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Add compiled micro .mlmodelc bundles (encoder + 8 buckets)
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[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.7.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
{
func main<ios17>(tensor<fp32, [1, 1, 384]> y_mask, tensor<fp32, [1, 192, 384]> z_p) {
tensor<int32, []> var_13 = const()[name = tensor<string, []>("op_13"), val = tensor<int32, []>(1)];
tensor<int32, [1]> var_22 = const()[name = tensor<string, []>("op_22"), val = tensor<int32, [1]>([1])];
tensor<string, []> z_p_to_fp16_dtype_0 = const()[name = tensor<string, []>("z_p_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
tensor<fp16, [1, 192, 384]> z_p_to_fp16 = cast(dtype = z_p_to_fp16_dtype_0, x = z_p)[name = tensor<string, []>("cast_10")];
tensor<fp16, [1, 192, 384]> var_23_cast_fp16 = reverse(axes = var_22, x = z_p_to_fp16)[name = tensor<string, []>("op_23_cast_fp16")];
tensor<int32, [2]> var_27 = const()[name = tensor<string, []>("op_27"), val = tensor<int32, [2]>([96, 96])];
tensor<int32, []> var_28_axis_0 = const()[name = tensor<string, []>("op_28_axis_0"), val = tensor<int32, []>(1)];
tensor<fp16, [1, 96, 384]> var_28_cast_fp16_0, tensor<fp16, [1, 96, 384]> var_28_cast_fp16_1 = split(axis = var_28_axis_0, split_sizes = var_27, x = var_23_cast_fp16)[name = tensor<string, []>("op_28_cast_fp16")];
tensor<string, []> var_37_pad_type_0 = const()[name = tensor<string, []>("op_37_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_37_strides_0 = const()[name = tensor<string, []>("op_37_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_37_pad_0 = const()[name = tensor<string, []>("op_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_37_dilations_0 = const()[name = tensor<string, []>("op_37_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_37_groups_0 = const()[name = tensor<string, []>("op_37_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_6_pre_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_pre_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
tensor<fp16, [96]> flow_flows_6_pre_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_pre_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18560)))];
tensor<fp16, [1, 96, 384]> var_37_cast_fp16 = conv(bias = flow_flows_6_pre_bias_to_fp16, dilations = var_37_dilations_0, groups = var_37_groups_0, pad = var_37_pad_0, pad_type = var_37_pad_type_0, strides = var_37_strides_0, weight = flow_flows_6_pre_weight_to_fp16, x = var_28_cast_fp16_0)[name = tensor<string, []>("op_37_cast_fp16")];
tensor<string, []> y_mask_to_fp16_dtype_0 = const()[name = tensor<string, []>("y_mask_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
tensor<fp16, [1, 1, 384]> y_mask_to_fp16 = cast(dtype = y_mask_to_fp16_dtype_0, x = y_mask)[name = tensor<string, []>("cast_9")];
tensor<fp16, [1, 96, 384]> x_1_cast_fp16 = mul(x = var_37_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x_1_cast_fp16")];
tensor<string, []> x_in_1_pad_type_0 = const()[name = tensor<string, []>("x_in_1_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_1_pad_0 = const()[name = tensor<string, []>("x_in_1_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_1_strides_0 = const()[name = tensor<string, []>("x_in_1_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_1_dilations_0 = const()[name = tensor<string, []>("x_in_1_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_1_groups_0 = const()[name = tensor<string, []>("x_in_1_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_6_enc_in_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18816)))];
tensor<fp16, [192]> flow_flows_6_enc_in_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203200)))];
tensor<fp16, [1, 192, 384]> x_in_1_cast_fp16 = conv(bias = flow_flows_6_enc_in_layers_0_bias_to_fp16, dilations = x_in_1_dilations_0, groups = x_in_1_groups_0, pad = x_in_1_pad_0, pad_type = x_in_1_pad_type_0, strides = x_in_1_strides_0, weight = flow_flows_6_enc_in_layers_0_weight_to_fp16, x = x_1_cast_fp16)[name = tensor<string, []>("x_in_1_cast_fp16")];
tensor<int32, [3]> var_66_begin_0 = const()[name = tensor<string, []>("op_66_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_66_end_0 = const()[name = tensor<string, []>("op_66_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_66_end_mask_0 = const()[name = tensor<string, []>("op_66_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_66_cast_fp16 = slice_by_index(begin = var_66_begin_0, end = var_66_end_0, end_mask = var_66_end_mask_0, x = x_in_1_cast_fp16)[name = tensor<string, []>("op_66_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_68_cast_fp16 = tanh(x = var_66_cast_fp16)[name = tensor<string, []>("op_68_cast_fp16")];
tensor<int32, [3]> var_70_begin_0 = const()[name = tensor<string, []>("op_70_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_70_end_0 = const()[name = tensor<string, []>("op_70_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_70_end_mask_0 = const()[name = tensor<string, []>("op_70_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_70_cast_fp16 = slice_by_index(begin = var_70_begin_0, end = var_70_end_0, end_mask = var_70_end_mask_0, x = x_in_1_cast_fp16)[name = tensor<string, []>("op_70_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_72_cast_fp16 = sigmoid(x = var_70_cast_fp16)[name = tensor<string, []>("op_72_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_3_cast_fp16 = mul(x = var_68_cast_fp16, y = var_72_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
tensor<string, []> res_skip_acts_1_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_1_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_1_strides_0 = const()[name = tensor<string, []>("res_skip_acts_1_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_1_pad_0 = const()[name = tensor<string, []>("res_skip_acts_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_1_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_1_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_1_groups_0 = const()[name = tensor<string, []>("res_skip_acts_1_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_6_enc_res_skip_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203648)))];
tensor<fp16, [192]> flow_flows_6_enc_res_skip_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(240576)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_1_cast_fp16 = conv(bias = flow_flows_6_enc_res_skip_layers_0_bias_to_fp16, dilations = res_skip_acts_1_dilations_0, groups = res_skip_acts_1_groups_0, pad = res_skip_acts_1_pad_0, pad_type = res_skip_acts_1_pad_type_0, strides = res_skip_acts_1_strides_0, weight = flow_flows_6_enc_res_skip_layers_0_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("res_skip_acts_1_cast_fp16")];
tensor<int32, [3]> var_83_begin_0 = const()[name = tensor<string, []>("op_83_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_83_end_0 = const()[name = tensor<string, []>("op_83_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_83_end_mask_0 = const()[name = tensor<string, []>("op_83_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_83_cast_fp16 = slice_by_index(begin = var_83_begin_0, end = var_83_end_0, end_mask = var_83_end_mask_0, x = res_skip_acts_1_cast_fp16)[name = tensor<string, []>("op_83_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_85_cast_fp16 = add(x = x_1_cast_fp16, y = var_83_cast_fp16)[name = tensor<string, []>("op_85_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_7_cast_fp16 = mul(x = var_85_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
tensor<int32, [3]> var_88_begin_0 = const()[name = tensor<string, []>("op_88_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_88_end_0 = const()[name = tensor<string, []>("op_88_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_88_end_mask_0 = const()[name = tensor<string, []>("op_88_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_88_cast_fp16 = slice_by_index(begin = var_88_begin_0, end = var_88_end_0, end_mask = var_88_end_mask_0, x = res_skip_acts_1_cast_fp16)[name = tensor<string, []>("op_88_cast_fp16")];
tensor<string, []> x_in_3_pad_type_0 = const()[name = tensor<string, []>("x_in_3_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_3_pad_0 = const()[name = tensor<string, []>("x_in_3_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_3_strides_0 = const()[name = tensor<string, []>("x_in_3_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_3_dilations_0 = const()[name = tensor<string, []>("x_in_3_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_3_groups_0 = const()[name = tensor<string, []>("x_in_3_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_6_enc_in_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(241024)))];
tensor<fp16, [192]> flow_flows_6_enc_in_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425408)))];
tensor<fp16, [1, 192, 384]> x_in_3_cast_fp16 = conv(bias = flow_flows_6_enc_in_layers_1_bias_to_fp16, dilations = x_in_3_dilations_0, groups = x_in_3_groups_0, pad = x_in_3_pad_0, pad_type = x_in_3_pad_type_0, strides = x_in_3_strides_0, weight = flow_flows_6_enc_in_layers_1_weight_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("x_in_3_cast_fp16")];
tensor<int32, [3]> var_101_begin_0 = const()[name = tensor<string, []>("op_101_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_101_end_0 = const()[name = tensor<string, []>("op_101_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_101_end_mask_0 = const()[name = tensor<string, []>("op_101_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_101_cast_fp16 = slice_by_index(begin = var_101_begin_0, end = var_101_end_0, end_mask = var_101_end_mask_0, x = x_in_3_cast_fp16)[name = tensor<string, []>("op_101_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_103_cast_fp16 = tanh(x = var_101_cast_fp16)[name = tensor<string, []>("op_103_cast_fp16")];
tensor<int32, [3]> var_105_begin_0 = const()[name = tensor<string, []>("op_105_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_105_end_0 = const()[name = tensor<string, []>("op_105_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_105_end_mask_0 = const()[name = tensor<string, []>("op_105_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_105_cast_fp16 = slice_by_index(begin = var_105_begin_0, end = var_105_end_0, end_mask = var_105_end_mask_0, x = x_in_3_cast_fp16)[name = tensor<string, []>("op_105_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_107_cast_fp16 = sigmoid(x = var_105_cast_fp16)[name = tensor<string, []>("op_107_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_9_cast_fp16 = mul(x = var_103_cast_fp16, y = var_107_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
tensor<string, []> res_skip_acts_3_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_3_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_3_strides_0 = const()[name = tensor<string, []>("res_skip_acts_3_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_3_pad_0 = const()[name = tensor<string, []>("res_skip_acts_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_3_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_3_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_3_groups_0 = const()[name = tensor<string, []>("res_skip_acts_3_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_6_enc_res_skip_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425856)))];
tensor<fp16, [192]> flow_flows_6_enc_res_skip_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(462784)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_3_cast_fp16 = conv(bias = flow_flows_6_enc_res_skip_layers_1_bias_to_fp16, dilations = res_skip_acts_3_dilations_0, groups = res_skip_acts_3_groups_0, pad = res_skip_acts_3_pad_0, pad_type = res_skip_acts_3_pad_type_0, strides = res_skip_acts_3_strides_0, weight = flow_flows_6_enc_res_skip_layers_1_weight_to_fp16, x = input_9_cast_fp16)[name = tensor<string, []>("res_skip_acts_3_cast_fp16")];
tensor<int32, [3]> var_118_begin_0 = const()[name = tensor<string, []>("op_118_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_118_end_0 = const()[name = tensor<string, []>("op_118_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_118_end_mask_0 = const()[name = tensor<string, []>("op_118_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_118_cast_fp16 = slice_by_index(begin = var_118_begin_0, end = var_118_end_0, end_mask = var_118_end_mask_0, x = res_skip_acts_3_cast_fp16)[name = tensor<string, []>("op_118_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_120_cast_fp16 = add(x = input_7_cast_fp16, y = var_118_cast_fp16)[name = tensor<string, []>("op_120_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_13_cast_fp16 = mul(x = var_120_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
tensor<int32, [3]> var_123_begin_0 = const()[name = tensor<string, []>("op_123_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_123_end_0 = const()[name = tensor<string, []>("op_123_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_123_end_mask_0 = const()[name = tensor<string, []>("op_123_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_123_cast_fp16 = slice_by_index(begin = var_123_begin_0, end = var_123_end_0, end_mask = var_123_end_mask_0, x = res_skip_acts_3_cast_fp16)[name = tensor<string, []>("op_123_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_5_cast_fp16 = add(x = var_88_cast_fp16, y = var_123_cast_fp16)[name = tensor<string, []>("output_5_cast_fp16")];
tensor<string, []> x_in_5_pad_type_0 = const()[name = tensor<string, []>("x_in_5_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_5_pad_0 = const()[name = tensor<string, []>("x_in_5_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_5_strides_0 = const()[name = tensor<string, []>("x_in_5_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_5_dilations_0 = const()[name = tensor<string, []>("x_in_5_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_5_groups_0 = const()[name = tensor<string, []>("x_in_5_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_6_enc_in_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(463232)))];
tensor<fp16, [192]> flow_flows_6_enc_in_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(647616)))];
tensor<fp16, [1, 192, 384]> x_in_5_cast_fp16 = conv(bias = flow_flows_6_enc_in_layers_2_bias_to_fp16, dilations = x_in_5_dilations_0, groups = x_in_5_groups_0, pad = x_in_5_pad_0, pad_type = x_in_5_pad_type_0, strides = x_in_5_strides_0, weight = flow_flows_6_enc_in_layers_2_weight_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("x_in_5_cast_fp16")];
tensor<int32, [3]> var_136_begin_0 = const()[name = tensor<string, []>("op_136_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_136_end_0 = const()[name = tensor<string, []>("op_136_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_136_end_mask_0 = const()[name = tensor<string, []>("op_136_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_136_cast_fp16 = slice_by_index(begin = var_136_begin_0, end = var_136_end_0, end_mask = var_136_end_mask_0, x = x_in_5_cast_fp16)[name = tensor<string, []>("op_136_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_138_cast_fp16 = tanh(x = var_136_cast_fp16)[name = tensor<string, []>("op_138_cast_fp16")];
tensor<int32, [3]> var_140_begin_0 = const()[name = tensor<string, []>("op_140_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_140_end_0 = const()[name = tensor<string, []>("op_140_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_140_end_mask_0 = const()[name = tensor<string, []>("op_140_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_140_cast_fp16 = slice_by_index(begin = var_140_begin_0, end = var_140_end_0, end_mask = var_140_end_mask_0, x = x_in_5_cast_fp16)[name = tensor<string, []>("op_140_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_142_cast_fp16 = sigmoid(x = var_140_cast_fp16)[name = tensor<string, []>("op_142_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_15_cast_fp16 = mul(x = var_138_cast_fp16, y = var_142_cast_fp16)[name = tensor<string, []>("input_15_cast_fp16")];
tensor<string, []> res_skip_acts_5_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_5_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_5_strides_0 = const()[name = tensor<string, []>("res_skip_acts_5_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_5_pad_0 = const()[name = tensor<string, []>("res_skip_acts_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_5_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_5_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_5_groups_0 = const()[name = tensor<string, []>("res_skip_acts_5_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_6_enc_res_skip_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648064)))];
tensor<fp16, [192]> flow_flows_6_enc_res_skip_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684992)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_5_cast_fp16 = conv(bias = flow_flows_6_enc_res_skip_layers_2_bias_to_fp16, dilations = res_skip_acts_5_dilations_0, groups = res_skip_acts_5_groups_0, pad = res_skip_acts_5_pad_0, pad_type = res_skip_acts_5_pad_type_0, strides = res_skip_acts_5_strides_0, weight = flow_flows_6_enc_res_skip_layers_2_weight_to_fp16, x = input_15_cast_fp16)[name = tensor<string, []>("res_skip_acts_5_cast_fp16")];
tensor<int32, [3]> var_153_begin_0 = const()[name = tensor<string, []>("op_153_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_153_end_0 = const()[name = tensor<string, []>("op_153_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_153_end_mask_0 = const()[name = tensor<string, []>("op_153_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_153_cast_fp16 = slice_by_index(begin = var_153_begin_0, end = var_153_end_0, end_mask = var_153_end_mask_0, x = res_skip_acts_5_cast_fp16)[name = tensor<string, []>("op_153_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_155_cast_fp16 = add(x = input_13_cast_fp16, y = var_153_cast_fp16)[name = tensor<string, []>("op_155_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_19_cast_fp16 = mul(x = var_155_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
tensor<int32, [3]> var_158_begin_0 = const()[name = tensor<string, []>("op_158_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_158_end_0 = const()[name = tensor<string, []>("op_158_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_158_end_mask_0 = const()[name = tensor<string, []>("op_158_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_158_cast_fp16 = slice_by_index(begin = var_158_begin_0, end = var_158_end_0, end_mask = var_158_end_mask_0, x = res_skip_acts_5_cast_fp16)[name = tensor<string, []>("op_158_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_7_cast_fp16 = add(x = output_5_cast_fp16, y = var_158_cast_fp16)[name = tensor<string, []>("output_7_cast_fp16")];
tensor<string, []> x_in_7_pad_type_0 = const()[name = tensor<string, []>("x_in_7_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_7_pad_0 = const()[name = tensor<string, []>("x_in_7_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_7_strides_0 = const()[name = tensor<string, []>("x_in_7_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_7_dilations_0 = const()[name = tensor<string, []>("x_in_7_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_7_groups_0 = const()[name = tensor<string, []>("x_in_7_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_6_enc_in_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_3_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(685440)))];
tensor<fp16, [192]> flow_flows_6_enc_in_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_in_layers_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(869824)))];
tensor<fp16, [1, 192, 384]> x_in_7_cast_fp16 = conv(bias = flow_flows_6_enc_in_layers_3_bias_to_fp16, dilations = x_in_7_dilations_0, groups = x_in_7_groups_0, pad = x_in_7_pad_0, pad_type = x_in_7_pad_type_0, strides = x_in_7_strides_0, weight = flow_flows_6_enc_in_layers_3_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("x_in_7_cast_fp16")];
tensor<int32, [3]> var_171_begin_0 = const()[name = tensor<string, []>("op_171_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_171_end_0 = const()[name = tensor<string, []>("op_171_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_171_end_mask_0 = const()[name = tensor<string, []>("op_171_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_171_cast_fp16 = slice_by_index(begin = var_171_begin_0, end = var_171_end_0, end_mask = var_171_end_mask_0, x = x_in_7_cast_fp16)[name = tensor<string, []>("op_171_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_173_cast_fp16 = tanh(x = var_171_cast_fp16)[name = tensor<string, []>("op_173_cast_fp16")];
tensor<int32, [3]> var_175_begin_0 = const()[name = tensor<string, []>("op_175_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_175_end_0 = const()[name = tensor<string, []>("op_175_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_175_end_mask_0 = const()[name = tensor<string, []>("op_175_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_175_cast_fp16 = slice_by_index(begin = var_175_begin_0, end = var_175_end_0, end_mask = var_175_end_mask_0, x = x_in_7_cast_fp16)[name = tensor<string, []>("op_175_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_177_cast_fp16 = sigmoid(x = var_175_cast_fp16)[name = tensor<string, []>("op_177_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_21_cast_fp16 = mul(x = var_173_cast_fp16, y = var_177_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
tensor<string, []> res_skip_acts_7_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_7_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_7_strides_0 = const()[name = tensor<string, []>("res_skip_acts_7_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_7_pad_0 = const()[name = tensor<string, []>("res_skip_acts_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_7_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_7_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_7_groups_0 = const()[name = tensor<string, []>("res_skip_acts_7_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_6_enc_res_skip_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_3_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(870272)))];
tensor<fp16, [96]> flow_flows_6_enc_res_skip_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_enc_res_skip_layers_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(888768)))];
tensor<fp16, [1, 96, 384]> res_skip_acts_7_cast_fp16 = conv(bias = flow_flows_6_enc_res_skip_layers_3_bias_to_fp16, dilations = res_skip_acts_7_dilations_0, groups = res_skip_acts_7_groups_0, pad = res_skip_acts_7_pad_0, pad_type = res_skip_acts_7_pad_type_0, strides = res_skip_acts_7_strides_0, weight = flow_flows_6_enc_res_skip_layers_3_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("res_skip_acts_7_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_9_cast_fp16 = add(x = output_7_cast_fp16, y = res_skip_acts_7_cast_fp16)[name = tensor<string, []>("output_9_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_25_cast_fp16 = mul(x = output_9_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
tensor<string, []> var_195_pad_type_0 = const()[name = tensor<string, []>("op_195_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_195_strides_0 = const()[name = tensor<string, []>("op_195_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_195_pad_0 = const()[name = tensor<string, []>("op_195_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_195_dilations_0 = const()[name = tensor<string, []>("op_195_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_195_groups_0 = const()[name = tensor<string, []>("op_195_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_6_post_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_post_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(889024)))];
tensor<fp16, [96]> flow_flows_6_post_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_6_post_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(907520)))];
tensor<fp16, [1, 96, 384]> var_195_cast_fp16 = conv(bias = flow_flows_6_post_bias_to_fp16, dilations = var_195_dilations_0, groups = var_195_groups_0, pad = var_195_pad_0, pad_type = var_195_pad_type_0, strides = var_195_strides_0, weight = flow_flows_6_post_weight_to_fp16, x = input_25_cast_fp16)[name = tensor<string, []>("op_195_cast_fp16")];
tensor<fp16, [1, 96, 384]> stats_1_cast_fp16 = mul(x = var_195_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("stats_1_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_198_cast_fp16 = sub(x = var_28_cast_fp16_1, y = stats_1_cast_fp16)[name = tensor<string, []>("op_198_cast_fp16")];
tensor<fp16, [1, 96, 384]> x1_3_cast_fp16 = mul(x = var_198_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x1_3_cast_fp16")];
tensor<bool, []> x_3_interleave_0 = const()[name = tensor<string, []>("x_3_interleave_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 192, 384]> x_3_cast_fp16 = concat(axis = var_13, interleave = x_3_interleave_0, values = (var_28_cast_fp16_0, x1_3_cast_fp16))[name = tensor<string, []>("x_3_cast_fp16")];
tensor<int32, [1]> var_205 = const()[name = tensor<string, []>("op_205"), val = tensor<int32, [1]>([1])];
tensor<fp16, [1, 192, 384]> var_206_cast_fp16 = reverse(axes = var_205, x = x_3_cast_fp16)[name = tensor<string, []>("op_206_cast_fp16")];
tensor<int32, [2]> var_210 = const()[name = tensor<string, []>("op_210"), val = tensor<int32, [2]>([96, 96])];
