| program(1.0) |
| [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] |
| { |
| func main<ios15>(tensor<fp32, [1, 192, 192, 3]> input_1) { |
| tensor<int32, [4]> transpose_1_perm_0 = const()[name = tensor<string, []>("transpose_1_perm_0"), val = tensor<int32, [4]>([0, 3, 1, 2])]; |
| tensor<string, []> input_1_to_fp16_dtype_0 = const()[name = tensor<string, []>("input_1_to_fp16_dtype_0"), val = tensor<string, []>("fp16")]; |
| tensor<string, []> Conv2Dx_pad_type_0 = const()[name = tensor<string, []>("Conv2Dx_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> Conv2Dx_strides_0 = const()[name = tensor<string, []>("Conv2Dx_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> Conv2Dx_dilations_0 = const()[name = tensor<string, []>("Conv2Dx_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2Dx_groups_0 = const()[name = tensor<string, []>("Conv2Dx_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2Dx_pad_0 = const()[name = tensor<string, []>("Conv2Dx_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 3, 3, 3]> transpose_0_to_fp16 = const()[name = tensor<string, []>("transpose_0_to_fp16"), val = tensor<fp16, [16, 3, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; |
| tensor<fp16, [16]> const_75_to_fp16 = const()[name = tensor<string, []>("const_75_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1024)))]; |
| tensor<fp16, [1, 192, 192, 3]> input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor<string, []>("cast_5")]; |
| tensor<fp16, [1, 3, 192, 192]> transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor<string, []>("transpose_98")]; |
| tensor<fp16, [1, 16, 96, 96]> conv2d_1_cast_fp16 = conv(bias = const_75_to_fp16, dilations = Conv2Dx_dilations_0, groups = Conv2Dx_groups_0, pad = Conv2Dx_pad_0, pad_type = Conv2Dx_pad_type_0, strides = Conv2Dx_strides_0, weight = transpose_0_to_fp16, x = transpose_1_cast_fp16)[name = tensor<string, []>("conv2d_1_cast_fp16")]; |
| tensor<fp16, [16]> p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1152)))]; |
| tensor<fp16, [1, 16, 96, 96]> p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_1_cast_fp16)[name = tensor<string, []>("p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwisex_pad_type_0 = const()[name = tensor<string, []>("depthwisex_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwisex_strides_0 = const()[name = tensor<string, []>("depthwisex_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwisex_dilations_0 = const()[name = tensor<string, []>("depthwisex_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwisex_groups_0 = const()[name = tensor<string, []>("depthwisex_groups_0"), val = tensor<int32, []>(16)]; |
| tensor<int32, [4]> depthwisex_pad_0 = const()[name = tensor<string, []>("depthwisex_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 1, 3, 3]> transpose_2_to_fp16 = const()[name = tensor<string, []>("transpose_2_to_fp16"), val = tensor<fp16, [16, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1280)))]; |
| tensor<fp16, [1, 16, 96, 96]> depthwisex_cast_fp16 = conv(dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwisex_cast_fp16")]; |
| tensor<string, []> Conv2D_2x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_2x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_2x_strides_0 = const()[name = tensor<string, []>("Conv2D_2x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_2x_dilations_0 = const()[name = tensor<string, []>("Conv2D_2x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_2x_groups_0 = const()[name = tensor<string, []>("Conv2D_2x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_2x_pad_0 = const()[name = tensor<string, []>("Conv2D_2x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 16, 1, 1]> transpose_4_to_fp16 = const()[name = tensor<string, []>("transpose_4_to_fp16"), val = tensor<fp16, [16, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1664)))]; |
| tensor<fp16, [16]> const_76_to_fp16 = const()[name = tensor<string, []>("const_76_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2240)))]; |
| tensor<fp16, [1, 16, 96, 96]> conv2d_2_1_cast_fp16 = conv(bias = const_76_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_4_to_fp16, x = depthwisex_cast_fp16)[name = tensor<string, []>("conv2d_2_1_cast_fp16")]; |
| tensor<fp16, [1, 16, 96, 96]> add_1_cast_fp16 = add(x = p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_2_1_cast_fp16)[name = tensor<string, []>("add_1_cast_fp16")]; |
| tensor<fp16, [16]> p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2368)))]; |
| tensor<fp16, [1, 16, 96, 96]> p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_1_cast_fp16)[name = tensor<string, []>("p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_1x_pad_type_0 = const()[name = tensor<string, []>("depthwise_1x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_1x_strides_0 = const()[name = tensor<string, []>("depthwise_1x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_1x_dilations_0 = const()[name = tensor<string, []>("depthwise_1x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_1x_groups_0 = const()[name = tensor<string, []>("depthwise_1x_groups_0"), val = tensor<int32, []>(16)]; |
| tensor<int32, [4]> depthwise_1x_pad_0 = const()[name = tensor<string, []>("depthwise_1x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 1, 3, 3]> transpose_6_to_fp16 = const()[name = tensor<string, []>("transpose_6_to_fp16"), val = tensor<fp16, [16, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2496)))]; |
| tensor<fp16, [1, 16, 96, 96]> depthwise_1x_cast_fp16 = conv(dilations = depthwise_1x_dilations_0, groups = depthwise_1x_groups_0, pad = depthwise_1x_pad_0, pad_type = depthwise_1x_pad_type_0, strides = depthwise_1x_strides_0, weight = transpose_6_to_fp16, x = p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_1x_cast_fp16")]; |
| tensor<string, []> Conv2D_3x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_3x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_3x_strides_0 = const()[name = tensor<string, []>("Conv2D_3x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_3x_dilations_0 = const()[name = tensor<string, []>("Conv2D_3x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_3x_groups_0 = const()[name = tensor<string, []>("Conv2D_3x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_3x_pad_0 = const()[name = tensor<string, []>("Conv2D_3x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 16, 1, 1]> transpose_8_to_fp16 = const()[name = tensor<string, []>("transpose_8_to_fp16"), val = tensor<fp16, [16, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2880)))]; |
| tensor<fp16, [16]> const_77_to_fp16 = const()[name = tensor<string, []>("const_77_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3456)))]; |
| tensor<fp16, [1, 16, 96, 96]> conv2d_3_1_cast_fp16 = conv(bias = const_77_to_fp16, dilations = Conv2D_3x_dilations_0, groups = Conv2D_3x_groups_0, pad = Conv2D_3x_pad_0, pad_type = Conv2D_3x_pad_type_0, strides = Conv2D_3x_strides_0, weight = transpose_8_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor<string, []>("conv2d_3_1_cast_fp16")]; |
| tensor<fp16, [1, 16, 96, 96]> add_2_cast_fp16 = add(x = p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_3_1_cast_fp16)[name = tensor<string, []>("add_2_cast_fp16")]; |
| tensor<fp16, [16]> p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3584)))]; |
| tensor<fp16, [1, 16, 96, 96]> p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_2_cast_fp16)[name = tensor<string, []>("p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<int32, [2]> max_pool_0_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_0_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_0_strides_0 = const()[name = tensor<string, []>("max_pool_0_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_0_pad_type_0 = const()[name = tensor<string, []>("max_pool_0_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_0_pad_0 = const()[name = tensor<string, []>("max_pool_0_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_0_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_0_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 16, 48, 48]> max_pool_0_cast_fp16 = max_pool(ceil_mode = max_pool_0_ceil_mode_0, kernel_sizes = max_pool_0_kernel_sizes_0, pad = max_pool_0_pad_0, pad_type = max_pool_0_pad_type_0, strides = max_pool_0_strides_0, x = p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_0_cast_fp16")]; |
| tensor<string, []> depthwise_2x_pad_type_0 = const()[name = tensor<string, []>("depthwise_2x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_2x_strides_0 = const()[name = tensor<string, []>("depthwise_2x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_2x_dilations_0 = const()[name = tensor<string, []>("depthwise_2x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_2x_groups_0 = const()[name = tensor<string, []>("depthwise_2x_groups_0"), val = tensor<int32, []>(16)]; |
