| 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, 64, 64, 3]> input_1) { |
| tensor<int32, [2]> output_eyes_contours_and_brows_shape = const()[name = tensor<string, []>("output_eyes_contours_and_brows_shape"), val = tensor<int32, [2]>([1, -1])]; |
| tensor<int32, [2]> output_iris_shape = const()[name = tensor<string, []>("output_iris_shape"), val = tensor<int32, [2]>([1, -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, [64, 3, 3, 3]> transpose_0_to_fp16 = const()[name = tensor<string, []>("transpose_0_to_fp16"), val = tensor<fp16, [64, 3, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; |
| tensor<fp16, [64]> const_161_to_fp16 = const()[name = tensor<string, []>("const_161_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3584)))]; |
| tensor<fp16, [1, 64, 64, 3]> input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor<string, []>("cast_3")]; |
| tensor<fp16, [1, 3, 64, 64]> transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor<string, []>("transpose_170")]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_1_cast_fp16 = conv(bias = const_161_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, [64]> conv2d_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3776)))]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_prelu_1_add_alpha_0_to_fp16, x = conv2d_1_cast_fp16)[name = tensor<string, []>("conv2d_prelu_1_add_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, [32, 64, 1, 1]> transpose_2_to_fp16 = const()[name = tensor<string, []>("transpose_2_to_fp16"), val = tensor<fp16, [32, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3968)))]; |
| tensor<fp16, [32]> const_162_to_fp16 = const()[name = tensor<string, []>("const_162_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8128)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_1_1_cast_fp16 = conv(bias = const_162_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_2_to_fp16, x = conv2d_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_1_1_cast_fp16")]; |
| tensor<fp16, [32]> conv2d_1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8256)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_1_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_1_prelu_1_add_alpha_0_to_fp16, x = conv2d_1_1_cast_fp16)[name = tensor<string, []>("conv2d_1_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, []>(32)]; |
| tensor<int32, [4]> depthwisex_pad_0 = const()[name = tensor<string, []>("depthwisex_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [32, 1, 3, 3]> transpose_4_to_fp16 = const()[name = tensor<string, []>("transpose_4_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8384)))]; |
| tensor<fp16, [1, 32, 32, 32]> 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_4_to_fp16, x = conv2d_1_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwisex_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, [64, 32, 1, 1]> transpose_6_to_fp16 = const()[name = tensor<string, []>("transpose_6_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9024)))]; |
| tensor<fp16, [64]> const_163_to_fp16 = const()[name = tensor<string, []>("const_163_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13184)))]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_2_1_cast_fp16 = conv(bias = const_163_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_6_to_fp16, x = depthwisex_cast_fp16)[name = tensor<string, []>("conv2d_2_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 32, 32]> add__xeno_compat__1_cast_fp16 = add(x = conv2d_prelu_1_add_cast_fp16, y = conv2d_2_1_cast_fp16)[name = tensor<string, []>("add__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [64]> add__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13376)))]; |
| tensor<fp16, [1, 64, 32, 32]> add__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add__xeno_compat__1_prelu_1_add_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, 64, 1, 1]> transpose_8_to_fp16 = const()[name = tensor<string, []>("transpose_8_to_fp16"), val = tensor<fp16, [32, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13568)))]; |
| tensor<fp16, [32]> const_164_to_fp16 = const()[name = tensor<string, []>("const_164_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17728)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_3_1_cast_fp16 = conv(bias = const_164_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_8_to_fp16, x = add__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_3_1_cast_fp16")]; |
| tensor<fp16, [32]> conv2d_3_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_3_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17856)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_3_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_3_prelu_1_add_alpha_0_to_fp16, x = conv2d_3_1_cast_fp16)[name = tensor<string, []>("conv2d_3_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, []>(32)]; |
| 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, [32, 1, 3, 3]> transpose_10_to_fp16 = const()[name = tensor<string, []>("transpose_10_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17984)))]; |
| tensor<fp16, [1, 32, 32, 32]> 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_10_to_fp16, x = conv2d_3_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_1x_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, [64, 32, 1, 1]> transpose_12_to_fp16 = const()[name = tensor<string, []>("transpose_12_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18624)))]; |
| tensor<fp16, [64]> const_165_to_fp16 = const()[name = tensor<string, []>("const_165_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22784)))]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_4_1_cast_fp16 = conv(bias = const_165_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_12_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor<string, []>("conv2d_4_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 32, 32]> add_1__xeno_compat__1_cast_fp16 = add(x = add__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_4_1_cast_fp16)[name = tensor<string, []>("add_1__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [64]> add_1__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_1__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22976)))]; |
| tensor<fp16, [1, 64, 32, 32]> add_1__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_1__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_1__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_1__xeno_compat__1_prelu_1_add_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, [32, 64, 1, 1]> transpose_14_to_fp16 = const()[name = tensor<string, []>("transpose_14_to_fp16"), val = tensor<fp16, [32, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23168)))]; |
| tensor<fp16, [32]> const_166_to_fp16 = const()[name = tensor<string, []>("const_166_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27328)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_5_1_cast_fp16 = conv(bias = const_166_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_14_to_fp16, x = add_1__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_5_1_cast_fp16")]; |