tensor<int32, []> var_211_axis_0 = const()[name = tensor<string, []>("op_211_axis_0"), val = tensor<int32, []>(1)];
tensor<fp16, [1, 96, 384]> var_211_cast_fp16_0, tensor<fp16, [1, 96, 384]> var_211_cast_fp16_1 = split(axis = var_211_axis_0, split_sizes = var_210, x = var_206_cast_fp16)[name = tensor<string, []>("op_211_cast_fp16")];
tensor<string, []> var_220_pad_type_0 = const()[name = tensor<string, []>("op_220_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_220_strides_0 = const()[name = tensor<string, []>("op_220_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_220_pad_0 = const()[name = tensor<string, []>("op_220_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_220_dilations_0 = const()[name = tensor<string, []>("op_220_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_220_groups_0 = const()[name = tensor<string, []>("op_220_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_4_pre_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_pre_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(907776)))];
tensor<fp16, [96]> flow_flows_4_pre_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_pre_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926272)))];
tensor<fp16, [1, 96, 384]> var_220_cast_fp16 = conv(bias = flow_flows_4_pre_bias_to_fp16, dilations = var_220_dilations_0, groups = var_220_groups_0, pad = var_220_pad_0, pad_type = var_220_pad_type_0, strides = var_220_strides_0, weight = flow_flows_4_pre_weight_to_fp16, x = var_211_cast_fp16_0)[name = tensor<string, []>("op_220_cast_fp16")];
tensor<fp16, [1, 96, 384]> x_5_cast_fp16 = mul(x = var_220_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x_5_cast_fp16")];
tensor<string, []> x_in_9_pad_type_0 = const()[name = tensor<string, []>("x_in_9_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_9_pad_0 = const()[name = tensor<string, []>("x_in_9_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_9_strides_0 = const()[name = tensor<string, []>("x_in_9_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_9_dilations_0 = const()[name = tensor<string, []>("x_in_9_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_9_groups_0 = const()[name = tensor<string, []>("x_in_9_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_4_enc_in_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926528)))];
tensor<fp16, [192]> flow_flows_4_enc_in_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110912)))];
tensor<fp16, [1, 192, 384]> x_in_9_cast_fp16 = conv(bias = flow_flows_4_enc_in_layers_0_bias_to_fp16, dilations = x_in_9_dilations_0, groups = x_in_9_groups_0, pad = x_in_9_pad_0, pad_type = x_in_9_pad_type_0, strides = x_in_9_strides_0, weight = flow_flows_4_enc_in_layers_0_weight_to_fp16, x = x_5_cast_fp16)[name = tensor<string, []>("x_in_9_cast_fp16")];
tensor<int32, [3]> var_249_begin_0 = const()[name = tensor<string, []>("op_249_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_249_end_0 = const()[name = tensor<string, []>("op_249_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_249_end_mask_0 = const()[name = tensor<string, []>("op_249_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_249_cast_fp16 = slice_by_index(begin = var_249_begin_0, end = var_249_end_0, end_mask = var_249_end_mask_0, x = x_in_9_cast_fp16)[name = tensor<string, []>("op_249_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_251_cast_fp16 = tanh(x = var_249_cast_fp16)[name = tensor<string, []>("op_251_cast_fp16")];
tensor<int32, [3]> var_253_begin_0 = const()[name = tensor<string, []>("op_253_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_253_end_0 = const()[name = tensor<string, []>("op_253_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_253_end_mask_0 = const()[name = tensor<string, []>("op_253_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_253_cast_fp16 = slice_by_index(begin = var_253_begin_0, end = var_253_end_0, end_mask = var_253_end_mask_0, x = x_in_9_cast_fp16)[name = tensor<string, []>("op_253_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_255_cast_fp16 = sigmoid(x = var_253_cast_fp16)[name = tensor<string, []>("op_255_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_29_cast_fp16 = mul(x = var_251_cast_fp16, y = var_255_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
tensor<string, []> res_skip_acts_9_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_9_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_9_strides_0 = const()[name = tensor<string, []>("res_skip_acts_9_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_9_pad_0 = const()[name = tensor<string, []>("res_skip_acts_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_9_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_9_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_9_groups_0 = const()[name = tensor<string, []>("res_skip_acts_9_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_4_enc_res_skip_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1111360)))];
tensor<fp16, [192]> flow_flows_4_enc_res_skip_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1148288)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_9_cast_fp16 = conv(bias = flow_flows_4_enc_res_skip_layers_0_bias_to_fp16, dilations = res_skip_acts_9_dilations_0, groups = res_skip_acts_9_groups_0, pad = res_skip_acts_9_pad_0, pad_type = res_skip_acts_9_pad_type_0, strides = res_skip_acts_9_strides_0, weight = flow_flows_4_enc_res_skip_layers_0_weight_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("res_skip_acts_9_cast_fp16")];
tensor<int32, [3]> var_266_begin_0 = const()[name = tensor<string, []>("op_266_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_266_end_0 = const()[name = tensor<string, []>("op_266_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_266_end_mask_0 = const()[name = tensor<string, []>("op_266_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_266_cast_fp16 = slice_by_index(begin = var_266_begin_0, end = var_266_end_0, end_mask = var_266_end_mask_0, x = res_skip_acts_9_cast_fp16)[name = tensor<string, []>("op_266_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_268_cast_fp16 = add(x = x_5_cast_fp16, y = var_266_cast_fp16)[name = tensor<string, []>("op_268_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_33_cast_fp16 = mul(x = var_268_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
tensor<int32, [3]> var_271_begin_0 = const()[name = tensor<string, []>("op_271_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_271_end_0 = const()[name = tensor<string, []>("op_271_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_271_end_mask_0 = const()[name = tensor<string, []>("op_271_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_271_cast_fp16 = slice_by_index(begin = var_271_begin_0, end = var_271_end_0, end_mask = var_271_end_mask_0, x = res_skip_acts_9_cast_fp16)[name = tensor<string, []>("op_271_cast_fp16")];
tensor<string, []> x_in_11_pad_type_0 = const()[name = tensor<string, []>("x_in_11_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_11_pad_0 = const()[name = tensor<string, []>("x_in_11_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_11_strides_0 = const()[name = tensor<string, []>("x_in_11_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_11_dilations_0 = const()[name = tensor<string, []>("x_in_11_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_11_groups_0 = const()[name = tensor<string, []>("x_in_11_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_4_enc_in_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1148736)))];
tensor<fp16, [192]> flow_flows_4_enc_in_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333120)))];
tensor<fp16, [1, 192, 384]> x_in_11_cast_fp16 = conv(bias = flow_flows_4_enc_in_layers_1_bias_to_fp16, dilations = x_in_11_dilations_0, groups = x_in_11_groups_0, pad = x_in_11_pad_0, pad_type = x_in_11_pad_type_0, strides = x_in_11_strides_0, weight = flow_flows_4_enc_in_layers_1_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("x_in_11_cast_fp16")];
tensor<int32, [3]> var_284_begin_0 = const()[name = tensor<string, []>("op_284_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_284_end_0 = const()[name = tensor<string, []>("op_284_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_284_end_mask_0 = const()[name = tensor<string, []>("op_284_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_284_cast_fp16 = slice_by_index(begin = var_284_begin_0, end = var_284_end_0, end_mask = var_284_end_mask_0, x = x_in_11_cast_fp16)[name = tensor<string, []>("op_284_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_286_cast_fp16 = tanh(x = var_284_cast_fp16)[name = tensor<string, []>("op_286_cast_fp16")];
tensor<int32, [3]> var_288_begin_0 = const()[name = tensor<string, []>("op_288_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_288_end_0 = const()[name = tensor<string, []>("op_288_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_288_end_mask_0 = const()[name = tensor<string, []>("op_288_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_288_cast_fp16 = slice_by_index(begin = var_288_begin_0, end = var_288_end_0, end_mask = var_288_end_mask_0, x = x_in_11_cast_fp16)[name = tensor<string, []>("op_288_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_290_cast_fp16 = sigmoid(x = var_288_cast_fp16)[name = tensor<string, []>("op_290_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_35_cast_fp16 = mul(x = var_286_cast_fp16, y = var_290_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
tensor<string, []> res_skip_acts_11_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_11_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_11_strides_0 = const()[name = tensor<string, []>("res_skip_acts_11_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_11_pad_0 = const()[name = tensor<string, []>("res_skip_acts_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_11_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_11_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_11_groups_0 = const()[name = tensor<string, []>("res_skip_acts_11_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_4_enc_res_skip_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333568)))];
tensor<fp16, [192]> flow_flows_4_enc_res_skip_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1370496)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_11_cast_fp16 = conv(bias = flow_flows_4_enc_res_skip_layers_1_bias_to_fp16, dilations = res_skip_acts_11_dilations_0, groups = res_skip_acts_11_groups_0, pad = res_skip_acts_11_pad_0, pad_type = res_skip_acts_11_pad_type_0, strides = res_skip_acts_11_strides_0, weight = flow_flows_4_enc_res_skip_layers_1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("res_skip_acts_11_cast_fp16")];
tensor<int32, [3]> var_301_begin_0 = const()[name = tensor<string, []>("op_301_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_301_end_0 = const()[name = tensor<string, []>("op_301_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_301_end_mask_0 = const()[name = tensor<string, []>("op_301_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_301_cast_fp16 = slice_by_index(begin = var_301_begin_0, end = var_301_end_0, end_mask = var_301_end_mask_0, x = res_skip_acts_11_cast_fp16)[name = tensor<string, []>("op_301_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_303_cast_fp16 = add(x = input_33_cast_fp16, y = var_301_cast_fp16)[name = tensor<string, []>("op_303_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_39_cast_fp16 = mul(x = var_303_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
tensor<int32, [3]> var_306_begin_0 = const()[name = tensor<string, []>("op_306_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_306_end_0 = const()[name = tensor<string, []>("op_306_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_306_end_mask_0 = const()[name = tensor<string, []>("op_306_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_306_cast_fp16 = slice_by_index(begin = var_306_begin_0, end = var_306_end_0, end_mask = var_306_end_mask_0, x = res_skip_acts_11_cast_fp16)[name = tensor<string, []>("op_306_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_15_cast_fp16 = add(x = var_271_cast_fp16, y = var_306_cast_fp16)[name = tensor<string, []>("output_15_cast_fp16")];
tensor<string, []> x_in_13_pad_type_0 = const()[name = tensor<string, []>("x_in_13_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_13_pad_0 = const()[name = tensor<string, []>("x_in_13_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_13_strides_0 = const()[name = tensor<string, []>("x_in_13_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_13_dilations_0 = const()[name = tensor<string, []>("x_in_13_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_13_groups_0 = const()[name = tensor<string, []>("x_in_13_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_4_enc_in_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1370944)))];
tensor<fp16, [192]> flow_flows_4_enc_in_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1555328)))];
tensor<fp16, [1, 192, 384]> x_in_13_cast_fp16 = conv(bias = flow_flows_4_enc_in_layers_2_bias_to_fp16, dilations = x_in_13_dilations_0, groups = x_in_13_groups_0, pad = x_in_13_pad_0, pad_type = x_in_13_pad_type_0, strides = x_in_13_strides_0, weight = flow_flows_4_enc_in_layers_2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("x_in_13_cast_fp16")];
tensor<int32, [3]> var_319_begin_0 = const()[name = tensor<string, []>("op_319_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_319_end_0 = const()[name = tensor<string, []>("op_319_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_319_end_mask_0 = const()[name = tensor<string, []>("op_319_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_319_cast_fp16 = slice_by_index(begin = var_319_begin_0, end = var_319_end_0, end_mask = var_319_end_mask_0, x = x_in_13_cast_fp16)[name = tensor<string, []>("op_319_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_321_cast_fp16 = tanh(x = var_319_cast_fp16)[name = tensor<string, []>("op_321_cast_fp16")];
tensor<int32, [3]> var_323_begin_0 = const()[name = tensor<string, []>("op_323_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_323_end_0 = const()[name = tensor<string, []>("op_323_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_323_end_mask_0 = const()[name = tensor<string, []>("op_323_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_323_cast_fp16 = slice_by_index(begin = var_323_begin_0, end = var_323_end_0, end_mask = var_323_end_mask_0, x = x_in_13_cast_fp16)[name = tensor<string, []>("op_323_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_325_cast_fp16 = sigmoid(x = var_323_cast_fp16)[name = tensor<string, []>("op_325_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_41_cast_fp16 = mul(x = var_321_cast_fp16, y = var_325_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
tensor<string, []> res_skip_acts_13_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_13_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_13_strides_0 = const()[name = tensor<string, []>("res_skip_acts_13_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_13_pad_0 = const()[name = tensor<string, []>("res_skip_acts_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_13_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_13_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_13_groups_0 = const()[name = tensor<string, []>("res_skip_acts_13_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_4_enc_res_skip_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1555776)))];
tensor<fp16, [192]> flow_flows_4_enc_res_skip_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1592704)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_13_cast_fp16 = conv(bias = flow_flows_4_enc_res_skip_layers_2_bias_to_fp16, dilations = res_skip_acts_13_dilations_0, groups = res_skip_acts_13_groups_0, pad = res_skip_acts_13_pad_0, pad_type = res_skip_acts_13_pad_type_0, strides = res_skip_acts_13_strides_0, weight = flow_flows_4_enc_res_skip_layers_2_weight_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("res_skip_acts_13_cast_fp16")];
tensor<int32, [3]> var_336_begin_0 = const()[name = tensor<string, []>("op_336_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_336_end_0 = const()[name = tensor<string, []>("op_336_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_336_end_mask_0 = const()[name = tensor<string, []>("op_336_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_336_cast_fp16 = slice_by_index(begin = var_336_begin_0, end = var_336_end_0, end_mask = var_336_end_mask_0, x = res_skip_acts_13_cast_fp16)[name = tensor<string, []>("op_336_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_338_cast_fp16 = add(x = input_39_cast_fp16, y = var_336_cast_fp16)[name = tensor<string, []>("op_338_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_45_cast_fp16 = mul(x = var_338_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
tensor<int32, [3]> var_341_begin_0 = const()[name = tensor<string, []>("op_341_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_341_end_0 = const()[name = tensor<string, []>("op_341_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_341_end_mask_0 = const()[name = tensor<string, []>("op_341_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_341_cast_fp16 = slice_by_index(begin = var_341_begin_0, end = var_341_end_0, end_mask = var_341_end_mask_0, x = res_skip_acts_13_cast_fp16)[name = tensor<string, []>("op_341_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_17_cast_fp16 = add(x = output_15_cast_fp16, y = var_341_cast_fp16)[name = tensor<string, []>("output_17_cast_fp16")];
tensor<string, []> x_in_15_pad_type_0 = const()[name = tensor<string, []>("x_in_15_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_15_pad_0 = const()[name = tensor<string, []>("x_in_15_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_15_strides_0 = const()[name = tensor<string, []>("x_in_15_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_15_dilations_0 = const()[name = tensor<string, []>("x_in_15_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_15_groups_0 = const()[name = tensor<string, []>("x_in_15_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_4_enc_in_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_3_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1593152)))];
tensor<fp16, [192]> flow_flows_4_enc_in_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_in_layers_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1777536)))];
tensor<fp16, [1, 192, 384]> x_in_15_cast_fp16 = conv(bias = flow_flows_4_enc_in_layers_3_bias_to_fp16, dilations = x_in_15_dilations_0, groups = x_in_15_groups_0, pad = x_in_15_pad_0, pad_type = x_in_15_pad_type_0, strides = x_in_15_strides_0, weight = flow_flows_4_enc_in_layers_3_weight_to_fp16, x = input_45_cast_fp16)[name = tensor<string, []>("x_in_15_cast_fp16")];
tensor<int32, [3]> var_354_begin_0 = const()[name = tensor<string, []>("op_354_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_354_end_0 = const()[name = tensor<string, []>("op_354_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_354_end_mask_0 = const()[name = tensor<string, []>("op_354_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_354_cast_fp16 = slice_by_index(begin = var_354_begin_0, end = var_354_end_0, end_mask = var_354_end_mask_0, x = x_in_15_cast_fp16)[name = tensor<string, []>("op_354_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_356_cast_fp16 = tanh(x = var_354_cast_fp16)[name = tensor<string, []>("op_356_cast_fp16")];
tensor<int32, [3]> var_358_begin_0 = const()[name = tensor<string, []>("op_358_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_358_end_0 = const()[name = tensor<string, []>("op_358_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_358_end_mask_0 = const()[name = tensor<string, []>("op_358_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_358_cast_fp16 = slice_by_index(begin = var_358_begin_0, end = var_358_end_0, end_mask = var_358_end_mask_0, x = x_in_15_cast_fp16)[name = tensor<string, []>("op_358_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_360_cast_fp16 = sigmoid(x = var_358_cast_fp16)[name = tensor<string, []>("op_360_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_47_cast_fp16 = mul(x = var_356_cast_fp16, y = var_360_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
tensor<string, []> res_skip_acts_15_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_15_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_15_strides_0 = const()[name = tensor<string, []>("res_skip_acts_15_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_15_pad_0 = const()[name = tensor<string, []>("res_skip_acts_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_15_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_15_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_15_groups_0 = const()[name = tensor<string, []>("res_skip_acts_15_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_4_enc_res_skip_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_3_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1777984)))];
tensor<fp16, [96]> flow_flows_4_enc_res_skip_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_enc_res_skip_layers_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1796480)))];
tensor<fp16, [1, 96, 384]> res_skip_acts_15_cast_fp16 = conv(bias = flow_flows_4_enc_res_skip_layers_3_bias_to_fp16, dilations = res_skip_acts_15_dilations_0, groups = res_skip_acts_15_groups_0, pad = res_skip_acts_15_pad_0, pad_type = res_skip_acts_15_pad_type_0, strides = res_skip_acts_15_strides_0, weight = flow_flows_4_enc_res_skip_layers_3_weight_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("res_skip_acts_15_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_19_cast_fp16 = add(x = output_17_cast_fp16, y = res_skip_acts_15_cast_fp16)[name = tensor<string, []>("output_19_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_51_cast_fp16 = mul(x = output_19_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
tensor<string, []> var_378_pad_type_0 = const()[name = tensor<string, []>("op_378_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_378_strides_0 = const()[name = tensor<string, []>("op_378_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_378_pad_0 = const()[name = tensor<string, []>("op_378_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_378_dilations_0 = const()[name = tensor<string, []>("op_378_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_378_groups_0 = const()[name = tensor<string, []>("op_378_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_4_post_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_post_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1796736)))];
tensor<fp16, [96]> flow_flows_4_post_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_4_post_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1815232)))];
tensor<fp16, [1, 96, 384]> var_378_cast_fp16 = conv(bias = flow_flows_4_post_bias_to_fp16, dilations = var_378_dilations_0, groups = var_378_groups_0, pad = var_378_pad_0, pad_type = var_378_pad_type_0, strides = var_378_strides_0, weight = flow_flows_4_post_weight_to_fp16, x = input_51_cast_fp16)[name = tensor<string, []>("op_378_cast_fp16")];
tensor<fp16, [1, 96, 384]> stats_3_cast_fp16 = mul(x = var_378_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("stats_3_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_381_cast_fp16 = sub(x = var_211_cast_fp16_1, y = stats_3_cast_fp16)[name = tensor<string, []>("op_381_cast_fp16")];
tensor<fp16, [1, 96, 384]> x1_7_cast_fp16 = mul(x = var_381_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x1_7_cast_fp16")];
tensor<bool, []> x_7_interleave_0 = const()[name = tensor<string, []>("x_7_interleave_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 192, 384]> x_7_cast_fp16 = concat(axis = var_13, interleave = x_7_interleave_0, values = (var_211_cast_fp16_0, x1_7_cast_fp16))[name = tensor<string, []>("x_7_cast_fp16")];
tensor<int32, [1]> var_388 = const()[name = tensor<string, []>("op_388"), val = tensor<int32, [1]>([1])];
tensor<fp16, [1, 192, 384]> var_389_cast_fp16 = reverse(axes = var_388, x = x_7_cast_fp16)[name = tensor<string, []>("op_389_cast_fp16")];
tensor<int32, [2]> var_393 = const()[name = tensor<string, []>("op_393"), val = tensor<int32, [2]>([96, 96])];
tensor<int32, []> var_394_axis_0 = const()[name = tensor<string, []>("op_394_axis_0"), val = tensor<int32, []>(1)];
tensor<fp16, [1, 96, 384]> var_394_cast_fp16_0, tensor<fp16, [1, 96, 384]> var_394_cast_fp16_1 = split(axis = var_394_axis_0, split_sizes = var_393, x = var_389_cast_fp16)[name = tensor<string, []>("op_394_cast_fp16")];
tensor<string, []> var_403_pad_type_0 = const()[name = tensor<string, []>("op_403_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_403_strides_0 = const()[name = tensor<string, []>("op_403_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_403_pad_0 = const()[name = tensor<string, []>("op_403_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_403_dilations_0 = const()[name = tensor<string, []>("op_403_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_403_groups_0 = const()[name = tensor<string, []>("op_403_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_2_pre_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_pre_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1815488)))];
tensor<fp16, [96]> flow_flows_2_pre_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_pre_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1833984)))];