| tensor<int32, [4]> depthwise_2x_pad_0 = const()[name = tensor<string, []>("depthwise_2x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [16, 1, 3, 3]> transpose_11_to_fp16 = const()[name = tensor<string, []>("transpose_11_to_fp16"), val = tensor<fp16, [16, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3712)))]; |
| tensor<fp16, [1, 16, 48, 48]> depthwise_2x_cast_fp16 = conv(dilations = depthwise_2x_dilations_0, groups = depthwise_2x_groups_0, pad = depthwise_2x_pad_0, pad_type = depthwise_2x_pad_type_0, strides = depthwise_2x_strides_0, weight = transpose_11_to_fp16, x = p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_2x_cast_fp16")]; |
| tensor<string, []> pad_0_mode_0 = const()[name = tensor<string, []>("pad_0_mode_0"), val = tensor<string, []>("constant")]; |
| tensor<int32, [8]> const_32 = const()[name = tensor<string, []>("const_32"), val = tensor<int32, [8]>([0, 0, 0, 16, 0, 0, 0, 0])]; |
| tensor<fp16, []> const_3_to_fp16 = const()[name = tensor<string, []>("const_3_to_fp16"), val = tensor<fp16, []>(0x0p+0)]; |
| tensor<fp16, [1, 32, 48, 48]> pad_0_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = pad_0_mode_0, pad = const_32, x = max_pool_0_cast_fp16)[name = tensor<string, []>("pad_0_cast_fp16")]; |
| tensor<string, []> Conv2D_4x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_4x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_4x_strides_0 = const()[name = tensor<string, []>("Conv2D_4x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_4x_dilations_0 = const()[name = tensor<string, []>("Conv2D_4x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_4x_groups_0 = const()[name = tensor<string, []>("Conv2D_4x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_4x_pad_0 = const()[name = tensor<string, []>("Conv2D_4x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 16, 1, 1]> transpose_13_to_fp16 = const()[name = tensor<string, []>("transpose_13_to_fp16"), val = tensor<fp16, [32, 16, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4096)))]; |
| tensor<fp16, [32]> const_78_to_fp16 = const()[name = tensor<string, []>("const_78_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5184)))]; |
| tensor<fp16, [1, 32, 48, 48]> conv2d_4_1_cast_fp16 = conv(bias = const_78_to_fp16, dilations = Conv2D_4x_dilations_0, groups = Conv2D_4x_groups_0, pad = Conv2D_4x_pad_0, pad_type = Conv2D_4x_pad_type_0, strides = Conv2D_4x_strides_0, weight = transpose_13_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor<string, []>("conv2d_4_1_cast_fp16")]; |
| tensor<fp16, [1, 32, 48, 48]> add_3_cast_fp16 = add(x = pad_0_cast_fp16, y = conv2d_4_1_cast_fp16)[name = tensor<string, []>("add_3_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5312)))]; |
| tensor<fp16, [1, 32, 48, 48]> p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_3_cast_fp16)[name = tensor<string, []>("p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_3x_pad_type_0 = const()[name = tensor<string, []>("depthwise_3x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_3x_strides_0 = const()[name = tensor<string, []>("depthwise_3x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_3x_dilations_0 = const()[name = tensor<string, []>("depthwise_3x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_3x_groups_0 = const()[name = tensor<string, []>("depthwise_3x_groups_0"), val = tensor<int32, []>(32)]; |
| tensor<int32, [4]> depthwise_3x_pad_0 = const()[name = tensor<string, []>("depthwise_3x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_15_to_fp16 = const()[name = tensor<string, []>("transpose_15_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5440)))]; |
| tensor<fp16, [1, 32, 48, 48]> depthwise_3x_cast_fp16 = conv(dilations = depthwise_3x_dilations_0, groups = depthwise_3x_groups_0, pad = depthwise_3x_pad_0, pad_type = depthwise_3x_pad_type_0, strides = depthwise_3x_strides_0, weight = transpose_15_to_fp16, x = p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_3x_cast_fp16")]; |
| tensor<string, []> Conv2D_5x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_5x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_5x_strides_0 = const()[name = tensor<string, []>("Conv2D_5x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_5x_dilations_0 = const()[name = tensor<string, []>("Conv2D_5x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_5x_groups_0 = const()[name = tensor<string, []>("Conv2D_5x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_5x_pad_0 = const()[name = tensor<string, []>("Conv2D_5x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 32, 1, 1]> transpose_17_to_fp16 = const()[name = tensor<string, []>("transpose_17_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6080)))]; |
| tensor<fp16, [32]> const_79_to_fp16 = const()[name = tensor<string, []>("const_79_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8192)))]; |
| tensor<fp16, [1, 32, 48, 48]> conv2d_5_1_cast_fp16 = conv(bias = const_79_to_fp16, dilations = Conv2D_5x_dilations_0, groups = Conv2D_5x_groups_0, pad = Conv2D_5x_pad_0, pad_type = Conv2D_5x_pad_type_0, strides = Conv2D_5x_strides_0, weight = transpose_17_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor<string, []>("conv2d_5_1_cast_fp16")]; |
| tensor<fp16, [1, 32, 48, 48]> add_4_cast_fp16 = add(x = p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_5_1_cast_fp16)[name = tensor<string, []>("add_4_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8320)))]; |
| tensor<fp16, [1, 32, 48, 48]> p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_4_cast_fp16)[name = tensor<string, []>("p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_4x_pad_type_0 = const()[name = tensor<string, []>("depthwise_4x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_4x_strides_0 = const()[name = tensor<string, []>("depthwise_4x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_4x_dilations_0 = const()[name = tensor<string, []>("depthwise_4x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_4x_groups_0 = const()[name = tensor<string, []>("depthwise_4x_groups_0"), val = tensor<int32, []>(32)]; |
| tensor<int32, [4]> depthwise_4x_pad_0 = const()[name = tensor<string, []>("depthwise_4x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_19_to_fp16 = const()[name = tensor<string, []>("transpose_19_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8448)))]; |
| tensor<fp16, [1, 32, 48, 48]> depthwise_4x_cast_fp16 = conv(dilations = depthwise_4x_dilations_0, groups = depthwise_4x_groups_0, pad = depthwise_4x_pad_0, pad_type = depthwise_4x_pad_type_0, strides = depthwise_4x_strides_0, weight = transpose_19_to_fp16, x = p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_4x_cast_fp16")]; |
| tensor<string, []> Conv2D_6x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_6x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_6x_strides_0 = const()[name = tensor<string, []>("Conv2D_6x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_6x_dilations_0 = const()[name = tensor<string, []>("Conv2D_6x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_6x_groups_0 = const()[name = tensor<string, []>("Conv2D_6x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_6x_pad_0 = const()[name = tensor<string, []>("Conv2D_6x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 32, 1, 1]> transpose_21_to_fp16 = const()[name = tensor<string, []>("transpose_21_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9088)))]; |
| tensor<fp16, [32]> const_80_to_fp16 = const()[name = tensor<string, []>("const_80_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11200)))]; |
| tensor<fp16, [1, 32, 48, 48]> conv2d_6_1_cast_fp16 = conv(bias = const_80_to_fp16, dilations = Conv2D_6x_dilations_0, groups = Conv2D_6x_groups_0, pad = Conv2D_6x_pad_0, pad_type = Conv2D_6x_pad_type_0, strides = Conv2D_6x_strides_0, weight = transpose_21_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor<string, []>("conv2d_6_1_cast_fp16")]; |
| tensor<fp16, [1, 32, 48, 48]> add_5_cast_fp16 = add(x = p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_6_1_cast_fp16)[name = tensor<string, []>("add_5_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11328)))]; |
