fp16 = mul(x = var_4025_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_89_cast_fp16")]; + tensor input_1147_perm_0 = const()[name = tensor("input_1147_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1149_pad_0 = const()[name = tensor("input_1149_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1149_mode_0 = const()[name = tensor("input_1149_mode_0"), val = tensor("constant")]; + tensor const_97_to_fp16 = const()[name = tensor("const_97_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1147_cast_fp16 = transpose(perm = input_1147_perm_0, x = inputs_89_cast_fp16)[name = tensor("transpose_284")]; + tensor input_1149_cast_fp16 = pad(constant_val = const_97_to_fp16, mode = input_1149_mode_0, pad = input_1149_pad_0, x = input_1147_cast_fp16)[name = tensor("input_1149_cast_fp16")]; + tensor x_447_pad_type_0 = const()[name = tensor("x_447_pad_type_0"), val = tensor("valid")]; + tensor x_447_groups_0 = const()[name = tensor("x_447_groups_0"), val = tensor(512)]; + tensor x_447_strides_0 = const()[name = tensor("x_447_strides_0"), val = tensor([1])]; + tensor x_447_pad_0 = const()[name = tensor("x_447_pad_0"), val = tensor([0, 0])]; + tensor x_447_dilations_0 = const()[name = tensor("x_447_dilations_0"), val = tensor([1])]; + tensor e_encoders_43_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_43_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279668672)))]; + tensor x_447_cast_fp16 = conv(dilations = x_447_dilations_0, groups = x_447_groups_0, pad = x_447_pad_0, pad_type = x_447_pad_type_0, strides = x_447_strides_0, weight = e_encoders_43_self_attn_fsmn_block_weight_to_fp16, x = input_1149_cast_fp16)[name = tensor("x_447_cast_fp16")]; + tensor x_449_perm_0 = const()[name = tensor("x_449_perm_0"), val = tensor([0, 2, 1])]; + tensor x_449_cast_fp16 = transpose(perm = x_449_perm_0, x = x_447_cast_fp16)[name = tensor("transpose_283")]; + tensor input_1151_cast_fp16 = add(x = x_449_cast_fp16, y = inputs_89_cast_fp16)[name = tensor("input_1151_cast_fp16")]; + tensor fsmn_memory_89_cast_fp16 = mul(x = input_1151_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_89_cast_fp16")]; + tensor var_4055_to_fp16 = const()[name = tensor("op_4055_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_179_cast_fp16 = mul(x = var_4030_cast_fp16, y = var_4055_to_fp16)[name = tensor("q_h_179_cast_fp16")]; + tensor scores_177_transpose_x_0 = const()[name = tensor("scores_177_transpose_x_0"), val = tensor(false)]; + tensor scores_177_transpose_y_0 = const()[name = tensor("scores_177_transpose_y_0"), val = tensor(false)]; + tensor transpose_238_perm_0 = const()[name = tensor("transpose_238_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_239_perm_0 = const()[name = tensor("transpose_239_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_239 = transpose(perm = transpose_239_perm_0, x = var_4033_cast_fp16)[name = tensor("transpose_281")]; + tensor transpose_238 = transpose(perm = transpose_238_perm_0, x = q_h_179_cast_fp16)[name = tensor("transpose_282")]; + tensor scores_177_cast_fp16 = matmul(transpose_x = scores_177_transpose_x_0, transpose_y = scores_177_transpose_y_0, x = transpose_238, y = transpose_239)[name = tensor("scores_177_cast_fp16")]; + tensor scores_179_cast_fp16 = select(a = var_11_to_fp16, b = scores_177_cast_fp16, cond = mask_5)[name = tensor("scores_179_cast_fp16")]; + tensor var_4063_cast_fp16 = softmax(axis = var_20, x = scores_179_cast_fp16)[name = tensor("op_4063_cast_fp16")]; + tensor input_1153_cast_fp16 = select(a = var_6_to_fp16, b = var_4063_cast_fp16, cond = mask_5)[name = tensor("input_1153_cast_fp16")]; + tensor x_453_transpose_x_0 = const()[name = tensor("x_453_transpose_x_0"), val = tensor(false)]; + tensor x_453_transpose_y_0 = const()[name = tensor("x_453_transpose_y_0"), val = tensor(false)]; + tensor value_89_cast_fp16 = transpose(perm = value_89_perm_0, x = var_4036_cast_fp16)[name = tensor("transpose_285")]; + tensor x_453_cast_fp16 = matmul(transpose_x = x_453_transpose_x_0, transpose_y = x_453_transpose_y_0, x = input_1153_cast_fp16, y = value_89_cast_fp16)[name = tensor("x_453_cast_fp16")]; + tensor var_4067_perm_0 = const()[name = tensor("op_4067_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4069 = const()[name = tensor("op_4069"), val = tensor([1, -1, 512])]; + tensor var_4067_cast_fp16 = transpose(perm = var_4067_perm_0, x = x_453_cast_fp16)[name = tensor("transpose_280")]; + tensor input_1155_cast_fp16 = reshape(shape = var_4069, x = var_4067_cast_fp16)[name = tensor("input_1155_cast_fp16")]; + tensor e_encoders_43_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_43_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279680000)))]; + tensor e_encoders_43_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_43_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280204352)))]; + tensor linear_177_cast_fp16 = linear(bias = e_encoders_43_self_attn_linear_out_bias_to_fp16, weight = e_encoders_43_self_attn_linear_out_weight_to_fp16, x = input_1155_cast_fp16)[name = tensor("linear_177_cast_fp16")]; + tensor input_1157_cast_fp16 = add(x = linear_177_cast_fp16, y = fsmn_memory_89_cast_fp16)[name = tensor("input_1157_cast_fp16")]; + tensor input_1159_cast_fp16 = add(x = input_1145_cast_fp16, y = input_1157_cast_fp16)[name = tensor("input_1159_cast_fp16")]; + tensor input_1161_axes_0 = const()[name = tensor("input_1161_axes_0"), val = tensor([-1])]; + tensor e_encoders_43_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_43_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280205440)))]; + tensor e_encoders_43_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_43_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280206528)))]; + tensor input_1161_cast_fp16 = layer_norm(axes = input_1161_axes_0, beta = e_encoders_43_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_43_norm2_weight_to_fp16, x = input_1159_cast_fp16)[name = tensor("input_1161_cast_fp16")]; + tensor e_encoders_43_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_43_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280207616)))]; + tensor e_encoders_43_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_43_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282304832)))]; + tensor linear_178_cast_fp16 = linear(bias = e_encoders_43_feed_forward_w_1_bias_to_fp16, weight = e_encoders_43_feed_forward_w_1_weight_to_fp16, x = input_1161_cast_fp16)[name = tensor("linear_178_cast_fp16")]; + tensor input_1165_cast_fp16 = relu(x = linear_178_cast_fp16)[name = tensor("input_1165_cast_fp16")]; + tensor e_encoders_43_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_43_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282308992)))]; + tensor e_encoders_43_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_43_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284406208)))]; + tensor linear_179_cast_fp16 = linear(bias = e_encoders_43_feed_forward_w_2_bias_to_fp16, weight = e_encoders_43_feed_forward_w_2_weight_to_fp16, x = input_1165_cast_fp16)[name = tensor("linear_179_cast_fp16")]; + tensor input_1171_cast_fp16 = add(x = input_1159_cast_fp16, y = linear_179_cast_fp16)[name = tensor("input_1171_cast_fp16")]; + tensor x_455_axes_0 = const()[name = tensor("x_455_axes_0"), val = tensor([-1])]; + tensor e_encoders_44_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_44_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284407296)))]; + tensor e_encoders_44_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_44_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284408384)))]; + tensor x_455_cast_fp16 = layer_norm(axes = x_455_axes_0, beta = e_encoders_44_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_44_norm1_weight_to_fp16, x = input_1171_cast_fp16)[name = tensor("x_455_cast_fp16")]; + tensor e_encoders_44_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_44_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284409472)))]; + tensor e_encoders_44_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_44_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285982400)))]; + tensor linear_180_cast_fp16 = linear(bias = e_encoders_44_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_44_self_attn_linear_q_k_v_weight_to_fp16, x = x_455_cast_fp16)[name = tensor("linear_180_cast_fp16")]; + tensor tile_45 = const()[name = tensor("tile_45"), val = tensor([512, 512, 512])]; + tensor var_4113_axis_0 = const()[name = tensor("op_4113_axis_0"), val = tensor(-1)]; + tensor var_4113_cast_fp16_0, tensor var_4113_cast_fp16_1, tensor var_4113_cast_fp16_2 = split(axis = var_4113_axis_0, split_sizes = tile_45, x = linear_180_cast_fp16)[name = tensor("op_4113_cast_fp16")]; + tensor concat_136x = const()[name = tensor("concat_136x"), val = tensor([1, -1, 4, 128])]; + tensor var_4118_cast_fp16 = reshape(shape = concat_136x, x = var_4113_cast_fp16_0)[name = tensor("op_4118_cast_fp16")]; + tensor concat_137x = const()[name = tensor("concat_137x"), val = tensor([1, -1, 4, 128])]; + tensor var_4121_cast_fp16 = reshape(shape = concat_137x, x = var_4113_cast_fp16_1)[name = tensor("op_4121_cast_fp16")]; + tensor concat_138x = const()[name = tensor("concat_138x"), val = tensor([1, -1, 4, 128])]; + tensor var_4124_cast_fp16 = reshape(shape = concat_138x, x = var_4113_cast_fp16_2)[name = tensor("op_4124_cast_fp16")]; + tensor value_91_perm_0 = const()[name = tensor("value_91_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_91_cast_fp16 = mul(x = var_4113_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_91_cast_fp16")]; + tensor input_1173_perm_0 = const()[name = tensor("input_1173_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1175_pad_0 = const()[name = tensor("input_1175_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1175_mode_0 = const()[name = tensor("input_1175_mode_0"), val = tensor("constant")]; + tensor const_99_to_fp16 = const()[name = tensor("const_99_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1173_cast_fp16 = transpose(perm = input_1173_perm_0, x = inputs_91_cast_fp16)[name = tensor("transpose_278")]; + tensor input_1175_cast_fp16 = pad(constant_val = const_99_to_fp16, mode = input_1175_mode_0, pad = input_1175_pad_0, x = input_1173_cast_fp16)[name = tensor("input_1175_cast_fp16")]; + tensor x_457_pad_type_0 = const()[name = tensor("x_457_pad_type_0"), val = tensor("valid")]; + tensor x_457_groups_0 = const()[name = tensor("x_457_groups_0"), val = tensor(512)]; + tensor x_457_strides_0 = const()[name = tensor("x_457_strides_0"), val = tensor([1])]; + tensor x_457_pad_0 = const()[name = tensor("x_457_pad_0"), val = tensor([0, 0])]; + tensor x_457_dilations_0 = const()[name = tensor("x_457_dilations_0"), val = tensor([1])]; + tensor e_encoders_44_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_44_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285985536)))]; + tensor x_457_cast_fp16 = conv(dilations = x_457_dilations_0, groups = x_457_groups_0, pad = x_457_pad_0, pad_type = x_457_pad_type_0, strides = x_457_strides_0, weight = e_encoders_44_self_attn_fsmn_block_weight_to_fp16, x = input_1175_cast_fp16)[name = tensor("x_457_cast_fp16")]; + tensor x_459_perm_0 = const()[name = tensor("x_459_perm_0"), val = tensor([0, 2, 1])]; + tensor x_459_cast_fp16 = transpose(perm = x_459_perm_0, x = x_457_cast_fp16)[name = tensor("transpose_277")]; + tensor input_1177_cast_fp16 = add(x = x_459_cast_fp16, y = inputs_91_cast_fp16)[name = tensor("input_1177_cast_fp16")]; + tensor fsmn_memory_91_cast_fp16 = mul(x = input_1177_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_91_cast_fp16")]; + tensor var_4143_to_fp16 = const()[name = tensor("op_4143_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_183_cast_fp16 = mul(x = var_4118_cast_fp16, y = var_4143_to_fp16)[name = tensor("q_h_183_cast_fp16")]; + tensor scores_181_transpose_x_0 = const()[name = tensor("scores_181_transpose_x_0"), val = tensor(false)]; + tensor scores_181_transpose_y_0 = const()[name = tensor("scores_181_transpose_y_0"), val = tensor(false)]; + tensor transpose_240_perm_0 = const()[name = tensor("transpose_240_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_241_perm_0 = const()[name = tensor("transpose_241_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_241 = transpose(perm = transpose_241_perm_0, x = var_4121_cast_fp16)[name = tensor("transpose_275")]; + tensor transpose_240 = transpose(perm = transpose_240_perm_0, x = q_h_183_cast_fp16)[name = tensor("transpose_276")]; + tensor scores_181_cast_fp16 = matmul(transpose_x = scores_181_transpose_x_0, transpose_y = scores_181_transpose_y_0, x = transpose_240, y = transpose_241)[name = tensor("scores_181_cast_fp16")]; + tensor scores_183_cast_fp16 = select(a = var_11_to_fp16, b = scores_181_cast_fp16, cond = mask_5)[name = tensor("scores_183_cast_fp16")]; + tensor var_4151_cast_fp16 = softmax(axis = var_20, x = scores_183_cast_fp16)[name = tensor("op_4151_cast_fp16")]; + tensor input_1179_cast_fp16 = select(a = var_6_to_fp16, b = var_4151_cast_fp16, cond = mask_5)[name = tensor("input_1179_cast_fp16")]; + tensor x_463_transpose_x_0 = const()[name = tensor("x_463_transpose_x_0"), val = tensor(false)]; + tensor x_463_transpose_y_0 = const()[name = tensor("x_463_transpose_y_0"), val = tensor(false)]; + tensor value_91_cast_fp16 = transpose(perm = value_91_perm_0, x = var_4124_cast_fp16)[name = tensor("transpose_279")]; + tensor x_463_cast_fp16 = matmul(transpose_x = x_463_transpose_x_0, transpose_y = x_463_transpose_y_0, x = input_1179_cast_fp16, y = value_91_cast_fp16)[name = tensor("x_463_cast_fp16")]; + tensor var_4155_perm_0 = const()[name = tensor("op_4155_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4157 = const()[name = tensor("op_4157"), val = tensor([1, -1, 512])]; + tensor var_4155_cast_fp16 = transpose(perm = var_4155_perm_0, x = x_463_cast_fp16)[name = tensor("transpose_274")]; + tensor input_1181_cast_fp16 = reshape(shape = var_4157, x = var_4155_cast_fp16)[name = tensor("input_1181_cast_fp16")]; + tensor e_encoders_44_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_44_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285996864)))]; + tensor e_encoders_44_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_44_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286521216)))]; + tensor linear_181_cast_fp16 = linear(bias = e_encoders_44_self_attn_linear_out_bias_to_fp16, weight = e_encoders_44_self_attn_linear_out_weight_to_fp16, x = input_1181_cast_fp16)[name = tensor("linear_181_cast_fp16")]; + tensor input_1183_cast_fp16 = add(x = linear_181_cast_fp16, y = fsmn_memory_91_cast_fp16)[name = tensor("input_1183_cast_fp16")]; + tensor input_1185_cast_fp16 = add(x = input_1171_cast_fp16, y = input_1183_cast_fp16)[name = tensor("input_1185_cast_fp16")]; + tensor input_1187_axes_0 = const()[name = tensor("input_1187_axes_0"), val = tensor([-1])]; + tensor e_encoders_44_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_44_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286522304)))]; + tensor e_encoders_44_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_44_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286523392)))]; + tensor input_1187_cast_fp16 = layer_norm(axes = input_1187_axes_0, beta = e_encoders_44_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_44_norm2_weight_to_fp16, x = input_1185_cast_fp16)[name = tensor("input_1187_cast_fp16")]; + tensor e_encoders_44_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_44_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286524480)))]; + tensor e_encoders_44_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_44_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288621696)))]; + tensor linear_182_cast_fp16 = linear(bias = e_encoders_44_feed_forward_w_1_bias_to_fp16, weight = e_encoders_44_feed_forward_w_1_weight_to_fp16, x = input_1187_cast_fp16)[name = tensor("linear_182_cast_fp16")]; + tensor input_1191_cast_fp16 = relu(x = linear_182_cast_fp16)[name = tensor("input_1191_cast_fp16")]; + tensor e_encoders_44_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_44_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288625856)))]; + tensor e_encoders_44_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_44_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290723072)))]; + tensor linear_183_cast_fp16 = linear(bias = e_encoders_44_feed_forward_w_2_bias_to_fp16, weight = e_encoders_44_feed_forward_w_2_weight_to_fp16, x = input_1191_cast_fp16)[name = tensor("linear_183_cast_fp16")]; + tensor input_1197_cast_fp16 = add(x = input_1185_cast_fp16, y = linear_183_cast_fp16)[name = tensor("input_1197_cast_fp16")]; + tensor x_465_axes_0 = const()[name = tensor("x_465_axes_0"), val = tensor([-1])]; + tensor e_encoders_45_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_45_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290724160)))]; + tensor e_encoders_45_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_45_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290725248)))]; + tensor x_465_cast_fp16 = layer_norm(axes = x_465_axes_0, beta = e_encoders_45_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_45_norm1_weight_to_fp16, x = input_1197_cast_fp16)[name = tensor("x_465_cast_fp16")]; + tensor e_encoders_45_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_45_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290726336)))]; + tensor e_encoders_45_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_45_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292299264)))]; + tensor linear_184_cast_fp16 = linear(bias = e_encoders_45_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_45_self_attn_linear_q_k_v_weight_to_fp16, x = x_465_cast_fp16)[name = tensor("linear_184_cast_fp16")]; + tensor tile_46 = const()[name = tensor("tile_46"), val = tensor([512, 512, 512])]; + tensor var_4201_axis_0 = const()[name = tensor("op_4201_axis_0"), val = tensor(-1)]; + tensor var_4201_cast_fp16_0, tensor var_4201_cast_fp16_1, tensor var_4201_cast_fp16_2 = split(axis = var_4201_axis_0, split_sizes = tile_46, x = linear_184_cast_fp16)[name = tensor("op_4201_cast_fp16")]; + tensor concat_139x = const()[name = tensor("concat_139x"), val = tensor([1, -1, 4, 128])]; + tensor var_4206_cast_fp16 = reshape(shape = concat_139x, x = var_4201_cast_fp16_0)[name = tensor("op_4206_cast_fp16")]; + tensor concat_140x = const()[name = tensor("concat_140x"), val = tensor([1, -1, 4, 128])]; + tensor var_4209_cast_fp16 = reshape(shape = concat_140x, x = var_4201_cast_fp16_1)[name = tensor("op_4209_cast_fp16")]; + tensor concat_141x = const()[name = tensor("concat_141x"), val = tensor([1, -1, 4, 128])]; + tensor var_4212_cast_fp16 = reshape(shape = concat_141x, x = var_4201_cast_fp16_2)[name = tensor("op_4212_cast_fp16")]; + tensor value_93_perm_0 = const()[name = tensor("value_93_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_93_cast_fp16 = mul(x = var_4201_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_93_cast_fp16")]; + tensor input_1199_perm_0 = const()[name = tensor("input_1199_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1201_pad_0 = const()[name = tensor("input_1201_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1201_mode_0 = const()[name = tensor("input_1201_mode_0"), val = tensor("constant")]; + tensor const_101_to_fp16 = const()[name = tensor("const_101_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1199_cast_fp16 = transpose(perm = input_1199_perm_0, x = inputs_93_cast_fp16)[name = tensor("transpose_272")]; + tensor input_1201_cast_fp16 = pad(constant_val = const_101_to_fp16, mode = input_1201_mode_0, pad = input_1201_pad_0, x = input_1199_cast_fp16)[name = tensor("input_1201_cast_fp16")]; + tensor x_467_pad_type_0 = const()[name = tensor("x_467_pad_type_0"), val = tensor("valid")]; + tensor x_467_groups_0 = const()[name = tensor("x_467_groups_0"), val = tensor(512)]; + tensor x_467_strides_0 = const()[name = tensor("x_467_strides_0"), val = tensor([1])]; + tensor x_467_pad_0 = const()[name = tensor("x_467_pad_0"), val = tensor([0, 0])]; + tensor x_467_dilations_0 = const()[name = tensor("x_467_dilations_0"), val = tensor([1])]; + tensor e_encoders_45_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_45_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292302400)))]; + tensor x_467_cast_fp16 = conv(dilations = x_467_dilations_0, groups = x_467_groups_0, pad = x_467_pad_0, pad_type = x_467_pad_type_0, strides = x_467_strides_0, weight = e_encoders_45_self_attn_fsmn_block_weight_to_fp16, x = input_1201_cast_fp16)[name = tensor("x_467_cast_fp16")]; + tensor x_469_perm_0 = const()[name = tensor("x_469_perm_0"), val = tensor([0, 2, 1])]; + tensor x_469_cast_fp16 = transpose(perm = x_469_perm_0, x = x_467_cast_fp16)[name = tensor("transpose_271")]; + tensor input_1203_cast_fp16 = add(x = x_469_cast_fp16, y = inputs_93_cast_fp16)[name = tensor("input_1203_cast_fp16")]; + tensor fsmn_memory_93_cast_fp16 = mul(x = input_1203_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_93_cast_fp16")]; + tensor var_4231_to_fp16 = const()[name = tensor("op_4231_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_187_cast_fp16 = mul(x = var_4206_cast_fp16, y = var_4231_to_fp16)[name = tensor("q_h_187_cast_fp16")]; + tensor scores_185_transpose_x_0 = const()[name = tensor("scores_185_transpose_x_0"), val = tensor(false)]; + tensor scores_185_transpose_y_0 = const()[name = tensor("scores_185_transpose_y_0"), val = tensor(false)]; + tensor transpose_242_perm_0 = const()[name = tensor("transpose_242_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_243_perm_0 = const()[name = tensor("transpose_243_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_243 = transpose(perm = transpose_243_perm_0, x = var_4209_cast_fp16)[name = tensor("transpose_269")]; + tensor transpose_242 = transpose(perm = transpose_242_perm_0, x = q_h_187_cast_fp16)[name = tensor("transpose_270")]; + tensor scores_185_cast_fp16 = matmul(transpose_x = scores_185_transpose_x_0, transpose_y = scores_185_transpose_y_0, x = transpose_242, y = transpose_243)[name = tensor("scores_185_cast_fp16")]; + tensor scores_187_cast_fp16 = select(a = var_11_to_fp16, b = scores_185_cast_fp16, cond = mask_5)[name = tensor("scores_187_cast_fp16")]; + tensor var_4239_cast_fp16 = softmax(axis = var_20, x = scores_187_cast_fp16)[name = tensor("op_4239_cast_fp16")]; + tensor input_1205_cast_fp16 = select(a = var_6_to_fp16, b = var_4239_cast_fp16, cond = mask_5)[name = tensor("input_1205_cast_fp16")]; + tensor x_473_transpose_x_0 = const()[name = tensor("x_473_transpose_x_0"), val = tensor(false)]; + tensor x_473_transpose_y_0 = const()[name = tensor("x_473_transpose_y_0"), val = tensor(false)]; + tensor value_93_cast_fp16 = transpose(perm = value_93_perm_0, x = var_4212_cast_fp16)[name = tensor("transpose_273")]; + tensor x_473_cast_fp16 = matmul(transpose_x = x_473_transpose_x_0, transpose_y = x_473_transpose_y_0, x = input_1205_cast_fp16, y = value_93_cast_fp16)[name = tensor("x_473_cast_fp16")]; + tensor var_4243_perm_0 = const()[name = tensor("op_4243_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4245 = const()[name = tensor("op_4245"), val = tensor([1, -1, 512])]; + tensor var_4243_cast_fp16 = transpose(perm = var_4243_perm_0, x = x_473_cast_fp16)[name = tensor("transpose_268")]; + tensor input_1207_cast_fp16 = reshape(shape = var_4245, x = var_4243_cast_fp16)[name = tensor("input_1207_cast_fp16")]; + tensor e_encoders_45_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_45_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292313728)))]; + tensor e_encoders_45_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_45_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292838080)))]; + tensor linear_185_cast_fp16 = linear(bias = e_encoders_45_self_attn_linear_out_bias_to_fp16, weight = e_encoders_45_self_attn_linear_out_weight_to_fp16, x = input_1207_cast_fp16)[name = tensor("linear_185_cast_fp16")]; + tensor input_1209_cast_fp16 = add(x = linear_185_cast_fp16, y = fsmn_memory_93_cast_fp16)[name = tensor("input_1209_cast_fp16")]; + tensor input_1211_cast_fp16 = add(x = input_1197_cast_fp16, y = input_1209_cast_fp16)[name = tensor("input_1211_cast_fp16")]; + tensor input_1213_axes_0 = const()[name = tensor("input_1213_axes_0"), val = tensor([-1])]; + tensor e_encoders_45_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_45_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292839168)))]; + tensor e_encoders_45_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_45_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292840256)))]; + tensor input_1213_cast_fp16 = layer_norm(axes = input_1213_axes_0, beta = e_encoders_45_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_45_norm2_weight_to_fp16, x = input_1211_cast_fp16)[name = tensor("input_1213_cast_fp16")]; + tensor e_encoders_45_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_45_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292841344)))]; + tensor e_encoders_45_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_45_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294938560)))]; + tensor linear_186_cast_fp16 = linear(bias = e_encoders_45_feed_forward_w_1_bias_to_fp16, weight = e_encoders_45_feed_forward_w_1_weight_to_fp16, x = input_1213_cast_fp16)[name = tensor("linear_186_cast_fp16")]; + tensor input_1217_cast_fp16 = relu(x = linear_186_cast_fp16)[name = tensor("input_1217_cast_fp16")]; + tensor e_encoders_45_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_45_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294942720)))]; + tensor e_encoders_45_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_45_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297039936)))]; + tensor linear_187_cast_fp16 = linear(bias = e_encoders_45_feed_forward_w_2_bias_to_fp16, weight = e_encoders_45_feed_forward_w_2_weight_to_fp16, x = input_1217_cast_fp16)[name = tensor("linear_187_cast_fp16")]; + tensor input_1223_cast_fp16 = add(x = input_1211_cast_fp16, y = linear_187_cast_fp16)[name = tensor("input_1223_cast_fp16")]; + tensor x_475_axes_0 = const()[name = tensor("x_475_axes_0"), val = tensor([-1])]; + tensor e_encoders_46_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_46_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297041024)))]; + tensor e_encoders_46_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_46_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297042112)))]; + tensor x_475_cast_fp16 = layer_norm(axes = x_475_axes_0, beta = e_encoders_46_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_46_norm1_weight_to_fp16, x = input_1223_cast_fp16)[name = tensor("x_475_cast_fp16")]; + tensor e_encoders_46_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_46_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297043200)))]; + tensor e_encoders_46_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_46_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298616128)))]; + tensor linear_188_cast_fp16 = linear(bias = e_encoders_46_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_46_self_attn_linear_q_k_v_weight_to_fp16, x = x_475_cast_fp16)[name = tensor("linear_188_cast_fp16")]; + tensor tile_47 = const()[name = tensor("tile_47"), val = tensor([512, 512, 512])]; + tensor var_4289_axis_0 = const()[name = tensor("op_4289_axis_0"), val = tensor(-1)]; + tensor var_4289_cast_fp16_0, tensor var_4289_cast_fp16_1, tensor var_4289_cast_fp16_2 = split(axis = var_4289_axis_0, split_sizes = tile_47, x = linear_188_cast_fp16)[name = tensor("op_4289_cast_fp16")]; + tensor