tensor<fp16, [1, 96, 384]> var_403_cast_fp16 = conv(bias = flow_flows_2_pre_bias_to_fp16, dilations = var_403_dilations_0, groups = var_403_groups_0, pad = var_403_pad_0, pad_type = var_403_pad_type_0, strides = var_403_strides_0, weight = flow_flows_2_pre_weight_to_fp16, x = var_394_cast_fp16_0)[name = tensor<string, []>("op_403_cast_fp16")];
tensor<fp16, [1, 96, 384]> x_9_cast_fp16 = mul(x = var_403_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x_9_cast_fp16")];
tensor<string, []> x_in_17_pad_type_0 = const()[name = tensor<string, []>("x_in_17_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_17_pad_0 = const()[name = tensor<string, []>("x_in_17_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_17_strides_0 = const()[name = tensor<string, []>("x_in_17_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_17_dilations_0 = const()[name = tensor<string, []>("x_in_17_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_17_groups_0 = const()[name = tensor<string, []>("x_in_17_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_2_enc_in_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1834240)))];
tensor<fp16, [192]> flow_flows_2_enc_in_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2018624)))];
tensor<fp16, [1, 192, 384]> x_in_17_cast_fp16 = conv(bias = flow_flows_2_enc_in_layers_0_bias_to_fp16, dilations = x_in_17_dilations_0, groups = x_in_17_groups_0, pad = x_in_17_pad_0, pad_type = x_in_17_pad_type_0, strides = x_in_17_strides_0, weight = flow_flows_2_enc_in_layers_0_weight_to_fp16, x = x_9_cast_fp16)[name = tensor<string, []>("x_in_17_cast_fp16")];
tensor<int32, [3]> var_432_begin_0 = const()[name = tensor<string, []>("op_432_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_432_end_0 = const()[name = tensor<string, []>("op_432_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_432_end_mask_0 = const()[name = tensor<string, []>("op_432_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_432_cast_fp16 = slice_by_index(begin = var_432_begin_0, end = var_432_end_0, end_mask = var_432_end_mask_0, x = x_in_17_cast_fp16)[name = tensor<string, []>("op_432_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_434_cast_fp16 = tanh(x = var_432_cast_fp16)[name = tensor<string, []>("op_434_cast_fp16")];
tensor<int32, [3]> var_436_begin_0 = const()[name = tensor<string, []>("op_436_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_436_end_0 = const()[name = tensor<string, []>("op_436_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_436_end_mask_0 = const()[name = tensor<string, []>("op_436_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_436_cast_fp16 = slice_by_index(begin = var_436_begin_0, end = var_436_end_0, end_mask = var_436_end_mask_0, x = x_in_17_cast_fp16)[name = tensor<string, []>("op_436_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_438_cast_fp16 = sigmoid(x = var_436_cast_fp16)[name = tensor<string, []>("op_438_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_55_cast_fp16 = mul(x = var_434_cast_fp16, y = var_438_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")];
tensor<string, []> res_skip_acts_17_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_17_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_17_strides_0 = const()[name = tensor<string, []>("res_skip_acts_17_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_17_pad_0 = const()[name = tensor<string, []>("res_skip_acts_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_17_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_17_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_17_groups_0 = const()[name = tensor<string, []>("res_skip_acts_17_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_2_enc_res_skip_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2019072)))];
tensor<fp16, [192]> flow_flows_2_enc_res_skip_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2056000)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_17_cast_fp16 = conv(bias = flow_flows_2_enc_res_skip_layers_0_bias_to_fp16, dilations = res_skip_acts_17_dilations_0, groups = res_skip_acts_17_groups_0, pad = res_skip_acts_17_pad_0, pad_type = res_skip_acts_17_pad_type_0, strides = res_skip_acts_17_strides_0, weight = flow_flows_2_enc_res_skip_layers_0_weight_to_fp16, x = input_55_cast_fp16)[name = tensor<string, []>("res_skip_acts_17_cast_fp16")];
tensor<int32, [3]> var_449_begin_0 = const()[name = tensor<string, []>("op_449_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_449_end_0 = const()[name = tensor<string, []>("op_449_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_449_end_mask_0 = const()[name = tensor<string, []>("op_449_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_449_cast_fp16 = slice_by_index(begin = var_449_begin_0, end = var_449_end_0, end_mask = var_449_end_mask_0, x = res_skip_acts_17_cast_fp16)[name = tensor<string, []>("op_449_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_451_cast_fp16 = add(x = x_9_cast_fp16, y = var_449_cast_fp16)[name = tensor<string, []>("op_451_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_59_cast_fp16 = mul(x = var_451_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
tensor<int32, [3]> var_454_begin_0 = const()[name = tensor<string, []>("op_454_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_454_end_0 = const()[name = tensor<string, []>("op_454_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_454_end_mask_0 = const()[name = tensor<string, []>("op_454_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_454_cast_fp16 = slice_by_index(begin = var_454_begin_0, end = var_454_end_0, end_mask = var_454_end_mask_0, x = res_skip_acts_17_cast_fp16)[name = tensor<string, []>("op_454_cast_fp16")];
tensor<string, []> x_in_19_pad_type_0 = const()[name = tensor<string, []>("x_in_19_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_19_pad_0 = const()[name = tensor<string, []>("x_in_19_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_19_strides_0 = const()[name = tensor<string, []>("x_in_19_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_19_dilations_0 = const()[name = tensor<string, []>("x_in_19_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_19_groups_0 = const()[name = tensor<string, []>("x_in_19_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_2_enc_in_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2056448)))];
tensor<fp16, [192]> flow_flows_2_enc_in_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2240832)))];
tensor<fp16, [1, 192, 384]> x_in_19_cast_fp16 = conv(bias = flow_flows_2_enc_in_layers_1_bias_to_fp16, dilations = x_in_19_dilations_0, groups = x_in_19_groups_0, pad = x_in_19_pad_0, pad_type = x_in_19_pad_type_0, strides = x_in_19_strides_0, weight = flow_flows_2_enc_in_layers_1_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("x_in_19_cast_fp16")];
tensor<int32, [3]> var_467_begin_0 = const()[name = tensor<string, []>("op_467_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_467_end_0 = const()[name = tensor<string, []>("op_467_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_467_end_mask_0 = const()[name = tensor<string, []>("op_467_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_467_cast_fp16 = slice_by_index(begin = var_467_begin_0, end = var_467_end_0, end_mask = var_467_end_mask_0, x = x_in_19_cast_fp16)[name = tensor<string, []>("op_467_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_469_cast_fp16 = tanh(x = var_467_cast_fp16)[name = tensor<string, []>("op_469_cast_fp16")];
tensor<int32, [3]> var_471_begin_0 = const()[name = tensor<string, []>("op_471_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_471_end_0 = const()[name = tensor<string, []>("op_471_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_471_end_mask_0 = const()[name = tensor<string, []>("op_471_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_471_cast_fp16 = slice_by_index(begin = var_471_begin_0, end = var_471_end_0, end_mask = var_471_end_mask_0, x = x_in_19_cast_fp16)[name = tensor<string, []>("op_471_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_473_cast_fp16 = sigmoid(x = var_471_cast_fp16)[name = tensor<string, []>("op_473_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_61_cast_fp16 = mul(x = var_469_cast_fp16, y = var_473_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
tensor<string, []> res_skip_acts_19_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_19_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_19_strides_0 = const()[name = tensor<string, []>("res_skip_acts_19_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_19_pad_0 = const()[name = tensor<string, []>("res_skip_acts_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_19_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_19_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_19_groups_0 = const()[name = tensor<string, []>("res_skip_acts_19_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_2_enc_res_skip_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2241280)))];
tensor<fp16, [192]> flow_flows_2_enc_res_skip_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2278208)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_19_cast_fp16 = conv(bias = flow_flows_2_enc_res_skip_layers_1_bias_to_fp16, dilations = res_skip_acts_19_dilations_0, groups = res_skip_acts_19_groups_0, pad = res_skip_acts_19_pad_0, pad_type = res_skip_acts_19_pad_type_0, strides = res_skip_acts_19_strides_0, weight = flow_flows_2_enc_res_skip_layers_1_weight_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("res_skip_acts_19_cast_fp16")];
tensor<int32, [3]> var_484_begin_0 = const()[name = tensor<string, []>("op_484_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_484_end_0 = const()[name = tensor<string, []>("op_484_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_484_end_mask_0 = const()[name = tensor<string, []>("op_484_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_484_cast_fp16 = slice_by_index(begin = var_484_begin_0, end = var_484_end_0, end_mask = var_484_end_mask_0, x = res_skip_acts_19_cast_fp16)[name = tensor<string, []>("op_484_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_486_cast_fp16 = add(x = input_59_cast_fp16, y = var_484_cast_fp16)[name = tensor<string, []>("op_486_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_65_cast_fp16 = mul(x = var_486_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
tensor<int32, [3]> var_489_begin_0 = const()[name = tensor<string, []>("op_489_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_489_end_0 = const()[name = tensor<string, []>("op_489_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_489_end_mask_0 = const()[name = tensor<string, []>("op_489_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_489_cast_fp16 = slice_by_index(begin = var_489_begin_0, end = var_489_end_0, end_mask = var_489_end_mask_0, x = res_skip_acts_19_cast_fp16)[name = tensor<string, []>("op_489_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_25_cast_fp16 = add(x = var_454_cast_fp16, y = var_489_cast_fp16)[name = tensor<string, []>("output_25_cast_fp16")];
tensor<string, []> x_in_21_pad_type_0 = const()[name = tensor<string, []>("x_in_21_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_21_pad_0 = const()[name = tensor<string, []>("x_in_21_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_21_strides_0 = const()[name = tensor<string, []>("x_in_21_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_21_dilations_0 = const()[name = tensor<string, []>("x_in_21_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_21_groups_0 = const()[name = tensor<string, []>("x_in_21_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_2_enc_in_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2278656)))];
tensor<fp16, [192]> flow_flows_2_enc_in_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2463040)))];
tensor<fp16, [1, 192, 384]> x_in_21_cast_fp16 = conv(bias = flow_flows_2_enc_in_layers_2_bias_to_fp16, dilations = x_in_21_dilations_0, groups = x_in_21_groups_0, pad = x_in_21_pad_0, pad_type = x_in_21_pad_type_0, strides = x_in_21_strides_0, weight = flow_flows_2_enc_in_layers_2_weight_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("x_in_21_cast_fp16")];
tensor<int32, [3]> var_502_begin_0 = const()[name = tensor<string, []>("op_502_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_502_end_0 = const()[name = tensor<string, []>("op_502_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_502_end_mask_0 = const()[name = tensor<string, []>("op_502_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_502_cast_fp16 = slice_by_index(begin = var_502_begin_0, end = var_502_end_0, end_mask = var_502_end_mask_0, x = x_in_21_cast_fp16)[name = tensor<string, []>("op_502_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_504_cast_fp16 = tanh(x = var_502_cast_fp16)[name = tensor<string, []>("op_504_cast_fp16")];
tensor<int32, [3]> var_506_begin_0 = const()[name = tensor<string, []>("op_506_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_506_end_0 = const()[name = tensor<string, []>("op_506_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_506_end_mask_0 = const()[name = tensor<string, []>("op_506_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_506_cast_fp16 = slice_by_index(begin = var_506_begin_0, end = var_506_end_0, end_mask = var_506_end_mask_0, x = x_in_21_cast_fp16)[name = tensor<string, []>("op_506_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_508_cast_fp16 = sigmoid(x = var_506_cast_fp16)[name = tensor<string, []>("op_508_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_67_cast_fp16 = mul(x = var_504_cast_fp16, y = var_508_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
tensor<string, []> res_skip_acts_21_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_21_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_21_strides_0 = const()[name = tensor<string, []>("res_skip_acts_21_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_21_pad_0 = const()[name = tensor<string, []>("res_skip_acts_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_21_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_21_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_21_groups_0 = const()[name = tensor<string, []>("res_skip_acts_21_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_2_enc_res_skip_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2463488)))];
tensor<fp16, [192]> flow_flows_2_enc_res_skip_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2500416)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_21_cast_fp16 = conv(bias = flow_flows_2_enc_res_skip_layers_2_bias_to_fp16, dilations = res_skip_acts_21_dilations_0, groups = res_skip_acts_21_groups_0, pad = res_skip_acts_21_pad_0, pad_type = res_skip_acts_21_pad_type_0, strides = res_skip_acts_21_strides_0, weight = flow_flows_2_enc_res_skip_layers_2_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("res_skip_acts_21_cast_fp16")];
tensor<int32, [3]> var_519_begin_0 = const()[name = tensor<string, []>("op_519_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_519_end_0 = const()[name = tensor<string, []>("op_519_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_519_end_mask_0 = const()[name = tensor<string, []>("op_519_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_519_cast_fp16 = slice_by_index(begin = var_519_begin_0, end = var_519_end_0, end_mask = var_519_end_mask_0, x = res_skip_acts_21_cast_fp16)[name = tensor<string, []>("op_519_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_521_cast_fp16 = add(x = input_65_cast_fp16, y = var_519_cast_fp16)[name = tensor<string, []>("op_521_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_71_cast_fp16 = mul(x = var_521_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
tensor<int32, [3]> var_524_begin_0 = const()[name = tensor<string, []>("op_524_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_524_end_0 = const()[name = tensor<string, []>("op_524_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_524_end_mask_0 = const()[name = tensor<string, []>("op_524_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_524_cast_fp16 = slice_by_index(begin = var_524_begin_0, end = var_524_end_0, end_mask = var_524_end_mask_0, x = res_skip_acts_21_cast_fp16)[name = tensor<string, []>("op_524_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_27_cast_fp16 = add(x = output_25_cast_fp16, y = var_524_cast_fp16)[name = tensor<string, []>("output_27_cast_fp16")];
tensor<string, []> x_in_23_pad_type_0 = const()[name = tensor<string, []>("x_in_23_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_23_pad_0 = const()[name = tensor<string, []>("x_in_23_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_23_strides_0 = const()[name = tensor<string, []>("x_in_23_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_23_dilations_0 = const()[name = tensor<string, []>("x_in_23_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_23_groups_0 = const()[name = tensor<string, []>("x_in_23_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_2_enc_in_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_3_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2500864)))];
tensor<fp16, [192]> flow_flows_2_enc_in_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_in_layers_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2685248)))];
tensor<fp16, [1, 192, 384]> x_in_23_cast_fp16 = conv(bias = flow_flows_2_enc_in_layers_3_bias_to_fp16, dilations = x_in_23_dilations_0, groups = x_in_23_groups_0, pad = x_in_23_pad_0, pad_type = x_in_23_pad_type_0, strides = x_in_23_strides_0, weight = flow_flows_2_enc_in_layers_3_weight_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("x_in_23_cast_fp16")];
tensor<int32, [3]> var_537_begin_0 = const()[name = tensor<string, []>("op_537_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_537_end_0 = const()[name = tensor<string, []>("op_537_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_537_end_mask_0 = const()[name = tensor<string, []>("op_537_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_537_cast_fp16 = slice_by_index(begin = var_537_begin_0, end = var_537_end_0, end_mask = var_537_end_mask_0, x = x_in_23_cast_fp16)[name = tensor<string, []>("op_537_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_539_cast_fp16 = tanh(x = var_537_cast_fp16)[name = tensor<string, []>("op_539_cast_fp16")];
tensor<int32, [3]> var_541_begin_0 = const()[name = tensor<string, []>("op_541_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_541_end_0 = const()[name = tensor<string, []>("op_541_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_541_end_mask_0 = const()[name = tensor<string, []>("op_541_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_541_cast_fp16 = slice_by_index(begin = var_541_begin_0, end = var_541_end_0, end_mask = var_541_end_mask_0, x = x_in_23_cast_fp16)[name = tensor<string, []>("op_541_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_543_cast_fp16 = sigmoid(x = var_541_cast_fp16)[name = tensor<string, []>("op_543_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_73_cast_fp16 = mul(x = var_539_cast_fp16, y = var_543_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
tensor<string, []> res_skip_acts_23_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_23_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_23_strides_0 = const()[name = tensor<string, []>("res_skip_acts_23_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_23_pad_0 = const()[name = tensor<string, []>("res_skip_acts_23_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_23_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_23_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_23_groups_0 = const()[name = tensor<string, []>("res_skip_acts_23_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_2_enc_res_skip_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_3_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2685696)))];
tensor<fp16, [96]> flow_flows_2_enc_res_skip_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_enc_res_skip_layers_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2704192)))];
tensor<fp16, [1, 96, 384]> res_skip_acts_23_cast_fp16 = conv(bias = flow_flows_2_enc_res_skip_layers_3_bias_to_fp16, dilations = res_skip_acts_23_dilations_0, groups = res_skip_acts_23_groups_0, pad = res_skip_acts_23_pad_0, pad_type = res_skip_acts_23_pad_type_0, strides = res_skip_acts_23_strides_0, weight = flow_flows_2_enc_res_skip_layers_3_weight_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("res_skip_acts_23_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_29_cast_fp16 = add(x = output_27_cast_fp16, y = res_skip_acts_23_cast_fp16)[name = tensor<string, []>("output_29_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_77_cast_fp16 = mul(x = output_29_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
tensor<string, []> var_561_pad_type_0 = const()[name = tensor<string, []>("op_561_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_561_strides_0 = const()[name = tensor<string, []>("op_561_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_561_pad_0 = const()[name = tensor<string, []>("op_561_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_561_dilations_0 = const()[name = tensor<string, []>("op_561_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_561_groups_0 = const()[name = tensor<string, []>("op_561_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_2_post_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_post_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2704448)))];
tensor<fp16, [96]> flow_flows_2_post_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_2_post_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2722944)))];
tensor<fp16, [1, 96, 384]> var_561_cast_fp16 = conv(bias = flow_flows_2_post_bias_to_fp16, dilations = var_561_dilations_0, groups = var_561_groups_0, pad = var_561_pad_0, pad_type = var_561_pad_type_0, strides = var_561_strides_0, weight = flow_flows_2_post_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("op_561_cast_fp16")];
tensor<fp16, [1, 96, 384]> stats_5_cast_fp16 = mul(x = var_561_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("stats_5_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_564_cast_fp16 = sub(x = var_394_cast_fp16_1, y = stats_5_cast_fp16)[name = tensor<string, []>("op_564_cast_fp16")];
tensor<fp16, [1, 96, 384]> x1_11_cast_fp16 = mul(x = var_564_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x1_11_cast_fp16")];
tensor<bool, []> x_11_interleave_0 = const()[name = tensor<string, []>("x_11_interleave_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 192, 384]> x_11_cast_fp16 = concat(axis = var_13, interleave = x_11_interleave_0, values = (var_394_cast_fp16_0, x1_11_cast_fp16))[name = tensor<string, []>("x_11_cast_fp16")];
tensor<int32, [1]> var_571 = const()[name = tensor<string, []>("op_571"), val = tensor<int32, [1]>([1])];
tensor<fp16, [1, 192, 384]> var_572_cast_fp16 = reverse(axes = var_571, x = x_11_cast_fp16)[name = tensor<string, []>("op_572_cast_fp16")];
tensor<int32, [2]> var_576 = const()[name = tensor<string, []>("op_576"), val = tensor<int32, [2]>([96, 96])];
tensor<int32, []> var_577_axis_0 = const()[name = tensor<string, []>("op_577_axis_0"), val = tensor<int32, []>(1)];
tensor<fp16, [1, 96, 384]> var_577_cast_fp16_0, tensor<fp16, [1, 96, 384]> var_577_cast_fp16_1 = split(axis = var_577_axis_0, split_sizes = var_576, x = var_572_cast_fp16)[name = tensor<string, []>("op_577_cast_fp16")];
tensor<string, []> var_586_pad_type_0 = const()[name = tensor<string, []>("op_586_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_586_strides_0 = const()[name = tensor<string, []>("op_586_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_586_pad_0 = const()[name = tensor<string, []>("op_586_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_586_dilations_0 = const()[name = tensor<string, []>("op_586_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_586_groups_0 = const()[name = tensor<string, []>("op_586_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_0_pre_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_pre_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2723200)))];
tensor<fp16, [96]> flow_flows_0_pre_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_pre_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2741696)))];
tensor<fp16, [1, 96, 384]> var_586_cast_fp16 = conv(bias = flow_flows_0_pre_bias_to_fp16, dilations = var_586_dilations_0, groups = var_586_groups_0, pad = var_586_pad_0, pad_type = var_586_pad_type_0, strides = var_586_strides_0, weight = flow_flows_0_pre_weight_to_fp16, x = var_577_cast_fp16_0)[name = tensor<string, []>("op_586_cast_fp16")];
tensor<fp16, [1, 96, 384]> x_13_cast_fp16 = mul(x = var_586_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x_13_cast_fp16")];
tensor<string, []> x_in_25_pad_type_0 = const()[name = tensor<string, []>("x_in_25_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_25_pad_0 = const()[name = tensor<string, []>("x_in_25_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_25_strides_0 = const()[name = tensor<string, []>("x_in_25_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_25_dilations_0 = const()[name = tensor<string, []>("x_in_25_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_25_groups_0 = const()[name = tensor<string, []>("x_in_25_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_0_enc_in_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2741952)))];