| tensor<fp16, [1, 32, 48, 48]> p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_5_cast_fp16)[name = tensor<string, []>("p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<int32, [2]> max_pool_1_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_1_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_1_strides_0 = const()[name = tensor<string, []>("max_pool_1_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_1_pad_type_0 = const()[name = tensor<string, []>("max_pool_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_1_pad_0 = const()[name = tensor<string, []>("max_pool_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_1_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_1_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 32, 24, 24]> max_pool_1_cast_fp16 = max_pool(ceil_mode = max_pool_1_ceil_mode_0, kernel_sizes = max_pool_1_kernel_sizes_0, pad = max_pool_1_pad_0, pad_type = max_pool_1_pad_type_0, strides = max_pool_1_strides_0, x = p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_1_cast_fp16")]; |
| tensor<string, []> depthwise_5x_pad_type_0 = const()[name = tensor<string, []>("depthwise_5x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_5x_strides_0 = const()[name = tensor<string, []>("depthwise_5x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_5x_dilations_0 = const()[name = tensor<string, []>("depthwise_5x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_5x_groups_0 = const()[name = tensor<string, []>("depthwise_5x_groups_0"), val = tensor<int32, []>(32)]; |
| tensor<int32, [4]> depthwise_5x_pad_0 = const()[name = tensor<string, []>("depthwise_5x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_24_to_fp16 = const()[name = tensor<string, []>("transpose_24_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11456)))]; |
| tensor<fp16, [1, 32, 24, 24]> depthwise_5x_cast_fp16 = conv(dilations = depthwise_5x_dilations_0, groups = depthwise_5x_groups_0, pad = depthwise_5x_pad_0, pad_type = depthwise_5x_pad_type_0, strides = depthwise_5x_strides_0, weight = transpose_24_to_fp16, x = p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_5x_cast_fp16")]; |
| tensor<string, []> pad_1_mode_0 = const()[name = tensor<string, []>("pad_1_mode_0"), val = tensor<string, []>("constant")]; |
| tensor<int32, [8]> const_43 = const()[name = tensor<string, []>("const_43"), val = tensor<int32, [8]>([0, 0, 0, 32, 0, 0, 0, 0])]; |
| tensor<fp16, []> const_7_to_fp16 = const()[name = tensor<string, []>("const_7_to_fp16"), val = tensor<fp16, []>(0x0p+0)]; |
| tensor<fp16, [1, 64, 24, 24]> pad_1_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = pad_1_mode_0, pad = const_43, x = max_pool_1_cast_fp16)[name = tensor<string, []>("pad_1_cast_fp16")]; |
| tensor<string, []> Conv2D_7x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_7x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_7x_strides_0 = const()[name = tensor<string, []>("Conv2D_7x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_7x_dilations_0 = const()[name = tensor<string, []>("Conv2D_7x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_7x_groups_0 = const()[name = tensor<string, []>("Conv2D_7x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_7x_pad_0 = const()[name = tensor<string, []>("Conv2D_7x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 32, 1, 1]> transpose_26_to_fp16 = const()[name = tensor<string, []>("transpose_26_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12096)))]; |
| tensor<fp16, [64]> const_81_to_fp16 = const()[name = tensor<string, []>("const_81_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16256)))]; |
| tensor<fp16, [1, 64, 24, 24]> conv2d_7_1_cast_fp16 = conv(bias = const_81_to_fp16, dilations = Conv2D_7x_dilations_0, groups = Conv2D_7x_groups_0, pad = Conv2D_7x_pad_0, pad_type = Conv2D_7x_pad_type_0, strides = Conv2D_7x_strides_0, weight = transpose_26_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor<string, []>("conv2d_7_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 24, 24]> add_6_cast_fp16 = add(x = pad_1_cast_fp16, y = conv2d_7_1_cast_fp16)[name = tensor<string, []>("add_6_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16448)))]; |
| tensor<fp16, [1, 64, 24, 24]> p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_6_cast_fp16)[name = tensor<string, []>("p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_6x_pad_type_0 = const()[name = tensor<string, []>("depthwise_6x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_6x_strides_0 = const()[name = tensor<string, []>("depthwise_6x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_6x_dilations_0 = const()[name = tensor<string, []>("depthwise_6x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_6x_groups_0 = const()[name = tensor<string, []>("depthwise_6x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_6x_pad_0 = const()[name = tensor<string, []>("depthwise_6x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_28_to_fp16 = const()[name = tensor<string, []>("transpose_28_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16640)))]; |
| tensor<fp16, [1, 64, 24, 24]> depthwise_6x_cast_fp16 = conv(dilations = depthwise_6x_dilations_0, groups = depthwise_6x_groups_0, pad = depthwise_6x_pad_0, pad_type = depthwise_6x_pad_type_0, strides = depthwise_6x_strides_0, weight = transpose_28_to_fp16, x = p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_6x_cast_fp16")]; |
| tensor<string, []> Conv2D_8x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_8x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_8x_strides_0 = const()[name = tensor<string, []>("Conv2D_8x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_8x_dilations_0 = const()[name = tensor<string, []>("Conv2D_8x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_8x_groups_0 = const()[name = tensor<string, []>("Conv2D_8x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_8x_pad_0 = const()[name = tensor<string, []>("Conv2D_8x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 64, 1, 1]> transpose_30_to_fp16 = const()[name = tensor<string, []>("transpose_30_to_fp16"), val = tensor<fp16, [64, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17856)))]; |
| tensor<fp16, [64]> const_82_to_fp16 = const()[name = tensor<string, []>("const_82_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26112)))]; |
| tensor<fp16, [1, 64, 24, 24]> conv2d_8_1_cast_fp16 = conv(bias = const_82_to_fp16, dilations = Conv2D_8x_dilations_0, groups = Conv2D_8x_groups_0, pad = Conv2D_8x_pad_0, pad_type = Conv2D_8x_pad_type_0, strides = Conv2D_8x_strides_0, weight = transpose_30_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor<string, []>("conv2d_8_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 24, 24]> add_7_cast_fp16 = add(x = p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_8_1_cast_fp16)[name = tensor<string, []>("add_7_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26304)))]; |
| tensor<fp16, [1, 64, 24, 24]> p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_7_cast_fp16)[name = tensor<string, []>("p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_7x_pad_type_0 = const()[name = tensor<string, []>("depthwise_7x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_7x_strides_0 = const()[name = tensor<string, []>("depthwise_7x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_7x_dilations_0 = const()[name = tensor<string, []>("depthwise_7x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_7x_groups_0 = const()[name = tensor<string, []>("depthwise_7x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_7x_pad_0 = const()[name = tensor<string, []>("depthwise_7x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_32_to_fp16 = const()[name = tensor<string, []>("transpose_32_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26496)))]; |
| tensor<fp16, [1, 64, 24, 24]> depthwise_7x_cast_fp16 = conv(dilations = depthwise_7x_dilations_0, groups = depthwise_7x_groups_0, pad = depthwise_7x_pad_0, pad_type = depthwise_7x_pad_type_0, strides = depthwise_7x_strides_0, weight = transpose_32_to_fp16, x = p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_7x_cast_fp16")]; |
| tensor<string, []> Conv2D_9x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_9x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_9x_strides_0 = const()[name = tensor<string, []>("Conv2D_9x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_9x_dilations_0 = const()[name = tensor<string, []>("Conv2D_9x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_9x_groups_0 = const()[name = tensor<string, []>("Conv2D_9x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_9x_pad_0 = const()[name = tensor<string, []>("Conv2D_9x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 64, 1, 1]> transpose_34_to_fp16 = const()[name = tensor<string, []>("transpose_34_to_fp16"), val = tensor<fp16, [64, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27712)))]; |
| tensor<fp16, [64]> const_83_to_fp16 = const()[name = tensor<string, []>("const_83_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35968)))]; |