concat_142x = const()[name = tensor("concat_142x"), val = tensor([1, -1, 4, 128])]; + tensor var_4294_cast_fp16 = reshape(shape = concat_142x, x = var_4289_cast_fp16_0)[name = tensor("op_4294_cast_fp16")]; + tensor concat_143x = const()[name = tensor("concat_143x"), val = tensor([1, -1, 4, 128])]; + tensor var_4297_cast_fp16 = reshape(shape = concat_143x, x = var_4289_cast_fp16_1)[name = tensor("op_4297_cast_fp16")]; + tensor concat_144x = const()[name = tensor("concat_144x"), val = tensor([1, -1, 4, 128])]; + tensor var_4300_cast_fp16 = reshape(shape = concat_144x, x = var_4289_cast_fp16_2)[name = tensor("op_4300_cast_fp16")]; + tensor value_95_perm_0 = const()[name = tensor("value_95_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_95_cast_fp16 = mul(x = var_4289_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_95_cast_fp16")]; + tensor input_1225_perm_0 = const()[name = tensor("input_1225_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1227_pad_0 = const()[name = tensor("input_1227_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1227_mode_0 = const()[name = tensor("input_1227_mode_0"), val = tensor("constant")]; + tensor const_103_to_fp16 = const()[name = tensor("const_103_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1225_cast_fp16 = transpose(perm = input_1225_perm_0, x = inputs_95_cast_fp16)[name = tensor("transpose_266")]; + tensor input_1227_cast_fp16 = pad(constant_val = const_103_to_fp16, mode = input_1227_mode_0, pad = input_1227_pad_0, x = input_1225_cast_fp16)[name = tensor("input_1227_cast_fp16")]; + tensor x_477_pad_type_0 = const()[name = tensor("x_477_pad_type_0"), val = tensor("valid")]; + tensor x_477_groups_0 = const()[name = tensor("x_477_groups_0"), val = tensor(512)]; + tensor x_477_strides_0 = const()[name = tensor("x_477_strides_0"), val = tensor([1])]; + tensor x_477_pad_0 = const()[name = tensor("x_477_pad_0"), val = tensor([0, 0])]; + tensor x_477_dilations_0 = const()[name = tensor("x_477_dilations_0"), val = tensor([1])]; + tensor e_encoders_46_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_46_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298619264)))]; + tensor x_477_cast_fp16 = conv(dilations = x_477_dilations_0, groups = x_477_groups_0, pad = x_477_pad_0, pad_type = x_477_pad_type_0, strides = x_477_strides_0, weight = e_encoders_46_self_attn_fsmn_block_weight_to_fp16, x = input_1227_cast_fp16)[name = tensor("x_477_cast_fp16")]; + tensor x_479_perm_0 = const()[name = tensor("x_479_perm_0"), val = tensor([0, 2, 1])]; + tensor x_479_cast_fp16 = transpose(perm = x_479_perm_0, x = x_477_cast_fp16)[name = tensor("transpose_265")]; + tensor input_1229_cast_fp16 = add(x = x_479_cast_fp16, y = inputs_95_cast_fp16)[name = tensor("input_1229_cast_fp16")]; + tensor fsmn_memory_95_cast_fp16 = mul(x = input_1229_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_95_cast_fp16")]; + tensor var_4319_to_fp16 = const()[name = tensor("op_4319_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_191_cast_fp16 = mul(x = var_4294_cast_fp16, y = var_4319_to_fp16)[name = tensor("q_h_191_cast_fp16")]; + tensor scores_189_transpose_x_0 = const()[name = tensor("scores_189_transpose_x_0"), val = tensor(false)]; + tensor scores_189_transpose_y_0 = const()[name = tensor("scores_189_transpose_y_0"), val = tensor(false)]; + tensor transpose_244_perm_0 = const()[name = tensor("transpose_244_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_245_perm_0 = const()[name = tensor("transpose_245_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_245 = transpose(perm = transpose_245_perm_0, x = var_4297_cast_fp16)[name = tensor("transpose_263")]; + tensor transpose_244 = transpose(perm = transpose_244_perm_0, x = q_h_191_cast_fp16)[name = tensor("transpose_264")]; + tensor scores_189_cast_fp16 = matmul(transpose_x = scores_189_transpose_x_0, transpose_y = scores_189_transpose_y_0, x = transpose_244, y = transpose_245)[name = tensor("scores_189_cast_fp16")]; + tensor scores_191_cast_fp16 = select(a = var_11_to_fp16, b = scores_189_cast_fp16, cond = mask_5)[name = tensor("scores_191_cast_fp16")]; + tensor var_4327_cast_fp16 = softmax(axis = var_20, x = scores_191_cast_fp16)[name = tensor("op_4327_cast_fp16")]; + tensor input_1231_cast_fp16 = select(a = var_6_to_fp16, b = var_4327_cast_fp16, cond = mask_5)[name = tensor("input_1231_cast_fp16")]; + tensor x_483_transpose_x_0 = const()[name = tensor("x_483_transpose_x_0"), val = tensor(false)]; + tensor x_483_transpose_y_0 = const()[name = tensor("x_483_transpose_y_0"), val = tensor(false)]; + tensor value_95_cast_fp16 = transpose(perm = value_95_perm_0, x = var_4300_cast_fp16)[name = tensor("transpose_267")]; + tensor x_483_cast_fp16 = matmul(transpose_x = x_483_transpose_x_0, transpose_y = x_483_transpose_y_0, x = input_1231_cast_fp16, y = value_95_cast_fp16)[name = tensor("x_483_cast_fp16")]; + tensor var_4331_perm_0 = const()[name = tensor("op_4331_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4333 = const()[name = tensor("op_4333"), val = tensor([1, -1, 512])]; + tensor var_4331_cast_fp16 = transpose(perm = var_4331_perm_0, x = x_483_cast_fp16)[name = tensor("transpose_262")]; + tensor input_1233_cast_fp16 = reshape(shape = var_4333, x = var_4331_cast_fp16)[name = tensor("input_1233_cast_fp16")]; + tensor e_encoders_46_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_46_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298630592)))]; + tensor e_encoders_46_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_46_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299154944)))]; + tensor linear_189_cast_fp16 = linear(bias = e_encoders_46_self_attn_linear_out_bias_to_fp16, weight = e_encoders_46_self_attn_linear_out_weight_to_fp16, x = input_1233_cast_fp16)[name = tensor("linear_189_cast_fp16")]; + tensor input_1235_cast_fp16 = add(x = linear_189_cast_fp16, y = fsmn_memory_95_cast_fp16)[name = tensor("input_1235_cast_fp16")]; + tensor input_1237_cast_fp16 = add(x = input_1223_cast_fp16, y = input_1235_cast_fp16)[name = tensor("input_1237_cast_fp16")]; + tensor input_1239_axes_0 = const()[name = tensor("input_1239_axes_0"), val = tensor([-1])]; + tensor e_encoders_46_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_46_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299156032)))]; + tensor e_encoders_46_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_46_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299157120)))]; + tensor input_1239_cast_fp16 = layer_norm(axes = input_1239_axes_0, beta = e_encoders_46_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_46_norm2_weight_to_fp16, x = input_1237_cast_fp16)[name = tensor("input_1239_cast_fp16")]; + tensor e_encoders_46_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_46_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299158208)))]; + tensor