tensor<fp16, [192]> flow_flows_0_enc_in_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2926336)))];
tensor<fp16, [1, 192, 384]> x_in_25_cast_fp16 = conv(bias = flow_flows_0_enc_in_layers_0_bias_to_fp16, dilations = x_in_25_dilations_0, groups = x_in_25_groups_0, pad = x_in_25_pad_0, pad_type = x_in_25_pad_type_0, strides = x_in_25_strides_0, weight = flow_flows_0_enc_in_layers_0_weight_to_fp16, x = x_13_cast_fp16)[name = tensor<string, []>("x_in_25_cast_fp16")];
tensor<int32, [3]> var_615_begin_0 = const()[name = tensor<string, []>("op_615_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_615_end_0 = const()[name = tensor<string, []>("op_615_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_615_end_mask_0 = const()[name = tensor<string, []>("op_615_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_615_cast_fp16 = slice_by_index(begin = var_615_begin_0, end = var_615_end_0, end_mask = var_615_end_mask_0, x = x_in_25_cast_fp16)[name = tensor<string, []>("op_615_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_617_cast_fp16 = tanh(x = var_615_cast_fp16)[name = tensor<string, []>("op_617_cast_fp16")];
tensor<int32, [3]> var_619_begin_0 = const()[name = tensor<string, []>("op_619_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_619_end_0 = const()[name = tensor<string, []>("op_619_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_619_end_mask_0 = const()[name = tensor<string, []>("op_619_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_619_cast_fp16 = slice_by_index(begin = var_619_begin_0, end = var_619_end_0, end_mask = var_619_end_mask_0, x = x_in_25_cast_fp16)[name = tensor<string, []>("op_619_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_621_cast_fp16 = sigmoid(x = var_619_cast_fp16)[name = tensor<string, []>("op_621_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_81_cast_fp16 = mul(x = var_617_cast_fp16, y = var_621_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
tensor<string, []> res_skip_acts_25_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_25_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_25_strides_0 = const()[name = tensor<string, []>("res_skip_acts_25_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_25_pad_0 = const()[name = tensor<string, []>("res_skip_acts_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_25_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_25_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_25_groups_0 = const()[name = tensor<string, []>("res_skip_acts_25_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_0_enc_res_skip_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_0_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2926784)))];
tensor<fp16, [192]> flow_flows_0_enc_res_skip_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2963712)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_25_cast_fp16 = conv(bias = flow_flows_0_enc_res_skip_layers_0_bias_to_fp16, dilations = res_skip_acts_25_dilations_0, groups = res_skip_acts_25_groups_0, pad = res_skip_acts_25_pad_0, pad_type = res_skip_acts_25_pad_type_0, strides = res_skip_acts_25_strides_0, weight = flow_flows_0_enc_res_skip_layers_0_weight_to_fp16, x = input_81_cast_fp16)[name = tensor<string, []>("res_skip_acts_25_cast_fp16")];
tensor<int32, [3]> var_632_begin_0 = const()[name = tensor<string, []>("op_632_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_632_end_0 = const()[name = tensor<string, []>("op_632_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_632_end_mask_0 = const()[name = tensor<string, []>("op_632_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_632_cast_fp16 = slice_by_index(begin = var_632_begin_0, end = var_632_end_0, end_mask = var_632_end_mask_0, x = res_skip_acts_25_cast_fp16)[name = tensor<string, []>("op_632_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_634_cast_fp16 = add(x = x_13_cast_fp16, y = var_632_cast_fp16)[name = tensor<string, []>("op_634_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_85_cast_fp16 = mul(x = var_634_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
tensor<int32, [3]> var_637_begin_0 = const()[name = tensor<string, []>("op_637_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_637_end_0 = const()[name = tensor<string, []>("op_637_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_637_end_mask_0 = const()[name = tensor<string, []>("op_637_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_637_cast_fp16 = slice_by_index(begin = var_637_begin_0, end = var_637_end_0, end_mask = var_637_end_mask_0, x = res_skip_acts_25_cast_fp16)[name = tensor<string, []>("op_637_cast_fp16")];
tensor<string, []> x_in_27_pad_type_0 = const()[name = tensor<string, []>("x_in_27_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_27_pad_0 = const()[name = tensor<string, []>("x_in_27_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_27_strides_0 = const()[name = tensor<string, []>("x_in_27_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_27_dilations_0 = const()[name = tensor<string, []>("x_in_27_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_27_groups_0 = const()[name = tensor<string, []>("x_in_27_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_0_enc_in_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2964160)))];
tensor<fp16, [192]> flow_flows_0_enc_in_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3148544)))];
tensor<fp16, [1, 192, 384]> x_in_27_cast_fp16 = conv(bias = flow_flows_0_enc_in_layers_1_bias_to_fp16, dilations = x_in_27_dilations_0, groups = x_in_27_groups_0, pad = x_in_27_pad_0, pad_type = x_in_27_pad_type_0, strides = x_in_27_strides_0, weight = flow_flows_0_enc_in_layers_1_weight_to_fp16, x = input_85_cast_fp16)[name = tensor<string, []>("x_in_27_cast_fp16")];
tensor<int32, [3]> var_650_begin_0 = const()[name = tensor<string, []>("op_650_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_650_end_0 = const()[name = tensor<string, []>("op_650_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_650_end_mask_0 = const()[name = tensor<string, []>("op_650_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_650_cast_fp16 = slice_by_index(begin = var_650_begin_0, end = var_650_end_0, end_mask = var_650_end_mask_0, x = x_in_27_cast_fp16)[name = tensor<string, []>("op_650_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_652_cast_fp16 = tanh(x = var_650_cast_fp16)[name = tensor<string, []>("op_652_cast_fp16")];
tensor<int32, [3]> var_654_begin_0 = const()[name = tensor<string, []>("op_654_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_654_end_0 = const()[name = tensor<string, []>("op_654_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_654_end_mask_0 = const()[name = tensor<string, []>("op_654_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_654_cast_fp16 = slice_by_index(begin = var_654_begin_0, end = var_654_end_0, end_mask = var_654_end_mask_0, x = x_in_27_cast_fp16)[name = tensor<string, []>("op_654_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_656_cast_fp16 = sigmoid(x = var_654_cast_fp16)[name = tensor<string, []>("op_656_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_87_cast_fp16 = mul(x = var_652_cast_fp16, y = var_656_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
tensor<string, []> res_skip_acts_27_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_27_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_27_strides_0 = const()[name = tensor<string, []>("res_skip_acts_27_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_27_pad_0 = const()[name = tensor<string, []>("res_skip_acts_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_27_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_27_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_27_groups_0 = const()[name = tensor<string, []>("res_skip_acts_27_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_0_enc_res_skip_layers_1_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_1_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3148992)))];
tensor<fp16, [192]> flow_flows_0_enc_res_skip_layers_1_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3185920)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_27_cast_fp16 = conv(bias = flow_flows_0_enc_res_skip_layers_1_bias_to_fp16, dilations = res_skip_acts_27_dilations_0, groups = res_skip_acts_27_groups_0, pad = res_skip_acts_27_pad_0, pad_type = res_skip_acts_27_pad_type_0, strides = res_skip_acts_27_strides_0, weight = flow_flows_0_enc_res_skip_layers_1_weight_to_fp16, x = input_87_cast_fp16)[name = tensor<string, []>("res_skip_acts_27_cast_fp16")];
tensor<int32, [3]> var_667_begin_0 = const()[name = tensor<string, []>("op_667_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_667_end_0 = const()[name = tensor<string, []>("op_667_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_667_end_mask_0 = const()[name = tensor<string, []>("op_667_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_667_cast_fp16 = slice_by_index(begin = var_667_begin_0, end = var_667_end_0, end_mask = var_667_end_mask_0, x = res_skip_acts_27_cast_fp16)[name = tensor<string, []>("op_667_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_669_cast_fp16 = add(x = input_85_cast_fp16, y = var_667_cast_fp16)[name = tensor<string, []>("op_669_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_91_cast_fp16 = mul(x = var_669_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
tensor<int32, [3]> var_672_begin_0 = const()[name = tensor<string, []>("op_672_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_672_end_0 = const()[name = tensor<string, []>("op_672_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_672_end_mask_0 = const()[name = tensor<string, []>("op_672_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_672_cast_fp16 = slice_by_index(begin = var_672_begin_0, end = var_672_end_0, end_mask = var_672_end_mask_0, x = res_skip_acts_27_cast_fp16)[name = tensor<string, []>("op_672_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_35_cast_fp16 = add(x = var_637_cast_fp16, y = var_672_cast_fp16)[name = tensor<string, []>("output_35_cast_fp16")];
tensor<string, []> x_in_29_pad_type_0 = const()[name = tensor<string, []>("x_in_29_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_29_pad_0 = const()[name = tensor<string, []>("x_in_29_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_29_strides_0 = const()[name = tensor<string, []>("x_in_29_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_29_dilations_0 = const()[name = tensor<string, []>("x_in_29_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_29_groups_0 = const()[name = tensor<string, []>("x_in_29_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_0_enc_in_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3186368)))];
tensor<fp16, [192]> flow_flows_0_enc_in_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3370752)))];
tensor<fp16, [1, 192, 384]> x_in_29_cast_fp16 = conv(bias = flow_flows_0_enc_in_layers_2_bias_to_fp16, dilations = x_in_29_dilations_0, groups = x_in_29_groups_0, pad = x_in_29_pad_0, pad_type = x_in_29_pad_type_0, strides = x_in_29_strides_0, weight = flow_flows_0_enc_in_layers_2_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("x_in_29_cast_fp16")];
tensor<int32, [3]> var_685_begin_0 = const()[name = tensor<string, []>("op_685_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_685_end_0 = const()[name = tensor<string, []>("op_685_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_685_end_mask_0 = const()[name = tensor<string, []>("op_685_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_685_cast_fp16 = slice_by_index(begin = var_685_begin_0, end = var_685_end_0, end_mask = var_685_end_mask_0, x = x_in_29_cast_fp16)[name = tensor<string, []>("op_685_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_687_cast_fp16 = tanh(x = var_685_cast_fp16)[name = tensor<string, []>("op_687_cast_fp16")];
tensor<int32, [3]> var_689_begin_0 = const()[name = tensor<string, []>("op_689_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_689_end_0 = const()[name = tensor<string, []>("op_689_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_689_end_mask_0 = const()[name = tensor<string, []>("op_689_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_689_cast_fp16 = slice_by_index(begin = var_689_begin_0, end = var_689_end_0, end_mask = var_689_end_mask_0, x = x_in_29_cast_fp16)[name = tensor<string, []>("op_689_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_691_cast_fp16 = sigmoid(x = var_689_cast_fp16)[name = tensor<string, []>("op_691_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_93_cast_fp16 = mul(x = var_687_cast_fp16, y = var_691_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
tensor<string, []> res_skip_acts_29_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_29_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_29_strides_0 = const()[name = tensor<string, []>("res_skip_acts_29_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_29_pad_0 = const()[name = tensor<string, []>("res_skip_acts_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_29_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_29_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_29_groups_0 = const()[name = tensor<string, []>("res_skip_acts_29_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 1]> flow_flows_0_enc_res_skip_layers_2_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_2_weight_to_fp16"), val = tensor<fp16, [192, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3371200)))];
tensor<fp16, [192]> flow_flows_0_enc_res_skip_layers_2_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3408128)))];
tensor<fp16, [1, 192, 384]> res_skip_acts_29_cast_fp16 = conv(bias = flow_flows_0_enc_res_skip_layers_2_bias_to_fp16, dilations = res_skip_acts_29_dilations_0, groups = res_skip_acts_29_groups_0, pad = res_skip_acts_29_pad_0, pad_type = res_skip_acts_29_pad_type_0, strides = res_skip_acts_29_strides_0, weight = flow_flows_0_enc_res_skip_layers_2_weight_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("res_skip_acts_29_cast_fp16")];
tensor<int32, [3]> var_702_begin_0 = const()[name = tensor<string, []>("op_702_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_702_end_0 = const()[name = tensor<string, []>("op_702_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_702_end_mask_0 = const()[name = tensor<string, []>("op_702_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_702_cast_fp16 = slice_by_index(begin = var_702_begin_0, end = var_702_end_0, end_mask = var_702_end_mask_0, x = res_skip_acts_29_cast_fp16)[name = tensor<string, []>("op_702_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_704_cast_fp16 = add(x = input_91_cast_fp16, y = var_702_cast_fp16)[name = tensor<string, []>("op_704_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_97_cast_fp16 = mul(x = var_704_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_97_cast_fp16")];
tensor<int32, [3]> var_707_begin_0 = const()[name = tensor<string, []>("op_707_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_707_end_0 = const()[name = tensor<string, []>("op_707_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_707_end_mask_0 = const()[name = tensor<string, []>("op_707_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_707_cast_fp16 = slice_by_index(begin = var_707_begin_0, end = var_707_end_0, end_mask = var_707_end_mask_0, x = res_skip_acts_29_cast_fp16)[name = tensor<string, []>("op_707_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_37_cast_fp16 = add(x = output_35_cast_fp16, y = var_707_cast_fp16)[name = tensor<string, []>("output_37_cast_fp16")];
tensor<string, []> x_in_pad_type_0 = const()[name = tensor<string, []>("x_in_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_in_pad_0 = const()[name = tensor<string, []>("x_in_pad_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [1]> x_in_strides_0 = const()[name = tensor<string, []>("x_in_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_in_dilations_0 = const()[name = tensor<string, []>("x_in_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_in_groups_0 = const()[name = tensor<string, []>("x_in_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [192, 96, 5]> flow_flows_0_enc_in_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_3_weight_to_fp16"), val = tensor<fp16, [192, 96, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3408576)))];
tensor<fp16, [192]> flow_flows_0_enc_in_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_in_layers_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3592960)))];
tensor<fp16, [1, 192, 384]> x_in_cast_fp16 = conv(bias = flow_flows_0_enc_in_layers_3_bias_to_fp16, dilations = x_in_dilations_0, groups = x_in_groups_0, pad = x_in_pad_0, pad_type = x_in_pad_type_0, strides = x_in_strides_0, weight = flow_flows_0_enc_in_layers_3_weight_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("x_in_cast_fp16")];
tensor<int32, [3]> var_720_begin_0 = const()[name = tensor<string, []>("op_720_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
tensor<int32, [3]> var_720_end_0 = const()[name = tensor<string, []>("op_720_end_0"), val = tensor<int32, [3]>([1, 96, 384])];
tensor<bool, [3]> var_720_end_mask_0 = const()[name = tensor<string, []>("op_720_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
tensor<fp16, [1, 96, 384]> var_720_cast_fp16 = slice_by_index(begin = var_720_begin_0, end = var_720_end_0, end_mask = var_720_end_mask_0, x = x_in_cast_fp16)[name = tensor<string, []>("op_720_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_722_cast_fp16 = tanh(x = var_720_cast_fp16)[name = tensor<string, []>("op_722_cast_fp16")];
tensor<int32, [3]> var_724_begin_0 = const()[name = tensor<string, []>("op_724_begin_0"), val = tensor<int32, [3]>([0, 96, 0])];
tensor<int32, [3]> var_724_end_0 = const()[name = tensor<string, []>("op_724_end_0"), val = tensor<int32, [3]>([1, 192, 384])];
tensor<bool, [3]> var_724_end_mask_0 = const()[name = tensor<string, []>("op_724_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
tensor<fp16, [1, 96, 384]> var_724_cast_fp16 = slice_by_index(begin = var_724_begin_0, end = var_724_end_0, end_mask = var_724_end_mask_0, x = x_in_cast_fp16)[name = tensor<string, []>("op_724_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_726_cast_fp16 = sigmoid(x = var_724_cast_fp16)[name = tensor<string, []>("op_726_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_99_cast_fp16 = mul(x = var_722_cast_fp16, y = var_726_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
tensor<string, []> res_skip_acts_pad_type_0 = const()[name = tensor<string, []>("res_skip_acts_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> res_skip_acts_strides_0 = const()[name = tensor<string, []>("res_skip_acts_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> res_skip_acts_pad_0 = const()[name = tensor<string, []>("res_skip_acts_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> res_skip_acts_dilations_0 = const()[name = tensor<string, []>("res_skip_acts_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> res_skip_acts_groups_0 = const()[name = tensor<string, []>("res_skip_acts_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_0_enc_res_skip_layers_3_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_3_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3593408)))];
tensor<fp16, [96]> flow_flows_0_enc_res_skip_layers_3_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_enc_res_skip_layers_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3611904)))];
tensor<fp16, [1, 96, 384]> res_skip_acts_cast_fp16 = conv(bias = flow_flows_0_enc_res_skip_layers_3_bias_to_fp16, dilations = res_skip_acts_dilations_0, groups = res_skip_acts_groups_0, pad = res_skip_acts_pad_0, pad_type = res_skip_acts_pad_type_0, strides = res_skip_acts_strides_0, weight = flow_flows_0_enc_res_skip_layers_3_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("res_skip_acts_cast_fp16")];
tensor<fp16, [1, 96, 384]> output_cast_fp16 = add(x = output_37_cast_fp16, y = res_skip_acts_cast_fp16)[name = tensor<string, []>("output_cast_fp16")];
tensor<fp16, [1, 96, 384]> input_103_cast_fp16 = mul(x = output_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
tensor<string, []> var_744_pad_type_0 = const()[name = tensor<string, []>("op_744_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> var_744_strides_0 = const()[name = tensor<string, []>("op_744_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> var_744_pad_0 = const()[name = tensor<string, []>("op_744_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> var_744_dilations_0 = const()[name = tensor<string, []>("op_744_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> var_744_groups_0 = const()[name = tensor<string, []>("op_744_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [96, 96, 1]> flow_flows_0_post_weight_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_post_weight_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3612160)))];
tensor<fp16, [96]> flow_flows_0_post_bias_to_fp16 = const()[name = tensor<string, []>("flow_flows_0_post_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3630656)))];
tensor<fp16, [1, 96, 384]> var_744_cast_fp16 = conv(bias = flow_flows_0_post_bias_to_fp16, dilations = var_744_dilations_0, groups = var_744_groups_0, pad = var_744_pad_0, pad_type = var_744_pad_type_0, strides = var_744_strides_0, weight = flow_flows_0_post_weight_to_fp16, x = input_103_cast_fp16)[name = tensor<string, []>("op_744_cast_fp16")];
tensor<fp16, [1, 96, 384]> stats_cast_fp16 = mul(x = var_744_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("stats_cast_fp16")];
tensor<fp16, [1, 96, 384]> var_747_cast_fp16 = sub(x = var_577_cast_fp16_1, y = stats_cast_fp16)[name = tensor<string, []>("op_747_cast_fp16")];
tensor<fp16, [1, 96, 384]> x1_cast_fp16 = mul(x = var_747_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("x1_cast_fp16")];
tensor<bool, []> z_interleave_0 = const()[name = tensor<string, []>("z_interleave_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 192, 384]> z_cast_fp16 = concat(axis = var_13, interleave = z_interleave_0, values = (var_577_cast_fp16_0, x1_cast_fp16))[name = tensor<string, []>("z_cast_fp16")];
tensor<fp16, [1, 192, 384]> input_105_cast_fp16 = mul(x = z_cast_fp16, y = y_mask_to_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
tensor<fp32, []> var_756 = const()[name = tensor<string, []>("op_756"), val = tensor<fp32, []>(0x1.47ae14p-7)];
tensor<fp32, []> var_764 = const()[name = tensor<string, []>("op_764"), val = tensor<fp32, []>(0x1.99999ap-4)];
tensor<string, []> input_107_pad_type_0 = const()[name = tensor<string, []>("input_107_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_107_strides_0 = const()[name = tensor<string, []>("input_107_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_107_dilations_0 = const()[name = tensor<string, []>("input_107_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_107_groups_0 = const()[name = tensor<string, []>("input_107_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [320, 192, 7]> dec_conv_pre_weight_to_fp16 = const()[name = tensor<string, []>("dec_conv_pre_weight_to_fp16"), val = tensor<fp16, [320, 192, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3630912)))];
tensor<fp16, [320]> dec_conv_pre_bias_to_fp16 = const()[name = tensor<string, []>("dec_conv_pre_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4491136)))];
tensor<fp16, [1, 320, 384]> input_107_cast_fp16 = conv(bias = dec_conv_pre_bias_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = dec_conv_pre_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
tensor<fp16, [1, 320, 384]> input_109_cast_fp16 = leaky_relu(alpha = var_764, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
tensor<string, []> input_111_pad_type_0 = const()[name = tensor<string, []>("input_111_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_111_pad_0 = const()[name = tensor<string, []>("input_111_pad_0"), val = tensor<int32, [2]>([4, 4])];
tensor<int32, [1]> input_111_strides_0 = const()[name = tensor<string, []>("input_111_strides_0"), val = tensor<int32, [1]>([8])];
tensor<int32, [1]> input_111_dilations_0 = const()[name = tensor<string, []>("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_111_groups_0 = const()[name = tensor<string, []>("input_111_groups_0"), val = tensor<int32, []>(1)];
tensor<int32, [3]> input_111_has_output_shape_output_shape_0 = const()[name = tensor<string, []>("input_111_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 160, 3072])];
tensor<fp16, [320, 160, 16]> dec_ups_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_ups_0_weight_to_fp16"), val = tensor<fp16, [320, 160, 16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4491840)))];
tensor<fp16, [160]> dec_ups_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_ups_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6130304)))];
tensor<fp16, [1, 160, 3072]> input_111_has_output_shape_cast_fp16 = conv_transpose(bias = dec_ups_0_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, output_shape = input_111_has_output_shape_output_shape_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = dec_ups_0_weight_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("input_111_has_output_shape_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_113_cast_fp16 = leaky_relu(alpha = var_764, x = input_111_has_output_shape_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