| tensor<fp16, [1, 64, 24, 24]> conv2d_9_1_cast_fp16 = conv(bias = const_83_to_fp16, dilations = Conv2D_9x_dilations_0, groups = Conv2D_9x_groups_0, pad = Conv2D_9x_pad_0, pad_type = Conv2D_9x_pad_type_0, strides = Conv2D_9x_strides_0, weight = transpose_34_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor<string, []>("conv2d_9_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 24, 24]> add_8_cast_fp16 = add(x = p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_9_1_cast_fp16)[name = tensor<string, []>("add_8_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36160)))]; |
| tensor<fp16, [1, 64, 24, 24]> p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_8_cast_fp16)[name = tensor<string, []>("p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<int32, [2]> max_pool_2_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_2_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_2_strides_0 = const()[name = tensor<string, []>("max_pool_2_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_2_pad_type_0 = const()[name = tensor<string, []>("max_pool_2_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_2_pad_0 = const()[name = tensor<string, []>("max_pool_2_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_2_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_2_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 64, 12, 12]> max_pool_2_cast_fp16 = max_pool(ceil_mode = max_pool_2_ceil_mode_0, kernel_sizes = max_pool_2_kernel_sizes_0, pad = max_pool_2_pad_0, pad_type = max_pool_2_pad_type_0, strides = max_pool_2_strides_0, x = p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_2_cast_fp16")]; |
| tensor<string, []> depthwise_8x_pad_type_0 = const()[name = tensor<string, []>("depthwise_8x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_8x_strides_0 = const()[name = tensor<string, []>("depthwise_8x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_8x_dilations_0 = const()[name = tensor<string, []>("depthwise_8x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_8x_groups_0 = const()[name = tensor<string, []>("depthwise_8x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_8x_pad_0 = const()[name = tensor<string, []>("depthwise_8x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_37_to_fp16 = const()[name = tensor<string, []>("transpose_37_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36352)))]; |
| tensor<fp16, [1, 64, 12, 12]> depthwise_8x_cast_fp16 = conv(dilations = depthwise_8x_dilations_0, groups = depthwise_8x_groups_0, pad = depthwise_8x_pad_0, pad_type = depthwise_8x_pad_type_0, strides = depthwise_8x_strides_0, weight = transpose_37_to_fp16, x = p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_8x_cast_fp16")]; |
| tensor<string, []> pad_2_mode_0 = const()[name = tensor<string, []>("pad_2_mode_0"), val = tensor<string, []>("constant")]; |
| tensor<int32, [8]> const_50 = const()[name = tensor<string, []>("const_50"), val = tensor<int32, [8]>([0, 0, 0, 64, 0, 0, 0, 0])]; |
| tensor<fp16, []> const_11_to_fp16 = const()[name = tensor<string, []>("const_11_to_fp16"), val = tensor<fp16, []>(0x0p+0)]; |
| tensor<fp16, [1, 128, 12, 12]> pad_2_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = pad_2_mode_0, pad = const_50, x = max_pool_2_cast_fp16)[name = tensor<string, []>("pad_2_cast_fp16")]; |
| tensor<string, []> Conv2D_10x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_10x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_10x_strides_0 = const()[name = tensor<string, []>("Conv2D_10x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_10x_dilations_0 = const()[name = tensor<string, []>("Conv2D_10x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_10x_groups_0 = const()[name = tensor<string, []>("Conv2D_10x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_10x_pad_0 = const()[name = tensor<string, []>("Conv2D_10x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_39_to_fp16 = const()[name = tensor<string, []>("transpose_39_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37568)))]; |
| tensor<fp16, [128]> const_84_to_fp16 = const()[name = tensor<string, []>("const_84_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54016)))]; |
| tensor<fp16, [1, 128, 12, 12]> conv2d_10_1_cast_fp16 = conv(bias = const_84_to_fp16, dilations = Conv2D_10x_dilations_0, groups = Conv2D_10x_groups_0, pad = Conv2D_10x_pad_0, pad_type = Conv2D_10x_pad_type_0, strides = Conv2D_10x_strides_0, weight = transpose_39_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor<string, []>("conv2d_10_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 12, 12]> add_9_cast_fp16 = add(x = pad_2_cast_fp16, y = conv2d_10_1_cast_fp16)[name = tensor<string, []>("add_9_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54336)))]; |
| tensor<fp16, [1, 128, 12, 12]> p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_9_cast_fp16)[name = tensor<string, []>("p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_9x_pad_type_0 = const()[name = tensor<string, []>("depthwise_9x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_9x_strides_0 = const()[name = tensor<string, []>("depthwise_9x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_9x_dilations_0 = const()[name = tensor<string, []>("depthwise_9x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_9x_groups_0 = const()[name = tensor<string, []>("depthwise_9x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_9x_pad_0 = const()[name = tensor<string, []>("depthwise_9x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_41_to_fp16 = const()[name = tensor<string, []>("transpose_41_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54656)))]; |
| tensor<fp16, [1, 128, 12, 12]> depthwise_9x_cast_fp16 = conv(dilations = depthwise_9x_dilations_0, groups = depthwise_9x_groups_0, pad = depthwise_9x_pad_0, pad_type = depthwise_9x_pad_type_0, strides = depthwise_9x_strides_0, weight = transpose_41_to_fp16, x = p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_9x_cast_fp16")]; |
| tensor<string, []> Conv2D_11x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_11x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_11x_strides_0 = const()[name = tensor<string, []>("Conv2D_11x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_11x_dilations_0 = const()[name = tensor<string, []>("Conv2D_11x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_11x_groups_0 = const()[name = tensor<string, []>("Conv2D_11x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_11x_pad_0 = const()[name = tensor<string, []>("Conv2D_11x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_43_to_fp16 = const()[name = tensor<string, []>("transpose_43_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57024)))]; |
| tensor<fp16, [128]> const_85_to_fp16 = const()[name = tensor<string, []>("const_85_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(89856)))]; |
| tensor<fp16, [1, 128, 12, 12]> conv2d_11_1_cast_fp16 = conv(bias = const_85_to_fp16, dilations = Conv2D_11x_dilations_0, groups = Conv2D_11x_groups_0, pad = Conv2D_11x_pad_0, pad_type = Conv2D_11x_pad_type_0, strides = Conv2D_11x_strides_0, weight = transpose_43_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor<string, []>("conv2d_11_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 12, 12]> add_10_cast_fp16 = add(x = p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_11_1_cast_fp16)[name = tensor<string, []>("add_10_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90176)))]; |
| tensor<fp16, [1, 128, 12, 12]> p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_10_cast_fp16)[name = tensor<string, []>("p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_10x_pad_type_0 = const()[name = tensor<string, []>("depthwise_10x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_10x_strides_0 = const()[name = tensor<string, []>("depthwise_10x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_10x_dilations_0 = const()[name = tensor<string, []>("depthwise_10x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_10x_groups_0 = const()[name = tensor<string, []>("depthwise_10x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_10x_pad_0 = const()[name = tensor<string, []>("depthwise_10x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_45_to_fp16 = const()[name = tensor<string, []>("transpose_45_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90496)))]; |
| tensor<fp16, [1, 128, 12, 12]> depthwise_10x_cast_fp16 = conv(dilations = depthwise_10x_dilations_0, groups = depthwise_10x_groups_0, pad = depthwise_10x_pad_0, pad_type = depthwise_10x_pad_type_0, strides = depthwise_10x_strides_0, weight = transpose_45_to_fp16, x = p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_10x_cast_fp16")]; |