e_encoders_46_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_46_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301255424)))]; + tensor linear_190_cast_fp16 = linear(bias = e_encoders_46_feed_forward_w_1_bias_to_fp16, weight = e_encoders_46_feed_forward_w_1_weight_to_fp16, x = input_1239_cast_fp16)[name = tensor("linear_190_cast_fp16")]; + tensor input_1243_cast_fp16 = relu(x = linear_190_cast_fp16)[name = tensor("input_1243_cast_fp16")]; + tensor e_encoders_46_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_46_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301259584)))]; + tensor e_encoders_46_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_46_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303356800)))]; + tensor linear_191_cast_fp16 = linear(bias = e_encoders_46_feed_forward_w_2_bias_to_fp16, weight = e_encoders_46_feed_forward_w_2_weight_to_fp16, x = input_1243_cast_fp16)[name = tensor("linear_191_cast_fp16")]; + tensor input_1249_cast_fp16 = add(x = input_1237_cast_fp16, y = linear_191_cast_fp16)[name = tensor("input_1249_cast_fp16")]; + tensor x_485_axes_0 = const()[name = tensor("x_485_axes_0"), val = tensor([-1])]; + tensor e_encoders_47_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_47_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303357888)))]; + tensor e_encoders_47_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_47_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303358976)))]; + tensor x_485_cast_fp16 = layer_norm(axes = x_485_axes_0, beta = e_encoders_47_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_47_norm1_weight_to_fp16, x = input_1249_cast_fp16)[name = tensor("x_485_cast_fp16")]; + tensor e_encoders_47_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_47_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303360064)))]; + tensor e_encoders_47_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_47_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304932992)))]; + tensor linear_192_cast_fp16 = linear(bias = e_encoders_47_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_47_self_attn_linear_q_k_v_weight_to_fp16, x = x_485_cast_fp16)[name = tensor("linear_192_cast_fp16")]; + tensor tile_48 = const()[name = tensor("tile_48"), val = tensor([512, 512, 512])]; + tensor var_4377_axis_0 = const()[name = tensor("op_4377_axis_0"), val = tensor(-1)]; + tensor var_4377_cast_fp16_0, tensor var_4377_cast_fp16_1, tensor var_4377_cast_fp16_2 = split(axis = var_4377_axis_0, split_sizes = tile_48, x = linear_192_cast_fp16)[name = tensor("op_4377_cast_fp16")]; + tensor concat_145x = const()[name = tensor("concat_145x"), val = tensor([1, -1, 4, 128])]; + tensor var_4382_cast_fp16 = reshape(shape = concat_145x, x = var_4377_cast_fp16_0)[name = tensor("op_4382_cast_fp16")]; + tensor concat_146x = const()[name = tensor("concat_146x"), val = tensor([1, -1, 4, 128])]; + tensor var_4385_cast_fp16 = reshape(shape = concat_146x, x = var_4377_cast_fp16_1)[name = tensor("op_4385_cast_fp16")]; + tensor concat_147x = const()[name = tensor("concat_147x"), val = tensor([1, -1, 4, 128])]; + tensor var_4388_cast_fp16 = reshape(shape = concat_147x, x = var_4377_cast_fp16_2)[name = tensor("op_4388_cast_fp16")]; + tensor value_97_perm_0 = const()[name = tensor("value_97_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_97_cast_fp16 = mul(x = var_4377_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_97_cast_fp16")]; + tensor input_1251_perm_0 = const()[name = tensor("input_1251_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1253_pad_0 = const()[name = tensor("input_1253_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1253_mode_0 = const()[name = tensor("input_1253_mode_0"), val = tensor("constant")]; + tensor const_105_to_fp16 = const()[name = tensor("const_105_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1251_cast_fp16 = transpose(perm = input_1251_perm_0, x = inputs_97_cast_fp16)[name = tensor("transpose_260")]; + tensor input_1253_cast_fp16 = pad(constant_val = const_105_to_fp16, mode = input_1253_mode_0, pad = input_1253_pad_0, x = input_1251_cast_fp16)[name = tensor("input_1253_cast_fp16")]; + tensor x_487_pad_type_0 = const()[name = tensor("x_487_pad_type_0"), val = tensor("valid")]; + tensor x_487_groups_0 = const()[name = tensor("x_487_groups_0"), val = tensor(512)]; + tensor x_487_strides_0 = const()[name = tensor("x_487_strides_0"), val = tensor([1])]; + tensor x_487_pad_0 = const()[name = tensor("x_487_pad_0"), val = tensor([0, 0])]; + tensor x_487_dilations_0 = const()[name = tensor("x_487_dilations_0"), val = tensor([1])]; + tensor e_encoders_47_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_47_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304936128)))]; + tensor x_487_cast_fp16 = conv(dilations = x_487_dilations_0, groups = x_487_groups_0, pad = x_487_pad_0, pad_type = x_487_pad_type_0, strides = x_487_strides_0, weight = e_encoders_47_self_attn_fsmn_block_weight_to_fp16, x = input_1253_cast_fp16)[name = tensor("x_487_cast_fp16")]; + tensor x_489_perm_0 = const()[name = tensor("x_489_perm_0"), val = tensor([0, 2, 1])]; + tensor x_489_cast_fp16 = transpose(perm = x_489_perm_0, x = x_487_cast_fp16)[name = tensor("transpose_259")]; + tensor input_1255_cast_fp16 = add(x = x_489_cast_fp16, y = inputs_97_cast_fp16)[name = tensor("input_1255_cast_fp16")]; + tensor fsmn_memory_97_cast_fp16 = mul(x = input_1255_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_97_cast_fp16")]; + tensor var_4407_to_fp16 = const()[name = tensor("op_4407_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_195_cast_fp16 = mul(x = var_4382_cast_fp16, y = var_4407_to_fp16)[name = tensor("q_h_195_cast_fp16")]; + tensor scores_193_transpose_x_0 = const()[name = tensor("scores_193_transpose_x_0"), val = tensor(false)]; + tensor scores_193_transpose_y_0 = const()[name = tensor("scores_193_transpose_y_0"), val = tensor(false)]; + tensor transpose_246_perm_0 = const()[name = tensor("transpose_246_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_247_perm_0 = const()[name = tensor("transpose_247_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_247 = transpose(perm = transpose_247_perm_0, x = var_4385_cast_fp16)[name = tensor("transpose_257")]; + tensor transpose_246 = transpose(perm = transpose_246_perm_0, x = q_h_195_cast_fp16)[name = tensor("transpose_258")]; + tensor scores_193_cast_fp16 = matmul(transpose_x = scores_193_transpose_x_0, transpose_y = scores_193_transpose_y_0, x = transpose_246, y = transpose_247)[name = tensor("scores_193_cast_fp16")]; + tensor scores_195_cast_fp16 = select(a = var_11_to_fp16, b = scores_193_cast_fp16, cond = mask_5)[name = tensor("scores_195_cast_fp16")]; + tensor var_4415_cast_fp16 = softmax(axis = var_20, x = scores_195_cast_fp16)[name = tensor("op_4415_cast_fp16")]; + tensor input_1257_cast_fp16 = select(a = var_6_to_fp16, b = var_4415_cast_fp16, cond = mask_5)[name = tensor("input_1257_cast_fp16")]; + tensor x_493_transpose_x_0 = const()[name = tensor("x_493_transpose_x_0"), val = tensor(false)]; + tensor x_493_transpose_y_0 = const()[name = tensor("x_493_transpose_y_0"), val = tensor(false)]; + tensor value_97_cast_fp16 = transpose(perm = value_97_perm_0, x = var_4388_cast_fp16)[name = tensor("transpose_261")]; + tensor x_493_cast_fp16 = matmul(transpose_x = x_493_transpose_x_0, transpose_y = x_493_transpose_y_0, x = input_1257_cast_fp16, y = value_97_cast_fp16)[name = tensor("x_493_cast_fp16")]; + tensor var_4419_perm_0 = const()[name = tensor("op_4419_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4421 = const()[name = tensor("op_4421"), val = tensor([1, -1, 512])]; + tensor var_4419_cast_fp16 = transpose(perm = var_4419_perm_0, x = x_493_cast_fp16)[name = tensor("transpose_256")]; + tensor input_1259_cast_fp16 = reshape(shape = var_4421, x = var_4419_cast_fp16)[name = tensor("input_1259_cast_fp16")]; + tensor e_encoders_47_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_47_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304947456)))]; + tensor e_encoders_47_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_47_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305471808)))]; + tensor linear_193_cast_fp16 = linear(bias = e_encoders_47_self_attn_linear_out_bias_to_fp16, weight = e_encoders_47_self_attn_linear_out_weight_to_fp16, x = input_1259_cast_fp16)[name = tensor("linear_193_cast_fp16")]; + tensor input_1261_cast_fp16 = add(x = linear_193_cast_fp16, y = fsmn_memory_97_cast_fp16)[name = tensor("input_1261_cast_fp16")]; + tensor input_1263_cast_fp16 = add(x = input_1249_cast_fp16, y = input_1261_cast_fp16)[name = tensor("input_1263_cast_fp16")]; + tensor input_1265_axes_0 = const()[name = tensor("input_1265_axes_0"), val = tensor([-1])]; + tensor e_encoders_47_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_47_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305472896)))]; + tensor e_encoders_47_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_47_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305473984)))]; + tensor input_1265_cast_fp16 = layer_norm(axes = input_1265_axes_0, beta = e_encoders_47_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_47_norm2_weight_to_fp16, x = input_1263_cast_fp16)[name = tensor("input_1265_cast_fp16")]; + tensor e_encoders_47_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_47_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305475072)))]; + tensor e_encoders_47_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_47_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307572288)))]; + tensor linear_194_cast_fp16 = linear(bias = e_encoders_47_feed_forward_w_1_bias_to_fp16, weight = e_encoders_47_feed_forward_w_1_weight_to_fp16, x = input_1265_cast_fp16)[name = tensor("linear_194_cast_fp16")]; + tensor input_1269_cast_fp16 = relu(x = linear_194_cast_fp16)[name = tensor("input_1269_cast_fp16")]; + tensor e_encoders_47_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_47_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307576448)))]; + tensor e_encoders_47_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_47_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309673664)))]; + tensor linear_195_cast_fp16 = linear(bias = e_encoders_47_feed_forward_w_2_bias_to_fp16, weight = e_encoders_47_feed_forward_w_2_weight_to_fp16, x = input_1269_cast_fp16)[name = tensor("linear_195_cast_fp16")]; + tensor input_1275_cast_fp16 = add(x = input_1263_cast_fp16, y = linear_195_cast_fp16)[name = tensor("input_1275_cast_fp16")]; + tensor x_495_axes_0 = const()[name = tensor("x_495_axes_0"), val = tensor([-1])]; + tensor e_encoders_48_norm1_weight_to_fp16 = const()[name = tensor("e_encoders_48_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309674752)))]; + tensor e_encoders_48_norm1_bias_to_fp16 = const()[name = tensor("e_encoders_48_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309675840)))]; + tensor x_495_cast_fp16 = layer_norm(axes = x_495_axes_0, beta = e_encoders_48_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_48_norm1_weight_to_fp16, x = input_1275_cast_fp16)[name = tensor("x_495_cast_fp16")]; + tensor e_encoders_48_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("e_encoders_48_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309676928)))]; + tensor e_encoders_48_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("e_encoders_48_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311249856)))]; + tensor linear_196_cast_fp16 = linear(bias = e_encoders_48_self_attn_linear_q_k_v_bias_to_fp16, weight = e_encoders_48_self_attn_linear_q_k_v_weight_to_fp16, x = x_495_cast_fp16)[name = tensor("linear_196_cast_fp16")]; + tensor tile_49 = const()[name = tensor("tile_49"), val = tensor([512, 512, 512])]; + tensor var_4465_axis_0 = const()[name = tensor("op_4465_axis_0"), val = tensor(-1)]; + tensor var_4465_cast_fp16_0, tensor var_4465_cast_fp16_1, tensor var_4465_cast_fp16_2 = split(axis = var_4465_axis_0, split_sizes = tile_49, x = linear_196_cast_fp16)[name = tensor("op_4465_cast_fp16")]; + tensor concat_148x = const()[name = tensor("concat_148x"), val = tensor([1, -1, 4, 128])]; + tensor var_4470_cast_fp16 = reshape(shape = concat_148x, x = var_4465_cast_fp16_0)[name = tensor("op_4470_cast_fp16")]; + tensor concat_149x = const()[name = tensor("concat_149x"), val = tensor([1, -1, 4, 128])]; + tensor var_4473_cast_fp16 = reshape(shape = concat_149x, x = var_4465_cast_fp16_1)[name = tensor("op_4473_cast_fp16")]; + tensor concat_150x = const()[name = tensor("concat_150x"), val = tensor([1, -1, 4, 128])]; + tensor var_4476_cast_fp16 = reshape(shape = concat_150x, x = var_4465_cast_fp16_2)[name = tensor("op_4476_cast_fp16")]; + tensor value_perm_0 = const()[name = tensor("value_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_cast_fp16 = mul(x = var_4465_cast_fp16_2, y = mask_3_to_fp16)[name = tensor("inputs_cast_fp16")]; + tensor input_1277_perm_0 = const()[name = tensor("input_1277_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1279_pad_0 = const()[name = tensor("input_1279_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1279_mode_0 = const()[name = tensor("input_1279_mode_0"), val = tensor("constant")]; + tensor const_107_to_fp16 = const()[name = tensor("const_107_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1277_cast_fp16 = transpose(perm = input_1277_perm_0, x = inputs_cast_fp16)[name = tensor("transpose_254")]; + tensor input_1279_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_1279_mode_0, pad = input_1279_pad_0, x = input_1277_cast_fp16)[name = tensor("input_1279_cast_fp16")]; + tensor x_497_pad_type_0 = const()[name = tensor("x_497_pad_type_0"), val = tensor("valid")]; + tensor x_497_groups_0 = const()[name = tensor("x_497_groups_0"), val = tensor(512)]; + tensor x_497_strides_0 = const()[name = tensor("x_497_strides_0"), val = tensor([1])]; + tensor x_497_pad_0 = const()[name = tensor("x_497_pad_0"), val = tensor([0, 0])]; + tensor x_497_dilations_0 = const()[name = tensor("x_497_dilations_0"), val = tensor([1])]; + tensor e_encoders_48_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("e_encoders_48_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311252992)))]; + tensor x_497_cast_fp16 = conv(dilations = x_497_dilations_0, groups = x_497_groups_0, pad = x_497_pad_0, pad_type = x_497_pad_type_0, strides = x_497_strides_0, weight = e_encoders_48_self_attn_fsmn_block_weight_to_fp16, x = input_1279_cast_fp16)[name = tensor("x_497_cast_fp16")]; + tensor x_499_perm_0 = const()[name = tensor("x_499_perm_0"), val = tensor([0, 2, 1])]; + tensor x_499_cast_fp16 = transpose(perm = x_499_perm_0, x = x_497_cast_fp16)[name = tensor("transpose_253")]; + tensor input_1281_cast_fp16 = add(x = x_499_cast_fp16, y = inputs_cast_fp16)[name = tensor("input_1281_cast_fp16")]; + tensor fsmn_memory_cast_fp16 = mul(x = input_1281_cast_fp16, y = mask_3_to_fp16)[name = tensor("fsmn_memory_cast_fp16")]; + tensor var_4495_to_fp16 = const()[name = tensor("op_4495_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_cast_fp16 = mul(x = var_4470_cast_fp16, y = var_4495_to_fp16)[name = tensor("q_h_cast_fp16")]; + tensor scores_197_transpose_x_0 = const()[name = tensor("scores_197_transpose_x_0"), val = tensor(false)]; + tensor scores_197_transpose_y_0 = const()[name = tensor("scores_197_transpose_y_0"), val = tensor(false)]; + tensor transpose_248_perm_0 = const()[name = tensor("transpose_248_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_249_perm_0 = const()[name = tensor("transpose_249_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_249 = transpose(perm = transpose_249_perm_0, x = var_4473_cast_fp16)[name = tensor("transpose_251")]; + tensor transpose_248 = transpose(perm = transpose_248_perm_0, x = q_h_cast_fp16)[name = tensor("transpose_252")]; + tensor scores_197_cast_fp16 = matmul(transpose_x = scores_197_transpose_x_0, transpose_y = scores_197_transpose_y_0, x = transpose_248, y = transpose_249)[name = tensor("scores_197_cast_fp16")]; + tensor scores_cast_fp16 = select(a = var_11_to_fp16, b = scores_197_cast_fp16, cond = mask_5)[name = tensor("scores_cast_fp16")]; + tensor var_4503_cast_fp16 = softmax(axis = var_20, x = scores_cast_fp16)[name = tensor("op_4503_cast_fp16")]; + tensor input_1283_cast_fp16 = select(a = var_6_to_fp16, b = var_4503_cast_fp16, cond = mask_5)[name = tensor("input_1283_cast_fp16")]; + tensor x_transpose_x_0 = const()[name = tensor("x_transpose_x_0"), val = tensor(false)]; + tensor x_transpose_y_0 = const()[name = tensor("x_transpose_y_0"), val = tensor(false)]; + tensor value_cast_fp16 = transpose(perm = value_perm_0, x = var_4476_cast_fp16)[name = tensor("transpose_255")]; + tensor x_cast_fp16 = matmul(transpose_x = x_transpose_x_0, transpose_y = x_transpose_y_0, x = input_1283_cast_fp16, y = value_cast_fp16)[name = tensor("x_cast_fp16")]; + tensor var_4507_perm_0 = const()[name = tensor("op_4507_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4509 = const()[name = tensor("op_4509"), val = tensor([1, -1, 512])]; + tensor var_4507_cast_fp16 = transpose(perm = var_4507_perm_0, x = x_cast_fp16)[name = tensor("transpose_250")]; + tensor input_1285_cast_fp16 = reshape(shape = var_4509, x = var_4507_cast_fp16)[name = tensor("input_1285_cast_fp16")]; + tensor e_encoders_48_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("e_encoders_48_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311264320)))]; + tensor e_encoders_48_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("e_encoders_48_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311788672)))]; + tensor linear_197_cast_fp16 = linear(bias = e_encoders_48_self_attn_linear_out_bias_to_fp16, weight = e_encoders_48_self_attn_linear_out_weight_to_fp16, x = input_1285_cast_fp16)[name = tensor("linear_197_cast_fp16")]; + tensor input_1287_cast_fp16 = add(x = linear_197_cast_fp16, y = fsmn_memory_cast_fp16)[name = tensor("input_1287_cast_fp16")]; + tensor input_1289_cast_fp16 = add(x = input_1275_cast_fp16, y = input_1287_cast_fp16)[name = tensor("input_1289_cast_fp16")]; + tensor input_1291_axes_0 = const()[name = tensor("input_1291_axes_0"), val = tensor([-1])]; + tensor e_encoders_48_norm2_weight_to_fp16 = const()[name = tensor("e_encoders_48_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311789760)))]; + tensor e_encoders_48_norm2_bias_to_fp16 = const()[name = tensor("e_encoders_48_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311790848)))]; + tensor input_1291_cast_fp16 = layer_norm(axes = input_1291_axes_0, beta = e_encoders_48_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_encoders_48_norm2_weight_to_fp16, x = input_1289_cast_fp16)[name = tensor("input_1291_cast_fp16")]; + tensor e_encoders_48_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("e_encoders_48_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311791936)))]; + tensor e_encoders_48_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("e_encoders_48_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313889152)))]; + tensor linear_198_cast_fp16 = linear(bias = e_encoders_48_feed_forward_w_1_bias_to_fp16, weight = e_encoders_48_feed_forward_w_1_weight_to_fp16, x = input_1291_cast_fp16)[name = tensor("linear_198_cast_fp16")]; + tensor input_1295_cast_fp16 = relu(x = linear_198_cast_fp16)[name = tensor("input_1295_cast_fp16")]; + tensor e_encoders_48_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("e_encoders_48_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313893312)))]; + tensor e_encoders_48_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("e_encoders_48_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315990528)))]; + tensor linear_199_cast_fp16 = linear(bias = e_encoders_48_feed_forward_w_2_bias_to_fp16, weight = e_encoders_48_feed_forward_w_2_weight_to_fp16, x = input_1295_cast_fp16)[name = tensor("linear_199_cast_fp16")]; + tensor input_cast_fp16 = add(x = input_1289_cast_fp16, y = linear_199_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor var_4540_axes_0 = const()[name = tensor("op_4540_axes_0"), val = tensor([-1])]; + tensor e_after_norm_weight_to_fp16 = const()[name = tensor("e_after_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315991616)))]; + tensor e_after_norm_bias_to_fp16 = const()[name = tensor("e_after_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315992704)))]; + tensor enc_out = layer_norm(axes = var_4540_axes_0, beta = e_after_norm_bias_to_fp16, epsilon = var_13_to_fp16, gamma = e_after_norm_weight_to_fp16, x = input_cast_fp16)[name = tensor("op_4540_cast_fp16")]; + tensor speech_lengths_tmp = identity(x = speech_lengths)[name = tensor("speech_lengths_tmp")]; + } -> (enc_out); +} \ No newline at end of file