tensor<string, []> input_115_pad_type_0 = const()[name = tensor<string, []>("input_115_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_115_pad_0 = const()[name = tensor<string, []>("input_115_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_115_strides_0 = const()[name = tensor<string, []>("input_115_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_115_dilations_0 = const()[name = tensor<string, []>("input_115_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_115_groups_0 = const()[name = tensor<string, []>("input_115_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6130688)))];
tensor<fp16, [160]> dec_resblocks_0_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6284352)))];
tensor<fp16, [1, 160, 3072]> input_115_cast_fp16 = conv(bias = dec_resblocks_0_convs1_0_bias_to_fp16, dilations = input_115_dilations_0, groups = input_115_groups_0, pad = input_115_pad_0, pad_type = input_115_pad_type_0, strides = input_115_strides_0, weight = dec_resblocks_0_convs1_0_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_117_cast_fp16 = leaky_relu(alpha = var_764, x = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
tensor<string, []> xt_1_pad_type_0 = const()[name = tensor<string, []>("xt_1_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_1_pad_0 = const()[name = tensor<string, []>("xt_1_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_1_strides_0 = const()[name = tensor<string, []>("xt_1_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_1_dilations_0 = const()[name = tensor<string, []>("xt_1_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_1_groups_0 = const()[name = tensor<string, []>("xt_1_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6284736)))];
tensor<fp16, [160]> dec_resblocks_0_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6438400)))];
tensor<fp16, [1, 160, 3072]> xt_1_cast_fp16 = conv(bias = dec_resblocks_0_convs2_0_bias_to_fp16, dilations = xt_1_dilations_0, groups = xt_1_groups_0, pad = xt_1_pad_0, pad_type = xt_1_pad_type_0, strides = xt_1_strides_0, weight = dec_resblocks_0_convs2_0_weight_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("xt_1_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_119_cast_fp16 = add(x = xt_1_cast_fp16, y = input_111_has_output_shape_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_121_cast_fp16 = leaky_relu(alpha = var_764, x = input_119_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
tensor<string, []> input_123_pad_type_0 = const()[name = tensor<string, []>("input_123_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_123_pad_0 = const()[name = tensor<string, []>("input_123_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_123_dilations_0 = const()[name = tensor<string, []>("input_123_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_123_strides_0 = const()[name = tensor<string, []>("input_123_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_123_groups_0 = const()[name = tensor<string, []>("input_123_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6438784)))];
tensor<fp16, [160]> dec_resblocks_0_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6592448)))];
tensor<fp16, [1, 160, 3072]> input_123_cast_fp16 = conv(bias = dec_resblocks_0_convs1_1_bias_to_fp16, dilations = input_123_dilations_0, groups = input_123_groups_0, pad = input_123_pad_0, pad_type = input_123_pad_type_0, strides = input_123_strides_0, weight = dec_resblocks_0_convs1_1_weight_to_fp16, x = input_121_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_125_cast_fp16 = leaky_relu(alpha = var_764, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
tensor<string, []> xt_3_pad_type_0 = const()[name = tensor<string, []>("xt_3_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_3_pad_0 = const()[name = tensor<string, []>("xt_3_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_3_strides_0 = const()[name = tensor<string, []>("xt_3_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_3_dilations_0 = const()[name = tensor<string, []>("xt_3_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_3_groups_0 = const()[name = tensor<string, []>("xt_3_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6592832)))];
tensor<fp16, [160]> dec_resblocks_0_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6746496)))];
tensor<fp16, [1, 160, 3072]> xt_3_cast_fp16 = conv(bias = dec_resblocks_0_convs2_1_bias_to_fp16, dilations = xt_3_dilations_0, groups = xt_3_groups_0, pad = xt_3_pad_0, pad_type = xt_3_pad_type_0, strides = xt_3_strides_0, weight = dec_resblocks_0_convs2_1_weight_to_fp16, x = input_125_cast_fp16)[name = tensor<string, []>("xt_3_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_127_cast_fp16 = add(x = xt_3_cast_fp16, y = input_119_cast_fp16)[name = tensor<string, []>("input_127_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_129_cast_fp16 = leaky_relu(alpha = var_764, x = input_127_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
tensor<string, []> input_131_pad_type_0 = const()[name = tensor<string, []>("input_131_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_131_pad_0 = const()[name = tensor<string, []>("input_131_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_131_dilations_0 = const()[name = tensor<string, []>("input_131_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_131_strides_0 = const()[name = tensor<string, []>("input_131_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_131_groups_0 = const()[name = tensor<string, []>("input_131_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6746880)))];
tensor<fp16, [160]> dec_resblocks_0_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs1_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6900544)))];
tensor<fp16, [1, 160, 3072]> input_131_cast_fp16 = conv(bias = dec_resblocks_0_convs1_2_bias_to_fp16, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = dec_resblocks_0_convs1_2_weight_to_fp16, x = input_129_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_133_cast_fp16 = leaky_relu(alpha = var_764, x = input_131_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
tensor<string, []> xt_5_pad_type_0 = const()[name = tensor<string, []>("xt_5_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_5_pad_0 = const()[name = tensor<string, []>("xt_5_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_5_strides_0 = const()[name = tensor<string, []>("xt_5_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_5_dilations_0 = const()[name = tensor<string, []>("xt_5_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_5_groups_0 = const()[name = tensor<string, []>("xt_5_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 3]> dec_resblocks_0_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6900928)))];
tensor<fp16, [160]> dec_resblocks_0_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_0_convs2_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7054592)))];
tensor<fp16, [1, 160, 3072]> xt_5_cast_fp16 = conv(bias = dec_resblocks_0_convs2_2_bias_to_fp16, dilations = xt_5_dilations_0, groups = xt_5_groups_0, pad = xt_5_pad_0, pad_type = xt_5_pad_type_0, strides = xt_5_strides_0, weight = dec_resblocks_0_convs2_2_weight_to_fp16, x = input_133_cast_fp16)[name = tensor<string, []>("xt_5_cast_fp16")];
tensor<fp16, [1, 160, 3072]> xs_1_cast_fp16 = add(x = xt_5_cast_fp16, y = input_127_cast_fp16)[name = tensor<string, []>("xs_1_cast_fp16")];
tensor<string, []> input_137_pad_type_0 = const()[name = tensor<string, []>("input_137_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_137_pad_0 = const()[name = tensor<string, []>("input_137_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_137_strides_0 = const()[name = tensor<string, []>("input_137_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_137_dilations_0 = const()[name = tensor<string, []>("input_137_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_137_groups_0 = const()[name = tensor<string, []>("input_137_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7054976)))];
tensor<fp16, [160]> dec_resblocks_1_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7413440)))];
tensor<fp16, [1, 160, 3072]> input_137_cast_fp16 = conv(bias = dec_resblocks_1_convs1_0_bias_to_fp16, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = dec_resblocks_1_convs1_0_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_139_cast_fp16 = leaky_relu(alpha = var_764, x = input_137_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
tensor<string, []> xt_7_pad_type_0 = const()[name = tensor<string, []>("xt_7_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_7_pad_0 = const()[name = tensor<string, []>("xt_7_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_7_strides_0 = const()[name = tensor<string, []>("xt_7_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_7_dilations_0 = const()[name = tensor<string, []>("xt_7_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_7_groups_0 = const()[name = tensor<string, []>("xt_7_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7413824)))];
tensor<fp16, [160]> dec_resblocks_1_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7772288)))];
tensor<fp16, [1, 160, 3072]> xt_7_cast_fp16 = conv(bias = dec_resblocks_1_convs2_0_bias_to_fp16, dilations = xt_7_dilations_0, groups = xt_7_groups_0, pad = xt_7_pad_0, pad_type = xt_7_pad_type_0, strides = xt_7_strides_0, weight = dec_resblocks_1_convs2_0_weight_to_fp16, x = input_139_cast_fp16)[name = tensor<string, []>("xt_7_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_141_cast_fp16 = add(x = xt_7_cast_fp16, y = input_111_has_output_shape_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_143_cast_fp16 = leaky_relu(alpha = var_764, x = input_141_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")];
tensor<string, []> input_145_pad_type_0 = const()[name = tensor<string, []>("input_145_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_145_pad_0 = const()[name = tensor<string, []>("input_145_pad_0"), val = tensor<int32, [2]>([9, 9])];
tensor<int32, [1]> input_145_dilations_0 = const()[name = tensor<string, []>("input_145_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_145_strides_0 = const()[name = tensor<string, []>("input_145_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_145_groups_0 = const()[name = tensor<string, []>("input_145_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7772672)))];
tensor<fp16, [160]> dec_resblocks_1_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8131136)))];
tensor<fp16, [1, 160, 3072]> input_145_cast_fp16 = conv(bias = dec_resblocks_1_convs1_1_bias_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = dec_resblocks_1_convs1_1_weight_to_fp16, x = input_143_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_147_cast_fp16 = leaky_relu(alpha = var_764, x = input_145_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
tensor<string, []> xt_9_pad_type_0 = const()[name = tensor<string, []>("xt_9_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_9_pad_0 = const()[name = tensor<string, []>("xt_9_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_9_strides_0 = const()[name = tensor<string, []>("xt_9_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_9_dilations_0 = const()[name = tensor<string, []>("xt_9_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_9_groups_0 = const()[name = tensor<string, []>("xt_9_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8131520)))];
tensor<fp16, [160]> dec_resblocks_1_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8489984)))];
tensor<fp16, [1, 160, 3072]> xt_9_cast_fp16 = conv(bias = dec_resblocks_1_convs2_1_bias_to_fp16, dilations = xt_9_dilations_0, groups = xt_9_groups_0, pad = xt_9_pad_0, pad_type = xt_9_pad_type_0, strides = xt_9_strides_0, weight = dec_resblocks_1_convs2_1_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("xt_9_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_149_cast_fp16 = add(x = xt_9_cast_fp16, y = input_141_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_151_cast_fp16 = leaky_relu(alpha = var_764, x = input_149_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
tensor<string, []> input_153_pad_type_0 = const()[name = tensor<string, []>("input_153_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_153_pad_0 = const()[name = tensor<string, []>("input_153_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_153_dilations_0 = const()[name = tensor<string, []>("input_153_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_153_strides_0 = const()[name = tensor<string, []>("input_153_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_153_groups_0 = const()[name = tensor<string, []>("input_153_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8490368)))];
tensor<fp16, [160]> dec_resblocks_1_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs1_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8848832)))];
tensor<fp16, [1, 160, 3072]> input_153_cast_fp16 = conv(bias = dec_resblocks_1_convs1_2_bias_to_fp16, dilations = input_153_dilations_0, groups = input_153_groups_0, pad = input_153_pad_0, pad_type = input_153_pad_type_0, strides = input_153_strides_0, weight = dec_resblocks_1_convs1_2_weight_to_fp16, x = input_151_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_155_cast_fp16 = leaky_relu(alpha = var_764, x = input_153_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
tensor<string, []> xt_11_pad_type_0 = const()[name = tensor<string, []>("xt_11_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_11_pad_0 = const()[name = tensor<string, []>("xt_11_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_11_strides_0 = const()[name = tensor<string, []>("xt_11_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_11_dilations_0 = const()[name = tensor<string, []>("xt_11_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_11_groups_0 = const()[name = tensor<string, []>("xt_11_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 7]> dec_resblocks_1_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8849216)))];
tensor<fp16, [160]> dec_resblocks_1_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_1_convs2_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9207680)))];
tensor<fp16, [1, 160, 3072]> xt_11_cast_fp16 = conv(bias = dec_resblocks_1_convs2_2_bias_to_fp16, dilations = xt_11_dilations_0, groups = xt_11_groups_0, pad = xt_11_pad_0, pad_type = xt_11_pad_type_0, strides = xt_11_strides_0, weight = dec_resblocks_1_convs2_2_weight_to_fp16, x = input_155_cast_fp16)[name = tensor<string, []>("xt_11_cast_fp16")];
tensor<fp16, [1, 160, 3072]> var_944_cast_fp16 = add(x = xt_11_cast_fp16, y = input_149_cast_fp16)[name = tensor<string, []>("op_944_cast_fp16")];
tensor<fp16, [1, 160, 3072]> xs_3_cast_fp16 = add(x = xs_1_cast_fp16, y = var_944_cast_fp16)[name = tensor<string, []>("xs_3_cast_fp16")];
tensor<string, []> input_159_pad_type_0 = const()[name = tensor<string, []>("input_159_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_159_pad_0 = const()[name = tensor<string, []>("input_159_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_159_strides_0 = const()[name = tensor<string, []>("input_159_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_159_dilations_0 = const()[name = tensor<string, []>("input_159_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_159_groups_0 = const()[name = tensor<string, []>("input_159_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9208064)))];
tensor<fp16, [160]> dec_resblocks_2_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9771328)))];
tensor<fp16, [1, 160, 3072]> input_159_cast_fp16 = conv(bias = dec_resblocks_2_convs1_0_bias_to_fp16, dilations = input_159_dilations_0, groups = input_159_groups_0, pad = input_159_pad_0, pad_type = input_159_pad_type_0, strides = input_159_strides_0, weight = dec_resblocks_2_convs1_0_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_161_cast_fp16 = leaky_relu(alpha = var_764, x = input_159_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
tensor<string, []> xt_13_pad_type_0 = const()[name = tensor<string, []>("xt_13_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_13_pad_0 = const()[name = tensor<string, []>("xt_13_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_13_strides_0 = const()[name = tensor<string, []>("xt_13_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_13_dilations_0 = const()[name = tensor<string, []>("xt_13_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_13_groups_0 = const()[name = tensor<string, []>("xt_13_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_0_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9771712)))];
tensor<fp16, [160]> dec_resblocks_2_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_0_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10334976)))];
tensor<fp16, [1, 160, 3072]> xt_13_cast_fp16 = conv(bias = dec_resblocks_2_convs2_0_bias_to_fp16, dilations = xt_13_dilations_0, groups = xt_13_groups_0, pad = xt_13_pad_0, pad_type = xt_13_pad_type_0, strides = xt_13_strides_0, weight = dec_resblocks_2_convs2_0_weight_to_fp16, x = input_161_cast_fp16)[name = tensor<string, []>("xt_13_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_163_cast_fp16 = add(x = xt_13_cast_fp16, y = input_111_has_output_shape_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_165_cast_fp16 = leaky_relu(alpha = var_764, x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
tensor<string, []> input_167_pad_type_0 = const()[name = tensor<string, []>("input_167_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_167_pad_0 = const()[name = tensor<string, []>("input_167_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_167_dilations_0 = const()[name = tensor<string, []>("input_167_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_167_strides_0 = const()[name = tensor<string, []>("input_167_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_167_groups_0 = const()[name = tensor<string, []>("input_167_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10335360)))];
tensor<fp16, [160]> dec_resblocks_2_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10898624)))];
tensor<fp16, [1, 160, 3072]> input_167_cast_fp16 = conv(bias = dec_resblocks_2_convs1_1_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = dec_resblocks_2_convs1_1_weight_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_169_cast_fp16 = leaky_relu(alpha = var_764, x = input_167_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
tensor<string, []> xt_15_pad_type_0 = const()[name = tensor<string, []>("xt_15_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_15_pad_0 = const()[name = tensor<string, []>("xt_15_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_15_strides_0 = const()[name = tensor<string, []>("xt_15_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_15_dilations_0 = const()[name = tensor<string, []>("xt_15_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_15_groups_0 = const()[name = tensor<string, []>("xt_15_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_1_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10899008)))];
tensor<fp16, [160]> dec_resblocks_2_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11462272)))];
tensor<fp16, [1, 160, 3072]> xt_15_cast_fp16 = conv(bias = dec_resblocks_2_convs2_1_bias_to_fp16, dilations = xt_15_dilations_0, groups = xt_15_groups_0, pad = xt_15_pad_0, pad_type = xt_15_pad_type_0, strides = xt_15_strides_0, weight = dec_resblocks_2_convs2_1_weight_to_fp16, x = input_169_cast_fp16)[name = tensor<string, []>("xt_15_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_171_cast_fp16 = add(x = xt_15_cast_fp16, y = input_163_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_173_cast_fp16 = leaky_relu(alpha = var_764, x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
tensor<string, []> input_175_pad_type_0 = const()[name = tensor<string, []>("input_175_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_175_pad_0 = const()[name = tensor<string, []>("input_175_pad_0"), val = tensor<int32, [2]>([25, 25])];
tensor<int32, [1]> input_175_dilations_0 = const()[name = tensor<string, []>("input_175_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_175_strides_0 = const()[name = tensor<string, []>("input_175_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_175_groups_0 = const()[name = tensor<string, []>("input_175_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11462656)))];
tensor<fp16, [160]> dec_resblocks_2_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs1_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12025920)))];
tensor<fp16, [1, 160, 3072]> input_175_cast_fp16 = conv(bias = dec_resblocks_2_convs1_2_bias_to_fp16, dilations = input_175_dilations_0, groups = input_175_groups_0, pad = input_175_pad_0, pad_type = input_175_pad_type_0, strides = input_175_strides_0, weight = dec_resblocks_2_convs1_2_weight_to_fp16, x = input_173_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_177_cast_fp16 = leaky_relu(alpha = var_764, x = input_175_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
tensor<string, []> xt_17_pad_type_0 = const()[name = tensor<string, []>("xt_17_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_17_pad_0 = const()[name = tensor<string, []>("xt_17_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_17_strides_0 = const()[name = tensor<string, []>("xt_17_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_17_dilations_0 = const()[name = tensor<string, []>("xt_17_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_17_groups_0 = const()[name = tensor<string, []>("xt_17_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [160, 160, 11]> dec_resblocks_2_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_2_weight_to_fp16"), val = tensor<fp16, [160, 160, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12026304)))];
tensor<fp16, [160]> dec_resblocks_2_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_2_convs2_2_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12589568)))];
tensor<fp16, [1, 160, 3072]> xt_17_cast_fp16 = conv(bias = dec_resblocks_2_convs2_2_bias_to_fp16, dilations = xt_17_dilations_0, groups = xt_17_groups_0, pad = xt_17_pad_0, pad_type = xt_17_pad_type_0, strides = xt_17_strides_0, weight = dec_resblocks_2_convs2_2_weight_to_fp16, x = input_177_cast_fp16)[name = tensor<string, []>("xt_17_cast_fp16")];
tensor<fp16, [1, 160, 3072]> var_1008_cast_fp16 = add(x = xt_17_cast_fp16, y = input_171_cast_fp16)[name = tensor<string, []>("op_1008_cast_fp16")];
tensor<fp16, [1, 160, 3072]> xs_5_cast_fp16 = add(x = xs_3_cast_fp16, y = var_1008_cast_fp16)[name = tensor<string, []>("xs_5_cast_fp16")];
tensor<fp16, []> _inversed_input_179_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_179_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)];
tensor<fp16, [1, 160, 3072]> _inversed_input_179_cast_fp16 = mul(x = xs_5_cast_fp16, y = _inversed_input_179_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_179_cast_fp16")];
tensor<fp16, [1, 160, 3072]> input_181_cast_fp16 = leaky_relu(alpha = var_764, x = _inversed_input_179_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
tensor<string, []> input_183_pad_type_0 = const()[name = tensor<string, []>("input_183_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_183_pad_0 = const()[name = tensor<string, []>("input_183_pad_0"), val = tensor<int32, [2]>([4, 4])];
tensor<int32, [1]> input_183_strides_0 = const()[name = tensor<string, []>("input_183_strides_0"), val = tensor<int32, [1]>([8])];
tensor<int32, [1]> input_183_dilations_0 = const()[name = tensor<string, []>("input_183_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_183_groups_0 = const()[name = tensor<string, []>("input_183_groups_0"), val = tensor<int32, []>(1)];
tensor<int32, [3]> input_183_has_output_shape_output_shape_0 = const()[name = tensor<string, []>("input_183_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 80, 24576])];
tensor<fp16, [160, 80, 16]> dec_ups_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_ups_1_weight_to_fp16"), val = tensor<fp16, [160, 80, 16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12589952)))];
tensor<fp16, [80]> dec_ups_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_ups_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12999616)))];
tensor<fp16, [1, 80, 24576]> input_183_has_output_shape_cast_fp16 = conv_transpose(bias = dec_ups_1_bias_to_fp16, dilations = input_183_dilations_0, groups = input_183_groups_0, output_shape = input_183_has_output_shape_output_shape_0, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = input_183_strides_0, weight = dec_ups_1_weight_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("input_183_has_output_shape_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_185_cast_fp16 = leaky_relu(alpha = var_764, x = input_183_has_output_shape_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
tensor<string, []> input_187_pad_type_0 = const()[name = tensor<string, []>("input_187_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_187_pad_0 = const()[name = tensor<string, []>("input_187_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_187_strides_0 = const()[name = tensor<string, []>("input_187_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_187_dilations_0 = const()[name = tensor<string, []>("input_187_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_187_groups_0 = const()[name = tensor<string, []>("input_187_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12999872)))];