| tensor<string, []> Conv2D_12x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_12x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_12x_strides_0 = const()[name = tensor<string, []>("Conv2D_12x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_12x_dilations_0 = const()[name = tensor<string, []>("Conv2D_12x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_12x_groups_0 = const()[name = tensor<string, []>("Conv2D_12x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_12x_pad_0 = const()[name = tensor<string, []>("Conv2D_12x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_47_to_fp16 = const()[name = tensor<string, []>("transpose_47_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92864)))]; |
| tensor<fp16, [128]> const_86_to_fp16 = const()[name = tensor<string, []>("const_86_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125696)))]; |
| tensor<fp16, [1, 128, 12, 12]> conv2d_12_1_cast_fp16 = conv(bias = const_86_to_fp16, dilations = Conv2D_12x_dilations_0, groups = Conv2D_12x_groups_0, pad = Conv2D_12x_pad_0, pad_type = Conv2D_12x_pad_type_0, strides = Conv2D_12x_strides_0, weight = transpose_47_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor<string, []>("conv2d_12_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 12, 12]> add_11_cast_fp16 = add(x = p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_12_1_cast_fp16)[name = tensor<string, []>("add_11_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126016)))]; |
| tensor<fp16, [1, 128, 12, 12]> p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_11_cast_fp16)[name = tensor<string, []>("p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<int32, [2]> max_pool_3_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_3_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_3_strides_0 = const()[name = tensor<string, []>("max_pool_3_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_3_pad_type_0 = const()[name = tensor<string, []>("max_pool_3_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_3_pad_0 = const()[name = tensor<string, []>("max_pool_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_3_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_3_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 128, 6, 6]> max_pool_3_cast_fp16 = max_pool(ceil_mode = max_pool_3_ceil_mode_0, kernel_sizes = max_pool_3_kernel_sizes_0, pad = max_pool_3_pad_0, pad_type = max_pool_3_pad_type_0, strides = max_pool_3_strides_0, x = p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_3_cast_fp16")]; |
| tensor<string, []> depthwise_11x_pad_type_0 = const()[name = tensor<string, []>("depthwise_11x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_11x_strides_0 = const()[name = tensor<string, []>("depthwise_11x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_11x_dilations_0 = const()[name = tensor<string, []>("depthwise_11x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_11x_groups_0 = const()[name = tensor<string, []>("depthwise_11x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_11x_pad_0 = const()[name = tensor<string, []>("depthwise_11x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_50_to_fp16 = const()[name = tensor<string, []>("transpose_50_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126336)))]; |
| tensor<fp16, [1, 128, 6, 6]> depthwise_11x_cast_fp16 = conv(dilations = depthwise_11x_dilations_0, groups = depthwise_11x_groups_0, pad = depthwise_11x_pad_0, pad_type = depthwise_11x_pad_type_0, strides = depthwise_11x_strides_0, weight = transpose_50_to_fp16, x = p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_11x_cast_fp16")]; |
| tensor<string, []> Conv2D_13x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_13x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_13x_strides_0 = const()[name = tensor<string, []>("Conv2D_13x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_13x_dilations_0 = const()[name = tensor<string, []>("Conv2D_13x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_13x_groups_0 = const()[name = tensor<string, []>("Conv2D_13x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_13x_pad_0 = const()[name = tensor<string, []>("Conv2D_13x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_52_to_fp16 = const()[name = tensor<string, []>("transpose_52_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128704)))]; |
| tensor<fp16, [128]> const_87_to_fp16 = const()[name = tensor<string, []>("const_87_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161536)))]; |
| tensor<fp16, [1, 128, 6, 6]> conv2d_13_1_cast_fp16 = conv(bias = const_87_to_fp16, dilations = Conv2D_13x_dilations_0, groups = Conv2D_13x_groups_0, pad = Conv2D_13x_pad_0, pad_type = Conv2D_13x_pad_type_0, strides = Conv2D_13x_strides_0, weight = transpose_52_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor<string, []>("conv2d_13_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 6, 6]> add_12_cast_fp16 = add(x = max_pool_3_cast_fp16, y = conv2d_13_1_cast_fp16)[name = tensor<string, []>("add_12_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161856)))]; |
| tensor<fp16, [1, 128, 6, 6]> p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_12_cast_fp16)[name = tensor<string, []>("p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_12x_pad_type_0 = const()[name = tensor<string, []>("depthwise_12x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_12x_strides_0 = const()[name = tensor<string, []>("depthwise_12x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_12x_dilations_0 = const()[name = tensor<string, []>("depthwise_12x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_12x_groups_0 = const()[name = tensor<string, []>("depthwise_12x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_12x_pad_0 = const()[name = tensor<string, []>("depthwise_12x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_54_to_fp16 = const()[name = tensor<string, []>("transpose_54_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162176)))]; |
| tensor<fp16, [1, 128, 6, 6]> depthwise_12x_cast_fp16 = conv(dilations = depthwise_12x_dilations_0, groups = depthwise_12x_groups_0, pad = depthwise_12x_pad_0, pad_type = depthwise_12x_pad_type_0, strides = depthwise_12x_strides_0, weight = transpose_54_to_fp16, x = p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_12x_cast_fp16")]; |
| tensor<string, []> Conv2D_14x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_14x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_14x_strides_0 = const()[name = tensor<string, []>("Conv2D_14x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_14x_dilations_0 = const()[name = tensor<string, []>("Conv2D_14x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_14x_groups_0 = const()[name = tensor<string, []>("Conv2D_14x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_14x_pad_0 = const()[name = tensor<string, []>("Conv2D_14x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_56_to_fp16 = const()[name = tensor<string, []>("transpose_56_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164544)))]; |
| tensor<fp16, [128]> const_88_to_fp16 = const()[name = tensor<string, []>("const_88_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197376)))]; |
| tensor<fp16, [1, 128, 6, 6]> conv2d_14_1_cast_fp16 = conv(bias = const_88_to_fp16, dilations = Conv2D_14x_dilations_0, groups = Conv2D_14x_groups_0, pad = Conv2D_14x_pad_0, pad_type = Conv2D_14x_pad_type_0, strides = Conv2D_14x_strides_0, weight = transpose_56_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor<string, []>("conv2d_14_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 6, 6]> add_13_cast_fp16 = add(x = p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_14_1_cast_fp16)[name = tensor<string, []>("add_13_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197696)))]; |
| tensor<fp16, [1, 128, 6, 6]> p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_13_cast_fp16)[name = tensor<string, []>("p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_13x_pad_type_0 = const()[name = tensor<string, []>("depthwise_13x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_13x_strides_0 = const()[name = tensor<string, []>("depthwise_13x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_13x_dilations_0 = const()[name = tensor<string, []>("depthwise_13x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_13x_groups_0 = const()[name = tensor<string, []>("depthwise_13x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_13x_pad_0 = const()[name = tensor<string, []>("depthwise_13x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_58_to_fp16 = const()[name = tensor<string, []>("transpose_58_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198016)))]; |