tensor<fp16, [80]> dec_resblocks_3_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13038336)))];
tensor<fp16, [1, 80, 24576]> input_187_cast_fp16 = conv(bias = dec_resblocks_3_convs1_0_bias_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = dec_resblocks_3_convs1_0_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_189_cast_fp16 = leaky_relu(alpha = var_764, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
tensor<string, []> xt_19_pad_type_0 = const()[name = tensor<string, []>("xt_19_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_19_pad_0 = const()[name = tensor<string, []>("xt_19_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_19_strides_0 = const()[name = tensor<string, []>("xt_19_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_19_dilations_0 = const()[name = tensor<string, []>("xt_19_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_19_groups_0 = const()[name = tensor<string, []>("xt_19_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13038592)))];
tensor<fp16, [80]> dec_resblocks_3_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13077056)))];
tensor<fp16, [1, 80, 24576]> xt_19_cast_fp16 = conv(bias = dec_resblocks_3_convs2_0_bias_to_fp16, dilations = xt_19_dilations_0, groups = xt_19_groups_0, pad = xt_19_pad_0, pad_type = xt_19_pad_type_0, strides = xt_19_strides_0, weight = dec_resblocks_3_convs2_0_weight_to_fp16, x = input_189_cast_fp16)[name = tensor<string, []>("xt_19_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_191_cast_fp16 = add(x = xt_19_cast_fp16, y = input_183_has_output_shape_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_193_cast_fp16 = leaky_relu(alpha = var_764, x = input_191_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")];
tensor<string, []> input_195_pad_type_0 = const()[name = tensor<string, []>("input_195_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_195_pad_0 = const()[name = tensor<string, []>("input_195_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_195_dilations_0 = const()[name = tensor<string, []>("input_195_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_195_strides_0 = const()[name = tensor<string, []>("input_195_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_195_groups_0 = const()[name = tensor<string, []>("input_195_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13077312)))];
tensor<fp16, [80]> dec_resblocks_3_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13115776)))];
tensor<fp16, [1, 80, 24576]> input_195_cast_fp16 = conv(bias = dec_resblocks_3_convs1_1_bias_to_fp16, dilations = input_195_dilations_0, groups = input_195_groups_0, pad = input_195_pad_0, pad_type = input_195_pad_type_0, strides = input_195_strides_0, weight = dec_resblocks_3_convs1_1_weight_to_fp16, x = input_193_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_197_cast_fp16 = leaky_relu(alpha = var_764, x = input_195_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
tensor<string, []> xt_21_pad_type_0 = const()[name = tensor<string, []>("xt_21_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_21_pad_0 = const()[name = tensor<string, []>("xt_21_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_21_strides_0 = const()[name = tensor<string, []>("xt_21_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_21_dilations_0 = const()[name = tensor<string, []>("xt_21_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_21_groups_0 = const()[name = tensor<string, []>("xt_21_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13116032)))];
tensor<fp16, [80]> dec_resblocks_3_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13154496)))];
tensor<fp16, [1, 80, 24576]> xt_21_cast_fp16 = conv(bias = dec_resblocks_3_convs2_1_bias_to_fp16, dilations = xt_21_dilations_0, groups = xt_21_groups_0, pad = xt_21_pad_0, pad_type = xt_21_pad_type_0, strides = xt_21_strides_0, weight = dec_resblocks_3_convs2_1_weight_to_fp16, x = input_197_cast_fp16)[name = tensor<string, []>("xt_21_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_199_cast_fp16 = add(x = xt_21_cast_fp16, y = input_191_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_201_cast_fp16 = leaky_relu(alpha = var_764, x = input_199_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
tensor<string, []> input_203_pad_type_0 = const()[name = tensor<string, []>("input_203_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_203_pad_0 = const()[name = tensor<string, []>("input_203_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_203_dilations_0 = const()[name = tensor<string, []>("input_203_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_203_strides_0 = const()[name = tensor<string, []>("input_203_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_203_groups_0 = const()[name = tensor<string, []>("input_203_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13154752)))];
tensor<fp16, [80]> dec_resblocks_3_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs1_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13193216)))];
tensor<fp16, [1, 80, 24576]> input_203_cast_fp16 = conv(bias = dec_resblocks_3_convs1_2_bias_to_fp16, dilations = input_203_dilations_0, groups = input_203_groups_0, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = input_203_strides_0, weight = dec_resblocks_3_convs1_2_weight_to_fp16, x = input_201_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_205_cast_fp16 = leaky_relu(alpha = var_764, x = input_203_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
tensor<string, []> xt_23_pad_type_0 = const()[name = tensor<string, []>("xt_23_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_23_pad_0 = const()[name = tensor<string, []>("xt_23_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_23_strides_0 = const()[name = tensor<string, []>("xt_23_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_23_dilations_0 = const()[name = tensor<string, []>("xt_23_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_23_groups_0 = const()[name = tensor<string, []>("xt_23_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 3]> dec_resblocks_3_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13193472)))];
tensor<fp16, [80]> dec_resblocks_3_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_3_convs2_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13231936)))];
tensor<fp16, [1, 80, 24576]> xt_23_cast_fp16 = conv(bias = dec_resblocks_3_convs2_2_bias_to_fp16, dilations = xt_23_dilations_0, groups = xt_23_groups_0, pad = xt_23_pad_0, pad_type = xt_23_pad_type_0, strides = xt_23_strides_0, weight = dec_resblocks_3_convs2_2_weight_to_fp16, x = input_205_cast_fp16)[name = tensor<string, []>("xt_23_cast_fp16")];
tensor<fp16, [1, 80, 24576]> xs_7_cast_fp16 = add(x = xt_23_cast_fp16, y = input_199_cast_fp16)[name = tensor<string, []>("xs_7_cast_fp16")];
tensor<string, []> input_209_pad_type_0 = const()[name = tensor<string, []>("input_209_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_209_pad_0 = const()[name = tensor<string, []>("input_209_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_209_strides_0 = const()[name = tensor<string, []>("input_209_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_209_dilations_0 = const()[name = tensor<string, []>("input_209_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_209_groups_0 = const()[name = tensor<string, []>("input_209_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13232192)))];
tensor<fp16, [80]> dec_resblocks_4_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13321856)))];
tensor<fp16, [1, 80, 24576]> input_209_cast_fp16 = conv(bias = dec_resblocks_4_convs1_0_bias_to_fp16, dilations = input_209_dilations_0, groups = input_209_groups_0, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = input_209_strides_0, weight = dec_resblocks_4_convs1_0_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_211_cast_fp16 = leaky_relu(alpha = var_764, x = input_209_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
tensor<string, []> xt_25_pad_type_0 = const()[name = tensor<string, []>("xt_25_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_25_pad_0 = const()[name = tensor<string, []>("xt_25_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_25_strides_0 = const()[name = tensor<string, []>("xt_25_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_25_dilations_0 = const()[name = tensor<string, []>("xt_25_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_25_groups_0 = const()[name = tensor<string, []>("xt_25_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13322112)))];
tensor<fp16, [80]> dec_resblocks_4_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13411776)))];
tensor<fp16, [1, 80, 24576]> xt_25_cast_fp16 = conv(bias = dec_resblocks_4_convs2_0_bias_to_fp16, dilations = xt_25_dilations_0, groups = xt_25_groups_0, pad = xt_25_pad_0, pad_type = xt_25_pad_type_0, strides = xt_25_strides_0, weight = dec_resblocks_4_convs2_0_weight_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("xt_25_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_213_cast_fp16 = add(x = xt_25_cast_fp16, y = input_183_has_output_shape_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_215_cast_fp16 = leaky_relu(alpha = var_764, x = input_213_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
tensor<string, []> input_217_pad_type_0 = const()[name = tensor<string, []>("input_217_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_217_pad_0 = const()[name = tensor<string, []>("input_217_pad_0"), val = tensor<int32, [2]>([9, 9])];
tensor<int32, [1]> input_217_dilations_0 = const()[name = tensor<string, []>("input_217_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_217_strides_0 = const()[name = tensor<string, []>("input_217_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_217_groups_0 = const()[name = tensor<string, []>("input_217_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13412032)))];
tensor<fp16, [80]> dec_resblocks_4_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13501696)))];
tensor<fp16, [1, 80, 24576]> input_217_cast_fp16 = conv(bias = dec_resblocks_4_convs1_1_bias_to_fp16, dilations = input_217_dilations_0, groups = input_217_groups_0, pad = input_217_pad_0, pad_type = input_217_pad_type_0, strides = input_217_strides_0, weight = dec_resblocks_4_convs1_1_weight_to_fp16, x = input_215_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_219_cast_fp16 = leaky_relu(alpha = var_764, x = input_217_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
tensor<string, []> xt_27_pad_type_0 = const()[name = tensor<string, []>("xt_27_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_27_pad_0 = const()[name = tensor<string, []>("xt_27_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_27_strides_0 = const()[name = tensor<string, []>("xt_27_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_27_dilations_0 = const()[name = tensor<string, []>("xt_27_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_27_groups_0 = const()[name = tensor<string, []>("xt_27_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13501952)))];
tensor<fp16, [80]> dec_resblocks_4_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13591616)))];
tensor<fp16, [1, 80, 24576]> xt_27_cast_fp16 = conv(bias = dec_resblocks_4_convs2_1_bias_to_fp16, dilations = xt_27_dilations_0, groups = xt_27_groups_0, pad = xt_27_pad_0, pad_type = xt_27_pad_type_0, strides = xt_27_strides_0, weight = dec_resblocks_4_convs2_1_weight_to_fp16, x = input_219_cast_fp16)[name = tensor<string, []>("xt_27_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_221_cast_fp16 = add(x = xt_27_cast_fp16, y = input_213_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_223_cast_fp16 = leaky_relu(alpha = var_764, x = input_221_cast_fp16)[name = tensor<string, []>("input_223_cast_fp16")];
tensor<string, []> input_225_pad_type_0 = const()[name = tensor<string, []>("input_225_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_225_pad_0 = const()[name = tensor<string, []>("input_225_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_225_dilations_0 = const()[name = tensor<string, []>("input_225_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_225_strides_0 = const()[name = tensor<string, []>("input_225_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_225_groups_0 = const()[name = tensor<string, []>("input_225_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13591872)))];
tensor<fp16, [80]> dec_resblocks_4_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs1_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13681536)))];
tensor<fp16, [1, 80, 24576]> input_225_cast_fp16 = conv(bias = dec_resblocks_4_convs1_2_bias_to_fp16, dilations = input_225_dilations_0, groups = input_225_groups_0, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = input_225_strides_0, weight = dec_resblocks_4_convs1_2_weight_to_fp16, x = input_223_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_227_cast_fp16 = leaky_relu(alpha = var_764, x = input_225_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
tensor<string, []> xt_29_pad_type_0 = const()[name = tensor<string, []>("xt_29_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_29_pad_0 = const()[name = tensor<string, []>("xt_29_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_29_strides_0 = const()[name = tensor<string, []>("xt_29_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_29_dilations_0 = const()[name = tensor<string, []>("xt_29_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_29_groups_0 = const()[name = tensor<string, []>("xt_29_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 7]> dec_resblocks_4_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13681792)))];
tensor<fp16, [80]> dec_resblocks_4_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_4_convs2_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13771456)))];
tensor<fp16, [1, 80, 24576]> xt_29_cast_fp16 = conv(bias = dec_resblocks_4_convs2_2_bias_to_fp16, dilations = xt_29_dilations_0, groups = xt_29_groups_0, pad = xt_29_pad_0, pad_type = xt_29_pad_type_0, strides = xt_29_strides_0, weight = dec_resblocks_4_convs2_2_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("xt_29_cast_fp16")];
tensor<fp16, [1, 80, 24576]> var_1145_cast_fp16 = add(x = xt_29_cast_fp16, y = input_221_cast_fp16)[name = tensor<string, []>("op_1145_cast_fp16")];
tensor<fp16, [1, 80, 24576]> xs_9_cast_fp16 = add(x = xs_7_cast_fp16, y = var_1145_cast_fp16)[name = tensor<string, []>("xs_9_cast_fp16")];
tensor<string, []> input_231_pad_type_0 = const()[name = tensor<string, []>("input_231_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_231_pad_0 = const()[name = tensor<string, []>("input_231_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_231_strides_0 = const()[name = tensor<string, []>("input_231_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_231_dilations_0 = const()[name = tensor<string, []>("input_231_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_231_groups_0 = const()[name = tensor<string, []>("input_231_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13771712)))];
tensor<fp16, [80]> dec_resblocks_5_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13912576)))];
tensor<fp16, [1, 80, 24576]> input_231_cast_fp16 = conv(bias = dec_resblocks_5_convs1_0_bias_to_fp16, dilations = input_231_dilations_0, groups = input_231_groups_0, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = input_231_strides_0, weight = dec_resblocks_5_convs1_0_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("input_231_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_233_cast_fp16 = leaky_relu(alpha = var_764, x = input_231_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
tensor<string, []> xt_31_pad_type_0 = const()[name = tensor<string, []>("xt_31_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_31_pad_0 = const()[name = tensor<string, []>("xt_31_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_31_strides_0 = const()[name = tensor<string, []>("xt_31_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_31_dilations_0 = const()[name = tensor<string, []>("xt_31_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_31_groups_0 = const()[name = tensor<string, []>("xt_31_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_0_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13912832)))];
tensor<fp16, [80]> dec_resblocks_5_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_0_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14053696)))];
tensor<fp16, [1, 80, 24576]> xt_31_cast_fp16 = conv(bias = dec_resblocks_5_convs2_0_bias_to_fp16, dilations = xt_31_dilations_0, groups = xt_31_groups_0, pad = xt_31_pad_0, pad_type = xt_31_pad_type_0, strides = xt_31_strides_0, weight = dec_resblocks_5_convs2_0_weight_to_fp16, x = input_233_cast_fp16)[name = tensor<string, []>("xt_31_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_235_cast_fp16 = add(x = xt_31_cast_fp16, y = input_183_has_output_shape_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_237_cast_fp16 = leaky_relu(alpha = var_764, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
tensor<string, []> input_239_pad_type_0 = const()[name = tensor<string, []>("input_239_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_239_pad_0 = const()[name = tensor<string, []>("input_239_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_239_dilations_0 = const()[name = tensor<string, []>("input_239_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_239_strides_0 = const()[name = tensor<string, []>("input_239_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_239_groups_0 = const()[name = tensor<string, []>("input_239_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14053952)))];
tensor<fp16, [80]> dec_resblocks_5_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14194816)))];
tensor<fp16, [1, 80, 24576]> input_239_cast_fp16 = conv(bias = dec_resblocks_5_convs1_1_bias_to_fp16, dilations = input_239_dilations_0, groups = input_239_groups_0, pad = input_239_pad_0, pad_type = input_239_pad_type_0, strides = input_239_strides_0, weight = dec_resblocks_5_convs1_1_weight_to_fp16, x = input_237_cast_fp16)[name = tensor<string, []>("input_239_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_241_cast_fp16 = leaky_relu(alpha = var_764, x = input_239_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
tensor<string, []> xt_33_pad_type_0 = const()[name = tensor<string, []>("xt_33_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_33_pad_0 = const()[name = tensor<string, []>("xt_33_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_33_strides_0 = const()[name = tensor<string, []>("xt_33_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_33_dilations_0 = const()[name = tensor<string, []>("xt_33_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_33_groups_0 = const()[name = tensor<string, []>("xt_33_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_1_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14195072)))];
tensor<fp16, [80]> dec_resblocks_5_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14335936)))];
tensor<fp16, [1, 80, 24576]> xt_33_cast_fp16 = conv(bias = dec_resblocks_5_convs2_1_bias_to_fp16, dilations = xt_33_dilations_0, groups = xt_33_groups_0, pad = xt_33_pad_0, pad_type = xt_33_pad_type_0, strides = xt_33_strides_0, weight = dec_resblocks_5_convs2_1_weight_to_fp16, x = input_241_cast_fp16)[name = tensor<string, []>("xt_33_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_243_cast_fp16 = add(x = xt_33_cast_fp16, y = input_235_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_245_cast_fp16 = leaky_relu(alpha = var_764, x = input_243_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
tensor<string, []> input_247_pad_type_0 = const()[name = tensor<string, []>("input_247_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_247_pad_0 = const()[name = tensor<string, []>("input_247_pad_0"), val = tensor<int32, [2]>([25, 25])];
tensor<int32, [1]> input_247_dilations_0 = const()[name = tensor<string, []>("input_247_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_247_strides_0 = const()[name = tensor<string, []>("input_247_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_247_groups_0 = const()[name = tensor<string, []>("input_247_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14336192)))];
tensor<fp16, [80]> dec_resblocks_5_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs1_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14477056)))];
tensor<fp16, [1, 80, 24576]> input_247_cast_fp16 = conv(bias = dec_resblocks_5_convs1_2_bias_to_fp16, dilations = input_247_dilations_0, groups = input_247_groups_0, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = input_247_strides_0, weight = dec_resblocks_5_convs1_2_weight_to_fp16, x = input_245_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_249_cast_fp16 = leaky_relu(alpha = var_764, x = input_247_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
tensor<string, []> xt_35_pad_type_0 = const()[name = tensor<string, []>("xt_35_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_35_pad_0 = const()[name = tensor<string, []>("xt_35_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_35_strides_0 = const()[name = tensor<string, []>("xt_35_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_35_dilations_0 = const()[name = tensor<string, []>("xt_35_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_35_groups_0 = const()[name = tensor<string, []>("xt_35_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [80, 80, 11]> dec_resblocks_5_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_2_weight_to_fp16"), val = tensor<fp16, [80, 80, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14477312)))];
tensor<fp16, [80]> dec_resblocks_5_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_5_convs2_2_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14618176)))];
tensor<fp16, [1, 80, 24576]> xt_35_cast_fp16 = conv(bias = dec_resblocks_5_convs2_2_bias_to_fp16, dilations = xt_35_dilations_0, groups = xt_35_groups_0, pad = xt_35_pad_0, pad_type = xt_35_pad_type_0, strides = xt_35_strides_0, weight = dec_resblocks_5_convs2_2_weight_to_fp16, x = input_249_cast_fp16)[name = tensor<string, []>("xt_35_cast_fp16")];
tensor<fp16, [1, 80, 24576]> var_1209_cast_fp16 = add(x = xt_35_cast_fp16, y = input_243_cast_fp16)[name = tensor<string, []>("op_1209_cast_fp16")];
tensor<fp16, [1, 80, 24576]> xs_11_cast_fp16 = add(x = xs_9_cast_fp16, y = var_1209_cast_fp16)[name = tensor<string, []>("xs_11_cast_fp16")];
tensor<fp16, []> _inversed_input_251_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_251_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)];
tensor<fp16, [1, 80, 24576]> _inversed_input_251_cast_fp16 = mul(x = xs_11_cast_fp16, y = _inversed_input_251_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_251_cast_fp16")];
tensor<fp16, [1, 80, 24576]> input_253_cast_fp16 = leaky_relu(alpha = var_764, x = _inversed_input_251_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
tensor<string, []> input_255_pad_type_0 = const()[name = tensor<string, []>("input_255_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_255_pad_0 = const()[name = tensor<string, []>("input_255_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_255_strides_0 = const()[name = tensor<string, []>("input_255_strides_0"), val = tensor<int32, [1]>([2])];
tensor<int32, [1]> input_255_dilations_0 = const()[name = tensor<string, []>("input_255_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_255_groups_0 = const()[name = tensor<string, []>("input_255_groups_0"), val = tensor<int32, []>(1)];
tensor<int32, [3]> input_255_has_output_shape_output_shape_0 = const()[name = tensor<string, []>("input_255_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 40, 49152])];
tensor<fp16, [80, 40, 4]> dec_ups_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_ups_2_weight_to_fp16"), val = tensor<fp16, [80, 40, 4]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14618432)))];
tensor<fp16, [40]> dec_ups_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_ups_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14644096)))];
tensor<fp16, [1, 40, 49152]> input_255_has_output_shape_cast_fp16 = conv_transpose(bias = dec_ups_2_bias_to_fp16, dilations = input_255_dilations_0, groups = input_255_groups_0, output_shape = input_255_has_output_shape_output_shape_0, pad = input_255_pad_0, pad_type = input_255_pad_type_0, strides = input_255_strides_0, weight = dec_ups_2_weight_to_fp16, x = input_253_cast_fp16)[name = tensor<string, []>("input_255_has_output_shape_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_257_cast_fp16 = leaky_relu(alpha = var_764, x = input_255_has_output_shape_cast_fp16)[name = tensor<string, []>("input_257_cast_fp16")];
tensor<string, []> input_259_pad_type_0 = const()[name = tensor<string, []>("input_259_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_259_pad_0 = const()[name = tensor<string, []>("input_259_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_259_strides_0 = const()[name = tensor<string, []>("input_259_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_259_dilations_0 = const()[name = tensor<string, []>("input_259_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_259_groups_0 = const()[name = tensor<string, []>("input_259_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14644288)))];
tensor<fp16, [40]> dec_resblocks_6_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14653952)))];
tensor<fp16, [1, 40, 49152]> input_259_cast_fp16 = conv(bias = dec_resblocks_6_convs1_0_bias_to_fp16, dilations = input_259_dilations_0, groups = input_259_groups_0, pad = input_259_pad_0, pad_type = input_259_pad_type_0, strides = input_259_strides_0, weight = dec_resblocks_6_convs1_0_weight_to_fp16, x = input_257_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_261_cast_fp16 = leaky_relu(alpha = var_764, x = input_259_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
tensor<string, []> xt_37_pad_type_0 = const()[name = tensor<string, []>("xt_37_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_37_pad_0 = const()[name = tensor<string, []>("xt_37_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_37_strides_0 = const()[name = tensor<string, []>("xt_37_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_37_dilations_0 = const()[name = tensor<string, []>("xt_37_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_37_groups_0 = const()[name = tensor<string, []>("xt_37_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14654144)))];
tensor<fp16, [40]> dec_resblocks_6_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14663808)))];
tensor<fp16, [1, 40, 49152]> xt_37_cast_fp16 = conv(bias = dec_resblocks_6_convs2_0_bias_to_fp16, dilations = xt_37_dilations_0, groups = xt_37_groups_0, pad = xt_37_pad_0, pad_type = xt_37_pad_type_0, strides = xt_37_strides_0, weight = dec_resblocks_6_convs2_0_weight_to_fp16, x = input_261_cast_fp16)[name = tensor<string, []>("xt_37_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_263_cast_fp16 = add(x = xt_37_cast_fp16, y = input_255_has_output_shape_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_265_cast_fp16 = leaky_relu(alpha = var_764, x = input_263_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
tensor<string, []> input_267_pad_type_0 = const()[name = tensor<string, []>("input_267_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_267_pad_0 = const()[name = tensor<string, []>("input_267_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_267_dilations_0 = const()[name = tensor<string, []>("input_267_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_267_strides_0 = const()[name = tensor<string, []>("input_267_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_267_groups_0 = const()[name = tensor<string, []>("input_267_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14664000)))];
tensor<fp16, [40]> dec_resblocks_6_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14673664)))];
tensor<fp16, [1, 40, 49152]> input_267_cast_fp16 = conv(bias = dec_resblocks_6_convs1_1_bias_to_fp16, dilations = input_267_dilations_0, groups = input_267_groups_0, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = input_267_strides_0, weight = dec_resblocks_6_convs1_1_weight_to_fp16, x = input_265_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_269_cast_fp16 = leaky_relu(alpha = var_764, x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
tensor<string, []> xt_39_pad_type_0 = const()[name = tensor<string, []>("xt_39_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_39_pad_0 = const()[name = tensor<string, []>("xt_39_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_39_strides_0 = const()[name = tensor<string, []>("xt_39_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_39_dilations_0 = const()[name = tensor<string, []>("xt_39_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_39_groups_0 = const()[name = tensor<string, []>("xt_39_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14673856)))];
tensor<fp16, [40]> dec_resblocks_6_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14683520)))];
tensor<fp16, [1, 40, 49152]> xt_39_cast_fp16 = conv(bias = dec_resblocks_6_convs2_1_bias_to_fp16, dilations = xt_39_dilations_0, groups = xt_39_groups_0, pad = xt_39_pad_0, pad_type = xt_39_pad_type_0, strides = xt_39_strides_0, weight = dec_resblocks_6_convs2_1_weight_to_fp16, x = input_269_cast_fp16)[name = tensor<string, []>("xt_39_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_271_cast_fp16 = add(x = xt_39_cast_fp16, y = input_263_cast_fp16)[name = tensor<string, []>("input_271_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_273_cast_fp16 = leaky_relu(alpha = var_764, x = input_271_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
tensor<string, []> input_275_pad_type_0 = const()[name = tensor<string, []>("input_275_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_275_pad_0 = const()[name = tensor<string, []>("input_275_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_275_dilations_0 = const()[name = tensor<string, []>("input_275_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_275_strides_0 = const()[name = tensor<string, []>("input_275_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_275_groups_0 = const()[name = tensor<string, []>("input_275_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14683712)))];
tensor<fp16, [40]> dec_resblocks_6_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs1_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14693376)))];
tensor<fp16, [1, 40, 49152]> input_275_cast_fp16 = conv(bias = dec_resblocks_6_convs1_2_bias_to_fp16, dilations = input_275_dilations_0, groups = input_275_groups_0, pad = input_275_pad_0, pad_type = input_275_pad_type_0, strides = input_275_strides_0, weight = dec_resblocks_6_convs1_2_weight_to_fp16, x = input_273_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_277_cast_fp16 = leaky_relu(alpha = var_764, x = input_275_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
tensor<string, []> xt_41_pad_type_0 = const()[name = tensor<string, []>("xt_41_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_41_pad_0 = const()[name = tensor<string, []>("xt_41_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_41_strides_0 = const()[name = tensor<string, []>("xt_41_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_41_dilations_0 = const()[name = tensor<string, []>("xt_41_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_41_groups_0 = const()[name = tensor<string, []>("xt_41_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 3]> dec_resblocks_6_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14693568)))];
tensor<fp16, [40]> dec_resblocks_6_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_6_convs2_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14703232)))];
tensor<fp16, [1, 40, 49152]> xt_41_cast_fp16 = conv(bias = dec_resblocks_6_convs2_2_bias_to_fp16, dilations = xt_41_dilations_0, groups = xt_41_groups_0, pad = xt_41_pad_0, pad_type = xt_41_pad_type_0, strides = xt_41_strides_0, weight = dec_resblocks_6_convs2_2_weight_to_fp16, x = input_277_cast_fp16)[name = tensor<string, []>("xt_41_cast_fp16")];
tensor<fp16, [1, 40, 49152]> xs_13_cast_fp16 = add(x = xt_41_cast_fp16, y = input_271_cast_fp16)[name = tensor<string, []>("xs_13_cast_fp16")];
tensor<string, []> input_281_pad_type_0 = const()[name = tensor<string, []>("input_281_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_281_pad_0 = const()[name = tensor<string, []>("input_281_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_281_strides_0 = const()[name = tensor<string, []>("input_281_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_281_dilations_0 = const()[name = tensor<string, []>("input_281_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_281_groups_0 = const()[name = tensor<string, []>("input_281_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14703424)))];
tensor<fp16, [40]> dec_resblocks_7_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14725888)))];
tensor<fp16, [1, 40, 49152]> input_281_cast_fp16 = conv(bias = dec_resblocks_7_convs1_0_bias_to_fp16, dilations = input_281_dilations_0, groups = input_281_groups_0, pad = input_281_pad_0, pad_type = input_281_pad_type_0, strides = input_281_strides_0, weight = dec_resblocks_7_convs1_0_weight_to_fp16, x = input_257_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_283_cast_fp16 = leaky_relu(alpha = var_764, x = input_281_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
tensor<string, []> xt_43_pad_type_0 = const()[name = tensor<string, []>("xt_43_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_43_pad_0 = const()[name = tensor<string, []>("xt_43_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_43_strides_0 = const()[name = tensor<string, []>("xt_43_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_43_dilations_0 = const()[name = tensor<string, []>("xt_43_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_43_groups_0 = const()[name = tensor<string, []>("xt_43_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14726080)))];
tensor<fp16, [40]> dec_resblocks_7_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14748544)))];
tensor<fp16, [1, 40, 49152]> xt_43_cast_fp16 = conv(bias = dec_resblocks_7_convs2_0_bias_to_fp16, dilations = xt_43_dilations_0, groups = xt_43_groups_0, pad = xt_43_pad_0, pad_type = xt_43_pad_type_0, strides = xt_43_strides_0, weight = dec_resblocks_7_convs2_0_weight_to_fp16, x = input_283_cast_fp16)[name = tensor<string, []>("xt_43_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_285_cast_fp16 = add(x = xt_43_cast_fp16, y = input_255_has_output_shape_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_287_cast_fp16 = leaky_relu(alpha = var_764, x = input_285_cast_fp16)[name = tensor<string, []>("input_287_cast_fp16")];
tensor<string, []> input_289_pad_type_0 = const()[name = tensor<string, []>("input_289_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_289_pad_0 = const()[name = tensor<string, []>("input_289_pad_0"), val = tensor<int32, [2]>([9, 9])];
tensor<int32, [1]> input_289_dilations_0 = const()[name = tensor<string, []>("input_289_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_289_strides_0 = const()[name = tensor<string, []>("input_289_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_289_groups_0 = const()[name = tensor<string, []>("input_289_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14748736)))];
tensor<fp16, [40]> dec_resblocks_7_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14771200)))];
tensor<fp16, [1, 40, 49152]> input_289_cast_fp16 = conv(bias = dec_resblocks_7_convs1_1_bias_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = dec_resblocks_7_convs1_1_weight_to_fp16, x = input_287_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_291_cast_fp16 = leaky_relu(alpha = var_764, x = input_289_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
tensor<string, []> xt_45_pad_type_0 = const()[name = tensor<string, []>("xt_45_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_45_pad_0 = const()[name = tensor<string, []>("xt_45_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_45_strides_0 = const()[name = tensor<string, []>("xt_45_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_45_dilations_0 = const()[name = tensor<string, []>("xt_45_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_45_groups_0 = const()[name = tensor<string, []>("xt_45_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14771392)))];
tensor<fp16, [40]> dec_resblocks_7_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14793856)))];
tensor<fp16, [1, 40, 49152]> xt_45_cast_fp16 = conv(bias = dec_resblocks_7_convs2_1_bias_to_fp16, dilations = xt_45_dilations_0, groups = xt_45_groups_0, pad = xt_45_pad_0, pad_type = xt_45_pad_type_0, strides = xt_45_strides_0, weight = dec_resblocks_7_convs2_1_weight_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("xt_45_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_293_cast_fp16 = add(x = xt_45_cast_fp16, y = input_285_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_295_cast_fp16 = leaky_relu(alpha = var_764, x = input_293_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
tensor<string, []> input_297_pad_type_0 = const()[name = tensor<string, []>("input_297_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_297_pad_0 = const()[name = tensor<string, []>("input_297_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_297_dilations_0 = const()[name = tensor<string, []>("input_297_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_297_strides_0 = const()[name = tensor<string, []>("input_297_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_297_groups_0 = const()[name = tensor<string, []>("input_297_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14794048)))];
tensor<fp16, [40]> dec_resblocks_7_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs1_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14816512)))];
tensor<fp16, [1, 40, 49152]> input_297_cast_fp16 = conv(bias = dec_resblocks_7_convs1_2_bias_to_fp16, dilations = input_297_dilations_0, groups = input_297_groups_0, pad = input_297_pad_0, pad_type = input_297_pad_type_0, strides = input_297_strides_0, weight = dec_resblocks_7_convs1_2_weight_to_fp16, x = input_295_cast_fp16)[name = tensor<string, []>("input_297_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_299_cast_fp16 = leaky_relu(alpha = var_764, x = input_297_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
tensor<string, []> xt_47_pad_type_0 = const()[name = tensor<string, []>("xt_47_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_47_pad_0 = const()[name = tensor<string, []>("xt_47_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_47_strides_0 = const()[name = tensor<string, []>("xt_47_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_47_dilations_0 = const()[name = tensor<string, []>("xt_47_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_47_groups_0 = const()[name = tensor<string, []>("xt_47_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 7]> dec_resblocks_7_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14816704)))];
tensor<fp16, [40]> dec_resblocks_7_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_7_convs2_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14839168)))];
tensor<fp16, [1, 40, 49152]> xt_47_cast_fp16 = conv(bias = dec_resblocks_7_convs2_2_bias_to_fp16, dilations = xt_47_dilations_0, groups = xt_47_groups_0, pad = xt_47_pad_0, pad_type = xt_47_pad_type_0, strides = xt_47_strides_0, weight = dec_resblocks_7_convs2_2_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("xt_47_cast_fp16")];
tensor<fp16, [1, 40, 49152]> var_1346_cast_fp16 = add(x = xt_47_cast_fp16, y = input_293_cast_fp16)[name = tensor<string, []>("op_1346_cast_fp16")];
tensor<fp16, [1, 40, 49152]> xs_15_cast_fp16 = add(x = xs_13_cast_fp16, y = var_1346_cast_fp16)[name = tensor<string, []>("xs_15_cast_fp16")];
tensor<string, []> input_303_pad_type_0 = const()[name = tensor<string, []>("input_303_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_303_pad_0 = const()[name = tensor<string, []>("input_303_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_303_strides_0 = const()[name = tensor<string, []>("input_303_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_303_dilations_0 = const()[name = tensor<string, []>("input_303_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_303_groups_0 = const()[name = tensor<string, []>("input_303_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14839360)))];
tensor<fp16, [40]> dec_resblocks_8_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14874624)))];
tensor<fp16, [1, 40, 49152]> input_303_cast_fp16 = conv(bias = dec_resblocks_8_convs1_0_bias_to_fp16, dilations = input_303_dilations_0, groups = input_303_groups_0, pad = input_303_pad_0, pad_type = input_303_pad_type_0, strides = input_303_strides_0, weight = dec_resblocks_8_convs1_0_weight_to_fp16, x = input_257_cast_fp16)[name = tensor<string, []>("input_303_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_305_cast_fp16 = leaky_relu(alpha = var_764, x = input_303_cast_fp16)[name = tensor<string, []>("input_305_cast_fp16")];
tensor<string, []> xt_49_pad_type_0 = const()[name = tensor<string, []>("xt_49_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_49_pad_0 = const()[name = tensor<string, []>("xt_49_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_49_strides_0 = const()[name = tensor<string, []>("xt_49_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_49_dilations_0 = const()[name = tensor<string, []>("xt_49_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_49_groups_0 = const()[name = tensor<string, []>("xt_49_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_0_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14874816)))];
tensor<fp16, [40]> dec_resblocks_8_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_0_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14910080)))];
tensor<fp16, [1, 40, 49152]> xt_49_cast_fp16 = conv(bias = dec_resblocks_8_convs2_0_bias_to_fp16, dilations = xt_49_dilations_0, groups = xt_49_groups_0, pad = xt_49_pad_0, pad_type = xt_49_pad_type_0, strides = xt_49_strides_0, weight = dec_resblocks_8_convs2_0_weight_to_fp16, x = input_305_cast_fp16)[name = tensor<string, []>("xt_49_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_307_cast_fp16 = add(x = xt_49_cast_fp16, y = input_255_has_output_shape_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_309_cast_fp16 = leaky_relu(alpha = var_764, x = input_307_cast_fp16)[name = tensor<string, []>("input_309_cast_fp16")];
tensor<string, []> input_311_pad_type_0 = const()[name = tensor<string, []>("input_311_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_311_pad_0 = const()[name = tensor<string, []>("input_311_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_311_dilations_0 = const()[name = tensor<string, []>("input_311_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_311_strides_0 = const()[name = tensor<string, []>("input_311_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_311_groups_0 = const()[name = tensor<string, []>("input_311_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14910272)))];
tensor<fp16, [40]> dec_resblocks_8_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14945536)))];
tensor<fp16, [1, 40, 49152]> input_311_cast_fp16 = conv(bias = dec_resblocks_8_convs1_1_bias_to_fp16, dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = dec_resblocks_8_convs1_1_weight_to_fp16, x = input_309_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_313_cast_fp16 = leaky_relu(alpha = var_764, x = input_311_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
tensor<string, []> xt_51_pad_type_0 = const()[name = tensor<string, []>("xt_51_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_51_pad_0 = const()[name = tensor<string, []>("xt_51_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_51_strides_0 = const()[name = tensor<string, []>("xt_51_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_51_dilations_0 = const()[name = tensor<string, []>("xt_51_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_51_groups_0 = const()[name = tensor<string, []>("xt_51_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_1_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14945728)))];
tensor<fp16, [40]> dec_resblocks_8_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_1_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14980992)))];
tensor<fp16, [1, 40, 49152]> xt_51_cast_fp16 = conv(bias = dec_resblocks_8_convs2_1_bias_to_fp16, dilations = xt_51_dilations_0, groups = xt_51_groups_0, pad = xt_51_pad_0, pad_type = xt_51_pad_type_0, strides = xt_51_strides_0, weight = dec_resblocks_8_convs2_1_weight_to_fp16, x = input_313_cast_fp16)[name = tensor<string, []>("xt_51_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_315_cast_fp16 = add(x = xt_51_cast_fp16, y = input_307_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_317_cast_fp16 = leaky_relu(alpha = var_764, x = input_315_cast_fp16)[name = tensor<string, []>("input_317_cast_fp16")];
tensor<string, []> input_319_pad_type_0 = const()[name = tensor<string, []>("input_319_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_319_pad_0 = const()[name = tensor<string, []>("input_319_pad_0"), val = tensor<int32, [2]>([25, 25])];
tensor<int32, [1]> input_319_dilations_0 = const()[name = tensor<string, []>("input_319_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_319_strides_0 = const()[name = tensor<string, []>("input_319_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_319_groups_0 = const()[name = tensor<string, []>("input_319_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14981184)))];
tensor<fp16, [40]> dec_resblocks_8_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs1_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15016448)))];
tensor<fp16, [1, 40, 49152]> input_319_cast_fp16 = conv(bias = dec_resblocks_8_convs1_2_bias_to_fp16, dilations = input_319_dilations_0, groups = input_319_groups_0, pad = input_319_pad_0, pad_type = input_319_pad_type_0, strides = input_319_strides_0, weight = dec_resblocks_8_convs1_2_weight_to_fp16, x = input_317_cast_fp16)[name = tensor<string, []>("input_319_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_321_cast_fp16 = leaky_relu(alpha = var_764, x = input_319_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
tensor<string, []> xt_53_pad_type_0 = const()[name = tensor<string, []>("xt_53_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_53_pad_0 = const()[name = tensor<string, []>("xt_53_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_53_strides_0 = const()[name = tensor<string, []>("xt_53_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_53_dilations_0 = const()[name = tensor<string, []>("xt_53_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_53_groups_0 = const()[name = tensor<string, []>("xt_53_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [40, 40, 11]> dec_resblocks_8_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_2_weight_to_fp16"), val = tensor<fp16, [40, 40, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15016640)))];
tensor<fp16, [40]> dec_resblocks_8_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_8_convs2_2_bias_to_fp16"), val = tensor<fp16, [40]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15051904)))];
tensor<fp16, [1, 40, 49152]> xt_53_cast_fp16 = conv(bias = dec_resblocks_8_convs2_2_bias_to_fp16, dilations = xt_53_dilations_0, groups = xt_53_groups_0, pad = xt_53_pad_0, pad_type = xt_53_pad_type_0, strides = xt_53_strides_0, weight = dec_resblocks_8_convs2_2_weight_to_fp16, x = input_321_cast_fp16)[name = tensor<string, []>("xt_53_cast_fp16")];
tensor<fp16, [1, 40, 49152]> var_1410_cast_fp16 = add(x = xt_53_cast_fp16, y = input_315_cast_fp16)[name = tensor<string, []>("op_1410_cast_fp16")];
tensor<fp16, [1, 40, 49152]> xs_17_cast_fp16 = add(x = xs_15_cast_fp16, y = var_1410_cast_fp16)[name = tensor<string, []>("xs_17_cast_fp16")];
tensor<fp16, []> _inversed_input_323_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_323_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)];
tensor<fp16, [1, 40, 49152]> _inversed_input_323_cast_fp16 = mul(x = xs_17_cast_fp16, y = _inversed_input_323_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_323_cast_fp16")];
tensor<fp16, [1, 40, 49152]> input_325_cast_fp16 = leaky_relu(alpha = var_764, x = _inversed_input_323_cast_fp16)[name = tensor<string, []>("input_325_cast_fp16")];
tensor<string, []> input_327_pad_type_0 = const()[name = tensor<string, []>("input_327_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_327_pad_0 = const()[name = tensor<string, []>("input_327_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_327_strides_0 = const()[name = tensor<string, []>("input_327_strides_0"), val = tensor<int32, [1]>([2])];
tensor<int32, [1]> input_327_dilations_0 = const()[name = tensor<string, []>("input_327_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_327_groups_0 = const()[name = tensor<string, []>("input_327_groups_0"), val = tensor<int32, []>(1)];
tensor<int32, [3]> input_327_has_output_shape_output_shape_0 = const()[name = tensor<string, []>("input_327_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 20, 98304])];
tensor<fp16, [40, 20, 4]> dec_ups_3_weight_to_fp16 = const()[name = tensor<string, []>("dec_ups_3_weight_to_fp16"), val = tensor<fp16, [40, 20, 4]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15052096)))];
tensor<fp16, [20]> dec_ups_3_bias_to_fp16 = const()[name = tensor<string, []>("dec_ups_3_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15058560)))];
tensor<fp16, [1, 20, 98304]> input_327_has_output_shape_cast_fp16 = conv_transpose(bias = dec_ups_3_bias_to_fp16, dilations = input_327_dilations_0, groups = input_327_groups_0, output_shape = input_327_has_output_shape_output_shape_0, pad = input_327_pad_0, pad_type = input_327_pad_type_0, strides = input_327_strides_0, weight = dec_ups_3_weight_to_fp16, x = input_325_cast_fp16)[name = tensor<string, []>("input_327_has_output_shape_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_329_cast_fp16 = leaky_relu(alpha = var_764, x = input_327_has_output_shape_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
tensor<string, []> input_331_pad_type_0 = const()[name = tensor<string, []>("input_331_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_331_pad_0 = const()[name = tensor<string, []>("input_331_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> input_331_strides_0 = const()[name = tensor<string, []>("input_331_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_331_dilations_0 = const()[name = tensor<string, []>("input_331_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_331_groups_0 = const()[name = tensor<string, []>("input_331_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15058688)))];