| tensor<fp16, [1, 128, 6, 6]> depthwise_13x_cast_fp16 = conv(dilations = depthwise_13x_dilations_0, groups = depthwise_13x_groups_0, pad = depthwise_13x_pad_0, pad_type = depthwise_13x_pad_type_0, strides = depthwise_13x_strides_0, weight = transpose_58_to_fp16, x = p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_13x_cast_fp16")]; |
| tensor<string, []> Conv2D_15x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_15x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_15x_strides_0 = const()[name = tensor<string, []>("Conv2D_15x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_15x_dilations_0 = const()[name = tensor<string, []>("Conv2D_15x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_15x_groups_0 = const()[name = tensor<string, []>("Conv2D_15x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_15x_pad_0 = const()[name = tensor<string, []>("Conv2D_15x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_60_to_fp16 = const()[name = tensor<string, []>("transpose_60_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200384)))]; |
| tensor<fp16, [128]> const_89_to_fp16 = const()[name = tensor<string, []>("const_89_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233216)))]; |
| tensor<fp16, [1, 128, 6, 6]> conv2d_15_1_cast_fp16 = conv(bias = const_89_to_fp16, dilations = Conv2D_15x_dilations_0, groups = Conv2D_15x_groups_0, pad = Conv2D_15x_pad_0, pad_type = Conv2D_15x_pad_type_0, strides = Conv2D_15x_strides_0, weight = transpose_60_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor<string, []>("conv2d_15_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 6, 6]> add_14_cast_fp16 = add(x = p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_15_1_cast_fp16)[name = tensor<string, []>("add_14_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233536)))]; |
| tensor<fp16, [1, 128, 6, 6]> p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_14_cast_fp16)[name = tensor<string, []>("p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<int32, [2]> max_pool_4_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_4_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_4_strides_0 = const()[name = tensor<string, []>("max_pool_4_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_4_pad_type_0 = const()[name = tensor<string, []>("max_pool_4_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_4_pad_0 = const()[name = tensor<string, []>("max_pool_4_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_4_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_4_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 128, 3, 3]> max_pool_4_cast_fp16 = max_pool(ceil_mode = max_pool_4_ceil_mode_0, kernel_sizes = max_pool_4_kernel_sizes_0, pad = max_pool_4_pad_0, pad_type = max_pool_4_pad_type_0, strides = max_pool_4_strides_0, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_4_cast_fp16")]; |
| tensor<string, []> depthwise_14x_pad_type_0 = const()[name = tensor<string, []>("depthwise_14x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_14x_strides_0 = const()[name = tensor<string, []>("depthwise_14x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_14x_dilations_0 = const()[name = tensor<string, []>("depthwise_14x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_14x_groups_0 = const()[name = tensor<string, []>("depthwise_14x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_14x_pad_0 = const()[name = tensor<string, []>("depthwise_14x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_63_to_fp16 = const()[name = tensor<string, []>("transpose_63_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233856)))]; |
| tensor<fp16, [1, 128, 3, 3]> depthwise_14x_cast_fp16 = conv(dilations = depthwise_14x_dilations_0, groups = depthwise_14x_groups_0, pad = depthwise_14x_pad_0, pad_type = depthwise_14x_pad_type_0, strides = depthwise_14x_strides_0, weight = transpose_63_to_fp16, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_14x_cast_fp16")]; |
| tensor<string, []> depthwise_16x_pad_type_0 = const()[name = tensor<string, []>("depthwise_16x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_16x_strides_0 = const()[name = tensor<string, []>("depthwise_16x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> depthwise_16x_dilations_0 = const()[name = tensor<string, []>("depthwise_16x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_16x_groups_0 = const()[name = tensor<string, []>("depthwise_16x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_16x_pad_0 = const()[name = tensor<string, []>("depthwise_16x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_66_to_fp16 = const()[name = tensor<string, []>("transpose_66_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(236224)))]; |
| tensor<fp16, [1, 128, 3, 3]> depthwise_16x_cast_fp16 = conv(dilations = depthwise_16x_dilations_0, groups = depthwise_16x_groups_0, pad = depthwise_16x_pad_0, pad_type = depthwise_16x_pad_type_0, strides = depthwise_16x_strides_0, weight = transpose_66_to_fp16, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_16x_cast_fp16")]; |
| tensor<string, []> Conv2D_16x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_16x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_16x_strides_0 = const()[name = tensor<string, []>("Conv2D_16x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_16x_dilations_0 = const()[name = tensor<string, []>("Conv2D_16x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_16x_groups_0 = const()[name = tensor<string, []>("Conv2D_16x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_16x_pad_0 = const()[name = tensor<string, []>("Conv2D_16x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_68_to_fp16 = const()[name = tensor<string, []>("transpose_68_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(238592)))]; |
| tensor<fp16, [128]> const_90_to_fp16 = const()[name = tensor<string, []>("const_90_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271424)))]; |
| tensor<fp16, [1, 128, 3, 3]> conv2d_16_1_cast_fp16 = conv(bias = const_90_to_fp16, dilations = Conv2D_16x_dilations_0, groups = Conv2D_16x_groups_0, pad = Conv2D_16x_pad_0, pad_type = Conv2D_16x_pad_type_0, strides = Conv2D_16x_strides_0, weight = transpose_68_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor<string, []>("conv2d_16_1_cast_fp16")]; |
| tensor<string, []> Conv2D_18x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_18x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_18x_strides_0 = const()[name = tensor<string, []>("Conv2D_18x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_18x_dilations_0 = const()[name = tensor<string, []>("Conv2D_18x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_18x_groups_0 = const()[name = tensor<string, []>("Conv2D_18x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_18x_pad_0 = const()[name = tensor<string, []>("Conv2D_18x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_70_to_fp16 = const()[name = tensor<string, []>("transpose_70_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271744)))]; |
| tensor<fp16, [128]> const_91_to_fp16 = const()[name = tensor<string, []>("const_91_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(304576)))]; |
| tensor<fp16, [1, 128, 3, 3]> conv2d_28_cast_fp16 = conv(bias = const_91_to_fp16, dilations = Conv2D_18x_dilations_0, groups = Conv2D_18x_groups_0, pad = Conv2D_18x_pad_0, pad_type = Conv2D_18x_pad_type_0, strides = Conv2D_18x_strides_0, weight = transpose_70_to_fp16, x = depthwise_16x_cast_fp16)[name = tensor<string, []>("conv2d_28_cast_fp16")]; |
| tensor<fp16, [1, 128, 3, 3]> add_15_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_16_1_cast_fp16)[name = tensor<string, []>("add_15_cast_fp16")]; |
| tensor<fp16, [1, 128, 3, 3]> add_23_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_28_cast_fp16)[name = tensor<string, []>("add_23_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(304896)))]; |
| tensor<fp16, [1, 128, 3, 3]> p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_15_cast_fp16)[name = tensor<string, []>("p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(305216)))]; |
| tensor<fp16, [1, 128, 3, 3]> p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_23_cast_fp16)[name = tensor<string, []>("p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_15x_pad_type_0 = const()[name = tensor<string, []>("depthwise_15x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_15x_strides_0 = const()[name = tensor<string, []>("depthwise_15x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_15x_dilations_0 = const()[name = tensor<string, []>("depthwise_15x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_15x_groups_0 = const()[name = tensor<string, []>("depthwise_15x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_15x_pad_0 = const()[name = tensor<string, []>("depthwise_15x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_72_to_fp16 = const()[name = tensor<string, []>("transpose_72_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(305536)))]; |
| tensor<fp16, [1, 128, 3, 3]> depthwise_15x_cast_fp16 = conv(dilations = depthwise_15x_dilations_0, groups = depthwise_15x_groups_0, pad = depthwise_15x_pad_0, pad_type = depthwise_15x_pad_type_0, strides = depthwise_15x_strides_0, weight = transpose_72_to_fp16, x = p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_15x_cast_fp16")]; |
| tensor<string, []> Conv2D_20x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_20x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_20x_strides_0 = const()[name = tensor<string, []>("Conv2D_20x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_20x_dilations_0 = const()[name = tensor<string, []>("Conv2D_20x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_20x_groups_0 = const()[name = tensor<string, []>("Conv2D_20x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_20x_pad_0 = const()[name = tensor<string, []>("Conv2D_20x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 128, 1, 1]> transpose_74_to_fp16 = const()[name = tensor<string, []>("transpose_74_to_fp16"), val = tensor<fp16, [32, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(307904)))]; |
| tensor<fp16, [32]> const_92_to_fp16 = const()[name = tensor<string, []>("const_92_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(316160)))]; |
| tensor<fp16, [1, 32, 3, 3]> conv2d_29_cast_fp16 = conv(bias = const_92_to_fp16, dilations = Conv2D_20x_dilations_0, groups = Conv2D_20x_groups_0, pad = Conv2D_20x_pad_0, pad_type = Conv2D_20x_pad_type_0, strides = Conv2D_20x_strides_0, weight = transpose_74_to_fp16, x = p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_29_cast_fp16")]; |
| tensor<string, []> Conv2D_17x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_17x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_17x_strides_0 = const()[name = tensor<string, []>("Conv2D_17x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_17x_dilations_0 = const()[name = tensor<string, []>("Conv2D_17x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_17x_groups_0 = const()[name = tensor<string, []>("Conv2D_17x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_17x_pad_0 = const()[name = tensor<string, []>("Conv2D_17x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_76_to_fp16 = const()[name = tensor<string, []>("transpose_76_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(316288)))]; |
| tensor<fp16, [128]> const_93_to_fp16 = const()[name = tensor<string, []>("const_93_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349120)))]; |
| tensor<fp16, [1, 128, 3, 3]> conv2d_17_1_cast_fp16 = conv(bias = const_93_to_fp16, dilations = Conv2D_17x_dilations_0, groups = Conv2D_17x_groups_0, pad = Conv2D_17x_pad_0, pad_type = Conv2D_17x_pad_type_0, strides = Conv2D_17x_strides_0, weight = transpose_76_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor<string, []>("conv2d_17_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 3, 3]> add_16_cast_fp16 = add(x = p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_17_1_cast_fp16)[name = tensor<string, []>("add_16_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349440)))]; |
| tensor<fp16, [1, 32, 3, 3]> p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_29_cast_fp16)[name = tensor<string, []>("p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_18x_pad_type_0 = const()[name = tensor<string, []>("depthwise_18x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_18x_strides_0 = const()[name = tensor<string, []>("depthwise_18x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_18x_dilations_0 = const()[name = tensor<string, []>("depthwise_18x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_18x_groups_0 = const()[name = tensor<string, []>("depthwise_18x_groups_0"), val = tensor<int32, []>(32)]; |
| tensor<int32, [4]> depthwise_18x_pad_0 = const()[name = tensor<string, []>("depthwise_18x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_78_to_fp16 = const()[name = tensor<string, []>("transpose_78_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349568)))]; |
| tensor<fp16, [1, 32, 3, 3]> depthwise_18x_cast_fp16 = conv(dilations = depthwise_18x_dilations_0, groups = depthwise_18x_groups_0, pad = depthwise_18x_pad_0, pad_type = depthwise_18x_pad_type_0, strides = depthwise_18x_strides_0, weight = transpose_78_to_fp16, x = p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_18x_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(350208)))]; |
| tensor<fp16, [1, 128, 3, 3]> p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_16_cast_fp16)[name = tensor<string, []>("p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_22x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_22x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_22x_strides_0 = const()[name = tensor<string, []>("Conv2D_22x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_22x_dilations_0 = const()[name = tensor<string, []>("Conv2D_22x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_22x_groups_0 = const()[name = tensor<string, []>("Conv2D_22x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_22x_pad_0 = const()[name = tensor<string, []>("Conv2D_22x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 32, 1, 1]> transpose_80_to_fp16 = const()[name = tensor<string, []>("transpose_80_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(350528)))]; |
| tensor<fp16, [32]> const_94_to_fp16 = const()[name = tensor<string, []>("const_94_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352640)))]; |
| tensor<fp16, [1, 32, 3, 3]> conv2d_30_cast_fp16 = conv(bias = const_94_to_fp16, dilations = Conv2D_22x_dilations_0, groups = Conv2D_22x_groups_0, pad = Conv2D_22x_pad_0, pad_type = Conv2D_22x_pad_type_0, strides = Conv2D_22x_strides_0, weight = transpose_80_to_fp16, x = depthwise_18x_cast_fp16)[name = tensor<string, []>("conv2d_30_cast_fp16")]; |
| tensor<string, []> depthwise_17x_pad_type_0 = const()[name = tensor<string, []>("depthwise_17x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_17x_strides_0 = const()[name = tensor<string, []>("depthwise_17x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_17x_dilations_0 = const()[name = tensor<string, []>("depthwise_17x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_17x_groups_0 = const()[name = tensor<string, []>("depthwise_17x_groups_0"), val = tensor<int32, []>(128)]; |
| tensor<int32, [4]> depthwise_17x_pad_0 = const()[name = tensor<string, []>("depthwise_17x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 1, 3, 3]> transpose_82_to_fp16 = const()[name = tensor<string, []>("transpose_82_to_fp16"), val = tensor<fp16, [128, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352768)))]; |
| tensor<fp16, [1, 128, 3, 3]> depthwise_17x_cast_fp16 = conv(dilations = depthwise_17x_dilations_0, groups = depthwise_17x_groups_0, pad = depthwise_17x_pad_0, pad_type = depthwise_17x_pad_type_0, strides = depthwise_17x_strides_0, weight = transpose_82_to_fp16, x = p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_17x_cast_fp16")]; |
| tensor<string, []> Conv2D_19x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_19x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_19x_strides_0 = const()[name = tensor<string, []>("Conv2D_19x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_19x_dilations_0 = const()[name = tensor<string, []>("Conv2D_19x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_19x_groups_0 = const()[name = tensor<string, []>("Conv2D_19x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_19x_pad_0 = const()[name = tensor<string, []>("Conv2D_19x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 128, 1, 1]> transpose_84_to_fp16 = const()[name = tensor<string, []>("transpose_84_to_fp16"), val = tensor<fp16, [128, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(355136)))]; |
| tensor<fp16, [128]> const_95_to_fp16 = const()[name = tensor<string, []>("const_95_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387968)))]; |
| tensor<fp16, [1, 128, 3, 3]> conv2d_18_1_cast_fp16 = conv(bias = const_95_to_fp16, dilations = Conv2D_19x_dilations_0, groups = Conv2D_19x_groups_0, pad = Conv2D_19x_pad_0, pad_type = Conv2D_19x_pad_type_0, strides = Conv2D_19x_strides_0, weight = transpose_84_to_fp16, x = depthwise_17x_cast_fp16)[name = tensor<string, []>("conv2d_18_1_cast_fp16")]; |
| tensor<fp16, [1, 32, 3, 3]> add_24_cast_fp16 = add(x = p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_30_cast_fp16)[name = tensor<string, []>("add_24_cast_fp16")]; |
| tensor<fp16, [1, 128, 3, 3]> add_17_cast_fp16 = add(x = p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_18_1_cast_fp16)[name = tensor<string, []>("add_17_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388288)))]; |