tensor<fp16, [20]> dec_resblocks_9_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15061184)))];
tensor<fp16, [1, 20, 98304]> input_331_cast_fp16 = conv(bias = dec_resblocks_9_convs1_0_bias_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = dec_resblocks_9_convs1_0_weight_to_fp16, x = input_329_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_333_cast_fp16 = leaky_relu(alpha = var_764, x = input_331_cast_fp16)[name = tensor<string, []>("input_333_cast_fp16")];
tensor<string, []> xt_55_pad_type_0 = const()[name = tensor<string, []>("xt_55_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_55_pad_0 = const()[name = tensor<string, []>("xt_55_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_55_strides_0 = const()[name = tensor<string, []>("xt_55_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_55_dilations_0 = const()[name = tensor<string, []>("xt_55_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_55_groups_0 = const()[name = tensor<string, []>("xt_55_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15061312)))];
tensor<fp16, [20]> dec_resblocks_9_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15063808)))];
tensor<fp16, [1, 20, 98304]> xt_55_cast_fp16 = conv(bias = dec_resblocks_9_convs2_0_bias_to_fp16, dilations = xt_55_dilations_0, groups = xt_55_groups_0, pad = xt_55_pad_0, pad_type = xt_55_pad_type_0, strides = xt_55_strides_0, weight = dec_resblocks_9_convs2_0_weight_to_fp16, x = input_333_cast_fp16)[name = tensor<string, []>("xt_55_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_335_cast_fp16 = add(x = xt_55_cast_fp16, y = input_327_has_output_shape_cast_fp16)[name = tensor<string, []>("input_335_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_337_cast_fp16 = leaky_relu(alpha = var_764, x = input_335_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
tensor<string, []> input_339_pad_type_0 = const()[name = tensor<string, []>("input_339_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_339_pad_0 = const()[name = tensor<string, []>("input_339_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_339_dilations_0 = const()[name = tensor<string, []>("input_339_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_339_strides_0 = const()[name = tensor<string, []>("input_339_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_339_groups_0 = const()[name = tensor<string, []>("input_339_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15063936)))];
tensor<fp16, [20]> dec_resblocks_9_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15066432)))];
tensor<fp16, [1, 20, 98304]> input_339_cast_fp16 = conv(bias = dec_resblocks_9_convs1_1_bias_to_fp16, dilations = input_339_dilations_0, groups = input_339_groups_0, pad = input_339_pad_0, pad_type = input_339_pad_type_0, strides = input_339_strides_0, weight = dec_resblocks_9_convs1_1_weight_to_fp16, x = input_337_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_341_cast_fp16 = leaky_relu(alpha = var_764, x = input_339_cast_fp16)[name = tensor<string, []>("input_341_cast_fp16")];
tensor<string, []> xt_57_pad_type_0 = const()[name = tensor<string, []>("xt_57_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_57_pad_0 = const()[name = tensor<string, []>("xt_57_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_57_strides_0 = const()[name = tensor<string, []>("xt_57_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_57_dilations_0 = const()[name = tensor<string, []>("xt_57_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_57_groups_0 = const()[name = tensor<string, []>("xt_57_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15066560)))];
tensor<fp16, [20]> dec_resblocks_9_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15069056)))];
tensor<fp16, [1, 20, 98304]> xt_57_cast_fp16 = conv(bias = dec_resblocks_9_convs2_1_bias_to_fp16, dilations = xt_57_dilations_0, groups = xt_57_groups_0, pad = xt_57_pad_0, pad_type = xt_57_pad_type_0, strides = xt_57_strides_0, weight = dec_resblocks_9_convs2_1_weight_to_fp16, x = input_341_cast_fp16)[name = tensor<string, []>("xt_57_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_343_cast_fp16 = add(x = xt_57_cast_fp16, y = input_335_cast_fp16)[name = tensor<string, []>("input_343_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_345_cast_fp16 = leaky_relu(alpha = var_764, x = input_343_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
tensor<string, []> input_347_pad_type_0 = const()[name = tensor<string, []>("input_347_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_347_pad_0 = const()[name = tensor<string, []>("input_347_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_347_dilations_0 = const()[name = tensor<string, []>("input_347_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_347_strides_0 = const()[name = tensor<string, []>("input_347_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_347_groups_0 = const()[name = tensor<string, []>("input_347_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15069184)))];
tensor<fp16, [20]> dec_resblocks_9_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs1_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15071680)))];
tensor<fp16, [1, 20, 98304]> input_347_cast_fp16 = conv(bias = dec_resblocks_9_convs1_2_bias_to_fp16, dilations = input_347_dilations_0, groups = input_347_groups_0, pad = input_347_pad_0, pad_type = input_347_pad_type_0, strides = input_347_strides_0, weight = dec_resblocks_9_convs1_2_weight_to_fp16, x = input_345_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_349_cast_fp16 = leaky_relu(alpha = var_764, x = input_347_cast_fp16)[name = tensor<string, []>("input_349_cast_fp16")];
tensor<string, []> xt_59_pad_type_0 = const()[name = tensor<string, []>("xt_59_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_59_pad_0 = const()[name = tensor<string, []>("xt_59_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [1]> xt_59_strides_0 = const()[name = tensor<string, []>("xt_59_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_59_dilations_0 = const()[name = tensor<string, []>("xt_59_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_59_groups_0 = const()[name = tensor<string, []>("xt_59_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 3]> dec_resblocks_9_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15071808)))];
tensor<fp16, [20]> dec_resblocks_9_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_9_convs2_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15074304)))];
tensor<fp16, [1, 20, 98304]> xt_59_cast_fp16 = conv(bias = dec_resblocks_9_convs2_2_bias_to_fp16, dilations = xt_59_dilations_0, groups = xt_59_groups_0, pad = xt_59_pad_0, pad_type = xt_59_pad_type_0, strides = xt_59_strides_0, weight = dec_resblocks_9_convs2_2_weight_to_fp16, x = input_349_cast_fp16)[name = tensor<string, []>("xt_59_cast_fp16")];
tensor<fp16, [1, 20, 98304]> xs_19_cast_fp16 = add(x = xt_59_cast_fp16, y = input_343_cast_fp16)[name = tensor<string, []>("xs_19_cast_fp16")];
tensor<string, []> input_353_pad_type_0 = const()[name = tensor<string, []>("input_353_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_353_pad_0 = const()[name = tensor<string, []>("input_353_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> input_353_strides_0 = const()[name = tensor<string, []>("input_353_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_353_dilations_0 = const()[name = tensor<string, []>("input_353_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_353_groups_0 = const()[name = tensor<string, []>("input_353_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15074432)))];
tensor<fp16, [20]> dec_resblocks_10_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15080128)))];
tensor<fp16, [1, 20, 98304]> input_353_cast_fp16 = conv(bias = dec_resblocks_10_convs1_0_bias_to_fp16, dilations = input_353_dilations_0, groups = input_353_groups_0, pad = input_353_pad_0, pad_type = input_353_pad_type_0, strides = input_353_strides_0, weight = dec_resblocks_10_convs1_0_weight_to_fp16, x = input_329_cast_fp16)[name = tensor<string, []>("input_353_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_355_cast_fp16 = leaky_relu(alpha = var_764, x = input_353_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
tensor<string, []> xt_61_pad_type_0 = const()[name = tensor<string, []>("xt_61_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_61_pad_0 = const()[name = tensor<string, []>("xt_61_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_61_strides_0 = const()[name = tensor<string, []>("xt_61_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_61_dilations_0 = const()[name = tensor<string, []>("xt_61_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_61_groups_0 = const()[name = tensor<string, []>("xt_61_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15080256)))];
tensor<fp16, [20]> dec_resblocks_10_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15085952)))];
tensor<fp16, [1, 20, 98304]> xt_61_cast_fp16 = conv(bias = dec_resblocks_10_convs2_0_bias_to_fp16, dilations = xt_61_dilations_0, groups = xt_61_groups_0, pad = xt_61_pad_0, pad_type = xt_61_pad_type_0, strides = xt_61_strides_0, weight = dec_resblocks_10_convs2_0_weight_to_fp16, x = input_355_cast_fp16)[name = tensor<string, []>("xt_61_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_357_cast_fp16 = add(x = xt_61_cast_fp16, y = input_327_has_output_shape_cast_fp16)[name = tensor<string, []>("input_357_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_359_cast_fp16 = leaky_relu(alpha = var_764, x = input_357_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
tensor<string, []> input_361_pad_type_0 = const()[name = tensor<string, []>("input_361_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_361_pad_0 = const()[name = tensor<string, []>("input_361_pad_0"), val = tensor<int32, [2]>([9, 9])];
tensor<int32, [1]> input_361_dilations_0 = const()[name = tensor<string, []>("input_361_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_361_strides_0 = const()[name = tensor<string, []>("input_361_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_361_groups_0 = const()[name = tensor<string, []>("input_361_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15086080)))];
tensor<fp16, [20]> dec_resblocks_10_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15091776)))];
tensor<fp16, [1, 20, 98304]> input_361_cast_fp16 = conv(bias = dec_resblocks_10_convs1_1_bias_to_fp16, dilations = input_361_dilations_0, groups = input_361_groups_0, pad = input_361_pad_0, pad_type = input_361_pad_type_0, strides = input_361_strides_0, weight = dec_resblocks_10_convs1_1_weight_to_fp16, x = input_359_cast_fp16)[name = tensor<string, []>("input_361_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_363_cast_fp16 = leaky_relu(alpha = var_764, x = input_361_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
tensor<string, []> xt_63_pad_type_0 = const()[name = tensor<string, []>("xt_63_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_63_pad_0 = const()[name = tensor<string, []>("xt_63_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_63_strides_0 = const()[name = tensor<string, []>("xt_63_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_63_dilations_0 = const()[name = tensor<string, []>("xt_63_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_63_groups_0 = const()[name = tensor<string, []>("xt_63_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15091904)))];
tensor<fp16, [20]> dec_resblocks_10_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15097600)))];
tensor<fp16, [1, 20, 98304]> xt_63_cast_fp16 = conv(bias = dec_resblocks_10_convs2_1_bias_to_fp16, dilations = xt_63_dilations_0, groups = xt_63_groups_0, pad = xt_63_pad_0, pad_type = xt_63_pad_type_0, strides = xt_63_strides_0, weight = dec_resblocks_10_convs2_1_weight_to_fp16, x = input_363_cast_fp16)[name = tensor<string, []>("xt_63_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_365_cast_fp16 = add(x = xt_63_cast_fp16, y = input_357_cast_fp16)[name = tensor<string, []>("input_365_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_367_cast_fp16 = leaky_relu(alpha = var_764, x = input_365_cast_fp16)[name = tensor<string, []>("input_367_cast_fp16")];
tensor<string, []> input_369_pad_type_0 = const()[name = tensor<string, []>("input_369_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_369_pad_0 = const()[name = tensor<string, []>("input_369_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_369_dilations_0 = const()[name = tensor<string, []>("input_369_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_369_strides_0 = const()[name = tensor<string, []>("input_369_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_369_groups_0 = const()[name = tensor<string, []>("input_369_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15097728)))];
tensor<fp16, [20]> dec_resblocks_10_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs1_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15103424)))];
tensor<fp16, [1, 20, 98304]> input_369_cast_fp16 = conv(bias = dec_resblocks_10_convs1_2_bias_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = dec_resblocks_10_convs1_2_weight_to_fp16, x = input_367_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_371_cast_fp16 = leaky_relu(alpha = var_764, x = input_369_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
tensor<string, []> xt_65_pad_type_0 = const()[name = tensor<string, []>("xt_65_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_65_pad_0 = const()[name = tensor<string, []>("xt_65_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> xt_65_strides_0 = const()[name = tensor<string, []>("xt_65_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_65_dilations_0 = const()[name = tensor<string, []>("xt_65_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_65_groups_0 = const()[name = tensor<string, []>("xt_65_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 7]> dec_resblocks_10_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15103552)))];
tensor<fp16, [20]> dec_resblocks_10_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_10_convs2_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15109248)))];
tensor<fp16, [1, 20, 98304]> xt_65_cast_fp16 = conv(bias = dec_resblocks_10_convs2_2_bias_to_fp16, dilations = xt_65_dilations_0, groups = xt_65_groups_0, pad = xt_65_pad_0, pad_type = xt_65_pad_type_0, strides = xt_65_strides_0, weight = dec_resblocks_10_convs2_2_weight_to_fp16, x = input_371_cast_fp16)[name = tensor<string, []>("xt_65_cast_fp16")];
tensor<fp16, [1, 20, 98304]> var_1547_cast_fp16 = add(x = xt_65_cast_fp16, y = input_365_cast_fp16)[name = tensor<string, []>("op_1547_cast_fp16")];
tensor<fp16, [1, 20, 98304]> xs_21_cast_fp16 = add(x = xs_19_cast_fp16, y = var_1547_cast_fp16)[name = tensor<string, []>("xs_21_cast_fp16")];
tensor<string, []> input_375_pad_type_0 = const()[name = tensor<string, []>("input_375_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_375_pad_0 = const()[name = tensor<string, []>("input_375_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> input_375_strides_0 = const()[name = tensor<string, []>("input_375_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> input_375_dilations_0 = const()[name = tensor<string, []>("input_375_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_375_groups_0 = const()[name = tensor<string, []>("input_375_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs1_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15109376)))];
tensor<fp16, [20]> dec_resblocks_11_convs1_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15118272)))];
tensor<fp16, [1, 20, 98304]> input_375_cast_fp16 = conv(bias = dec_resblocks_11_convs1_0_bias_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = dec_resblocks_11_convs1_0_weight_to_fp16, x = input_329_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_377_cast_fp16 = leaky_relu(alpha = var_764, x = input_375_cast_fp16)[name = tensor<string, []>("input_377_cast_fp16")];
tensor<string, []> xt_67_pad_type_0 = const()[name = tensor<string, []>("xt_67_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_67_pad_0 = const()[name = tensor<string, []>("xt_67_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_67_strides_0 = const()[name = tensor<string, []>("xt_67_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_67_dilations_0 = const()[name = tensor<string, []>("xt_67_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_67_groups_0 = const()[name = tensor<string, []>("xt_67_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs2_0_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_0_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15118400)))];
tensor<fp16, [20]> dec_resblocks_11_convs2_0_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_0_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15127296)))];
tensor<fp16, [1, 20, 98304]> xt_67_cast_fp16 = conv(bias = dec_resblocks_11_convs2_0_bias_to_fp16, dilations = xt_67_dilations_0, groups = xt_67_groups_0, pad = xt_67_pad_0, pad_type = xt_67_pad_type_0, strides = xt_67_strides_0, weight = dec_resblocks_11_convs2_0_weight_to_fp16, x = input_377_cast_fp16)[name = tensor<string, []>("xt_67_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_379_cast_fp16 = add(x = xt_67_cast_fp16, y = input_327_has_output_shape_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_381_cast_fp16 = leaky_relu(alpha = var_764, x = input_379_cast_fp16)[name = tensor<string, []>("input_381_cast_fp16")];
tensor<string, []> input_383_pad_type_0 = const()[name = tensor<string, []>("input_383_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_383_pad_0 = const()[name = tensor<string, []>("input_383_pad_0"), val = tensor<int32, [2]>([15, 15])];
tensor<int32, [1]> input_383_dilations_0 = const()[name = tensor<string, []>("input_383_dilations_0"), val = tensor<int32, [1]>([3])];
tensor<int32, [1]> input_383_strides_0 = const()[name = tensor<string, []>("input_383_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_383_groups_0 = const()[name = tensor<string, []>("input_383_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs1_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15127424)))];
tensor<fp16, [20]> dec_resblocks_11_convs1_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15136320)))];
tensor<fp16, [1, 20, 98304]> input_383_cast_fp16 = conv(bias = dec_resblocks_11_convs1_1_bias_to_fp16, dilations = input_383_dilations_0, groups = input_383_groups_0, pad = input_383_pad_0, pad_type = input_383_pad_type_0, strides = input_383_strides_0, weight = dec_resblocks_11_convs1_1_weight_to_fp16, x = input_381_cast_fp16)[name = tensor<string, []>("input_383_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_385_cast_fp16 = leaky_relu(alpha = var_764, x = input_383_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
tensor<string, []> xt_69_pad_type_0 = const()[name = tensor<string, []>("xt_69_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_69_pad_0 = const()[name = tensor<string, []>("xt_69_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_69_strides_0 = const()[name = tensor<string, []>("xt_69_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_69_dilations_0 = const()[name = tensor<string, []>("xt_69_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_69_groups_0 = const()[name = tensor<string, []>("xt_69_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs2_1_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_1_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15136448)))];
tensor<fp16, [20]> dec_resblocks_11_convs2_1_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_1_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15145344)))];
tensor<fp16, [1, 20, 98304]> xt_69_cast_fp16 = conv(bias = dec_resblocks_11_convs2_1_bias_to_fp16, dilations = xt_69_dilations_0, groups = xt_69_groups_0, pad = xt_69_pad_0, pad_type = xt_69_pad_type_0, strides = xt_69_strides_0, weight = dec_resblocks_11_convs2_1_weight_to_fp16, x = input_385_cast_fp16)[name = tensor<string, []>("xt_69_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_387_cast_fp16 = add(x = xt_69_cast_fp16, y = input_379_cast_fp16)[name = tensor<string, []>("input_387_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_389_cast_fp16 = leaky_relu(alpha = var_764, x = input_387_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
tensor<string, []> input_391_pad_type_0 = const()[name = tensor<string, []>("input_391_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> input_391_pad_0 = const()[name = tensor<string, []>("input_391_pad_0"), val = tensor<int32, [2]>([25, 25])];
tensor<int32, [1]> input_391_dilations_0 = const()[name = tensor<string, []>("input_391_dilations_0"), val = tensor<int32, [1]>([5])];
tensor<int32, [1]> input_391_strides_0 = const()[name = tensor<string, []>("input_391_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> input_391_groups_0 = const()[name = tensor<string, []>("input_391_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs1_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15145472)))];
tensor<fp16, [20]> dec_resblocks_11_convs1_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs1_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15154368)))];
tensor<fp16, [1, 20, 98304]> input_391_cast_fp16 = conv(bias = dec_resblocks_11_convs1_2_bias_to_fp16, dilations = input_391_dilations_0, groups = input_391_groups_0, pad = input_391_pad_0, pad_type = input_391_pad_type_0, strides = input_391_strides_0, weight = dec_resblocks_11_convs1_2_weight_to_fp16, x = input_389_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_393_cast_fp16 = leaky_relu(alpha = var_764, x = input_391_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
tensor<string, []> xt_pad_type_0 = const()[name = tensor<string, []>("xt_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> xt_pad_0 = const()[name = tensor<string, []>("xt_pad_0"), val = tensor<int32, [2]>([5, 5])];
tensor<int32, [1]> xt_strides_0 = const()[name = tensor<string, []>("xt_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> xt_dilations_0 = const()[name = tensor<string, []>("xt_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> xt_groups_0 = const()[name = tensor<string, []>("xt_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [20, 20, 11]> dec_resblocks_11_convs2_2_weight_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_2_weight_to_fp16"), val = tensor<fp16, [20, 20, 11]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15154496)))];
tensor<fp16, [20]> dec_resblocks_11_convs2_2_bias_to_fp16 = const()[name = tensor<string, []>("dec_resblocks_11_convs2_2_bias_to_fp16"), val = tensor<fp16, [20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15163392)))];
tensor<fp16, [1, 20, 98304]> xt_cast_fp16 = conv(bias = dec_resblocks_11_convs2_2_bias_to_fp16, dilations = xt_dilations_0, groups = xt_groups_0, pad = xt_pad_0, pad_type = xt_pad_type_0, strides = xt_strides_0, weight = dec_resblocks_11_convs2_2_weight_to_fp16, x = input_393_cast_fp16)[name = tensor<string, []>("xt_cast_fp16")];
tensor<fp16, [1, 20, 98304]> var_1611_cast_fp16 = add(x = xt_cast_fp16, y = input_387_cast_fp16)[name = tensor<string, []>("op_1611_cast_fp16")];
tensor<fp16, [1, 20, 98304]> xs_cast_fp16 = add(x = xs_21_cast_fp16, y = var_1611_cast_fp16)[name = tensor<string, []>("xs_cast_fp16")];
tensor<fp16, []> _inversed_input_395_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_input_395_y_0_to_fp16"), val = tensor<fp16, []>(0x1.554p-2)];
tensor<fp16, [1, 20, 98304]> _inversed_input_395_cast_fp16 = mul(x = xs_cast_fp16, y = _inversed_input_395_y_0_to_fp16)[name = tensor<string, []>("_inversed_input_395_cast_fp16")];
tensor<fp16, [1, 20, 98304]> input_cast_fp16 = leaky_relu(alpha = var_756, x = _inversed_input_395_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
tensor<string, []> x_pad_type_0 = const()[name = tensor<string, []>("x_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> x_pad_0 = const()[name = tensor<string, []>("x_pad_0"), val = tensor<int32, [2]>([3, 3])];
tensor<int32, [1]> x_strides_0 = const()[name = tensor<string, []>("x_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> x_dilations_0 = const()[name = tensor<string, []>("x_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> x_groups_0 = const()[name = tensor<string, []>("x_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [1, 20, 7]> dec_conv_post_weight_to_fp16 = const()[name = tensor<string, []>("dec_conv_post_weight_to_fp16"), val = tensor<fp16, [1, 20, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15163520)))];
tensor<fp16, [1, 1, 98304]> x_cast_fp16 = conv(dilations = x_dilations_0, groups = x_groups_0, pad = x_pad_0, pad_type = x_pad_type_0, strides = x_strides_0, weight = dec_conv_post_weight_to_fp16, x = input_cast_fp16)[name = tensor<string, []>("x_cast_fp16")];
tensor<fp16, [1, 1, 98304]> var_1622_cast_fp16 = tanh(x = x_cast_fp16)[name = tensor<string, []>("op_1622_cast_fp16")];
tensor<string, []> var_1622_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_1622_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
tensor<fp32, [1, 1, 98304]> audio = cast(dtype = var_1622_cast_fp16_to_fp32_dtype_0, x = var_1622_cast_fp16)[name = tensor<string, []>("cast_8")];
} -> (audio);
}