| tensor<fp16, [1, 32, 3, 3]> p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_24_cast_fp16)[name = tensor<string, []>("p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_24x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_24x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_24x_strides_0 = const()[name = tensor<string, []>("Conv2D_24x_strides_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [2]> Conv2D_24x_dilations_0 = const()[name = tensor<string, []>("Conv2D_24x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_24x_groups_0 = const()[name = tensor<string, []>("Conv2D_24x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_24x_pad_0 = const()[name = tensor<string, []>("Conv2D_24x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [1, 32, 3, 3]> conv_0_weight_0_to_fp16 = const()[name = tensor<string, []>("conv_0_weight_0_to_fp16"), val = tensor<fp16, [1, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388416)))]; |
| tensor<fp16, [1]> conv_0_bias_0_to_fp16 = const()[name = tensor<string, []>("conv_0_bias_0_to_fp16"), val = tensor<fp16, [1]>([-0x1.36cp-2])]; |
| tensor<fp16, [1, 1, 1, 1]> conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, dilations = Conv2D_24x_dilations_0, groups = Conv2D_24x_groups_0, pad = Conv2D_24x_pad_0, pad_type = Conv2D_24x_pad_type_0, strides = Conv2D_24x_strides_0, weight = conv_0_weight_0_to_fp16, x = p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv_0_cast_fp16")]; |
| tensor<int32, [4]> Conv2D_24_perm_0 = const()[name = tensor<string, []>("Conv2D_24_perm_0"), val = tensor<int32, [4]>([0, 2, 3, 1])]; |
| tensor<string, []> conv2d_31_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("conv2d_31_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")]; |
| tensor<fp16, [128]> p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389056)))]; |
| tensor<fp16, [1, 128, 3, 3]> p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_17_cast_fp16)[name = tensor<string, []>("p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_21x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_21x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_21x_strides_0 = const()[name = tensor<string, []>("Conv2D_21x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_21x_dilations_0 = const()[name = tensor<string, []>("Conv2D_21x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_21x_groups_0 = const()[name = tensor<string, []>("Conv2D_21x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_21x_pad_0 = const()[name = tensor<string, []>("Conv2D_21x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 128, 1, 1]> transpose_88_to_fp16 = const()[name = tensor<string, []>("transpose_88_to_fp16"), val = tensor<fp16, [32, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389376)))]; |
| tensor<fp16, [32]> const_96_to_fp16 = const()[name = tensor<string, []>("const_96_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397632)))]; |
| tensor<fp16, [1, 32, 3, 3]> conv2d_19_1_cast_fp16 = conv(bias = const_96_to_fp16, dilations = Conv2D_21x_dilations_0, groups = Conv2D_21x_groups_0, pad = Conv2D_21x_pad_0, pad_type = Conv2D_21x_pad_type_0, strides = Conv2D_21x_strides_0, weight = transpose_88_to_fp16, x = p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_19_1_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397760)))]; |
| tensor<fp16, [1, 32, 3, 3]> p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_19_1_cast_fp16)[name = tensor<string, []>("p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_19x_pad_type_0 = const()[name = tensor<string, []>("depthwise_19x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_19x_strides_0 = const()[name = tensor<string, []>("depthwise_19x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_19x_dilations_0 = const()[name = tensor<string, []>("depthwise_19x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_19x_groups_0 = const()[name = tensor<string, []>("depthwise_19x_groups_0"), val = tensor<int32, []>(32)]; |
| tensor<int32, [4]> depthwise_19x_pad_0 = const()[name = tensor<string, []>("depthwise_19x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_90_to_fp16 = const()[name = tensor<string, []>("transpose_90_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397888)))]; |
| tensor<fp16, [1, 32, 3, 3]> depthwise_19x_cast_fp16 = conv(dilations = depthwise_19x_dilations_0, groups = depthwise_19x_groups_0, pad = depthwise_19x_pad_0, pad_type = depthwise_19x_pad_type_0, strides = depthwise_19x_strides_0, weight = transpose_90_to_fp16, x = p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_19x_cast_fp16")]; |
| tensor<string, []> Conv2D_23x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_23x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_23x_strides_0 = const()[name = tensor<string, []>("Conv2D_23x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_23x_dilations_0 = const()[name = tensor<string, []>("Conv2D_23x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_23x_groups_0 = const()[name = tensor<string, []>("Conv2D_23x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_23x_pad_0 = const()[name = tensor<string, []>("Conv2D_23x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 32, 1, 1]> transpose_92_to_fp16 = const()[name = tensor<string, []>("transpose_92_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(398528)))]; |
| tensor<fp16, [32]> const_97_to_fp16 = const()[name = tensor<string, []>("const_97_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(400640)))]; |
| tensor<fp16, [1, 32, 3, 3]> conv2d_20_1_cast_fp16 = conv(bias = const_97_to_fp16, dilations = Conv2D_23x_dilations_0, groups = Conv2D_23x_groups_0, pad = Conv2D_23x_pad_0, pad_type = Conv2D_23x_pad_type_0, strides = Conv2D_23x_strides_0, weight = transpose_92_to_fp16, x = depthwise_19x_cast_fp16)[name = tensor<string, []>("conv2d_20_1_cast_fp16")]; |
| tensor<fp16, [1, 32, 3, 3]> add_18_cast_fp16 = add(x = p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_20_1_cast_fp16)[name = tensor<string, []>("add_18_cast_fp16")]; |
| tensor<fp16, [32]> p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(400768)))]; |
| tensor<fp16, [1, 32, 3, 3]> p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_18_cast_fp16)[name = tensor<string, []>("p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_25x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_25x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_25x_strides_0 = const()[name = tensor<string, []>("Conv2D_25x_strides_0"), val = tensor<int32, [2]>([3, 3])]; |
| tensor<int32, [2]> Conv2D_25x_dilations_0 = const()[name = tensor<string, []>("Conv2D_25x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_25x_groups_0 = const()[name = tensor<string, []>("Conv2D_25x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_25x_pad_0 = const()[name = tensor<string, []>("Conv2D_25x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [1404, 32, 3, 3]> conv_1_weight_0_to_fp16 = const()[name = tensor<string, []>("conv_1_weight_0_to_fp16"), val = tensor<fp16, [1404, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(400896)))]; |
| tensor<fp16, [1404]> conv_1_bias_0_to_fp16 = const()[name = tensor<string, []>("conv_1_bias_0_to_fp16"), val = tensor<fp16, [1404]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1209664)))]; |
| tensor<fp16, [1, 1404, 1, 1]> conv_1_cast_fp16 = conv(bias = conv_1_bias_0_to_fp16, dilations = Conv2D_25x_dilations_0, groups = Conv2D_25x_groups_0, pad = Conv2D_25x_pad_0, pad_type = Conv2D_25x_pad_type_0, strides = Conv2D_25x_strides_0, weight = conv_1_weight_0_to_fp16, x = p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv_1_cast_fp16")]; |
| tensor<int32, [4]> Conv2D_25_perm_0 = const()[name = tensor<string, []>("Conv2D_25_perm_0"), val = tensor<int32, [4]>([0, 2, 3, 1])]; |
| tensor<string, []> conv2d_21_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("conv2d_21_1_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")]; |
| tensor<fp16, [1, 1, 1, 1404]> conv2d_21_1_cast_fp16 = transpose(perm = Conv2D_25_perm_0, x = conv_1_cast_fp16)[name = tensor<string, []>("transpose_96")]; |
| tensor<fp32, [1, 1, 1, 1404]> conv2d_21_1 = cast(dtype = conv2d_21_1_cast_fp16_to_fp32_dtype_0, x = conv2d_21_1_cast_fp16)[name = tensor<string, []>("cast_3")]; |
| tensor<fp16, [1, 1, 1, 1]> conv2d_31_cast_fp16 = transpose(perm = Conv2D_24_perm_0, x = conv_0_cast_fp16)[name = tensor<string, []>("transpose_97")]; |
| tensor<fp32, [1, 1, 1, 1]> conv2d_31 = cast(dtype = conv2d_31_cast_fp16_to_fp32_dtype_0, x = conv2d_31_cast_fp16)[name = tensor<string, []>("cast_4")]; |
| } -> (conv2d_21_1, conv2d_31); |
| } |