| tensor<fp16, [32]> conv2d_5_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_5_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27456)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_5_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_5_prelu_1_add_alpha_0_to_fp16, x = conv2d_5_1_cast_fp16)[name = tensor<string, []>("conv2d_5_prelu_1_add_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]>([1, 1])]; |
| 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, []>(32)]; |
| 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, [32, 1, 3, 3]> transpose_16_to_fp16 = const()[name = tensor<string, []>("transpose_16_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27584)))]; |
| tensor<fp16, [1, 32, 32, 32]> 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_16_to_fp16, x = conv2d_5_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_2x_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, 32, 1, 1]> transpose_18_to_fp16 = const()[name = tensor<string, []>("transpose_18_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28224)))]; |
| tensor<fp16, [64]> const_167_to_fp16 = const()[name = tensor<string, []>("const_167_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32384)))]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_6_1_cast_fp16 = conv(bias = const_167_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_18_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor<string, []>("conv2d_6_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 32, 32]> add_2__xeno_compat__1_cast_fp16 = add(x = add_1__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_6_1_cast_fp16)[name = tensor<string, []>("add_2__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [64]> add_2__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_2__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32576)))]; |
| tensor<fp16, [1, 64, 32, 32]> add_2__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_2__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_2__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_2__xeno_compat__1_prelu_1_add_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, [32, 64, 1, 1]> transpose_20_to_fp16 = const()[name = tensor<string, []>("transpose_20_to_fp16"), val = tensor<fp16, [32, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32768)))]; |
| tensor<fp16, [32]> const_168_to_fp16 = const()[name = tensor<string, []>("const_168_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36928)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_7_1_cast_fp16 = conv(bias = const_168_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_20_to_fp16, x = add_2__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_7_1_cast_fp16")]; |
| tensor<fp16, [32]> conv2d_7_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_7_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37056)))]; |
| tensor<fp16, [1, 32, 32, 32]> conv2d_7_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_7_prelu_1_add_alpha_0_to_fp16, x = conv2d_7_1_cast_fp16)[name = tensor<string, []>("conv2d_7_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_22_to_fp16 = const()[name = tensor<string, []>("transpose_22_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37184)))]; |
| tensor<fp16, [1, 32, 32, 32]> 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_22_to_fp16, x = conv2d_7_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_3x_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, [64, 32, 1, 1]> transpose_24_to_fp16 = const()[name = tensor<string, []>("transpose_24_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37824)))]; |
| tensor<fp16, [64]> const_169_to_fp16 = const()[name = tensor<string, []>("const_169_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41984)))]; |
| tensor<fp16, [1, 64, 32, 32]> conv2d_8_1_cast_fp16 = conv(bias = const_169_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_24_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor<string, []>("conv2d_8_1_cast_fp16")]; |
| tensor<fp16, [1, 64, 32, 32]> add_3__xeno_compat__1_cast_fp16 = add(x = add_2__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_8_1_cast_fp16)[name = tensor<string, []>("add_3__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [64]> add_3__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_3__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42176)))]; |
| tensor<fp16, [1, 64, 32, 32]> add_3__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_3__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_3__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_3__xeno_compat__1_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, 64, 16, 16]> 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 = add_3__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_0_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]>([2, 2])]; |
| 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, [64, 64, 2, 2]> transpose_27_to_fp16 = const()[name = tensor<string, []>("transpose_27_to_fp16"), val = tensor<fp16, [64, 64, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42368)))]; |
| tensor<fp16, [64]> const_170_to_fp16 = const()[name = tensor<string, []>("const_170_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(75200)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_9_1_cast_fp16 = conv(bias = const_170_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_27_to_fp16, x = add_3__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_9_1_cast_fp16")]; |
| tensor<string, []> pad_0_mode_0 = const()[name = tensor<string, []>("pad_0_mode_0"), val = tensor<string, []>("constant")]; |
| tensor<int32, [8]> const_74 = const()[name = tensor<string, []>("const_74"), val = tensor<int32, [8]>([0, 0, 0, 64, 0, 0, 0, 0])]; |
| tensor<fp16, []> const_9_to_fp16 = const()[name = tensor<string, []>("const_9_to_fp16"), val = tensor<fp16, []>(0x0p+0)]; |
| tensor<fp16, [1, 128, 16, 16]> pad_0_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = pad_0_mode_0, pad = const_74, x = max_pool_0_cast_fp16)[name = tensor<string, []>("pad_0_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_9_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_9_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(75392)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_9_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_9_prelu_1_add_alpha_0_to_fp16, x = conv2d_9_1_cast_fp16)[name = tensor<string, []>("conv2d_9_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_29_to_fp16 = const()[name = tensor<string, []>("transpose_29_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(75584)))]; |
| tensor<fp16, [1, 64, 16, 16]> 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_29_to_fp16, x = conv2d_9_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_4x_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, 64, 1, 1]> transpose_31_to_fp16 = const()[name = tensor<string, []>("transpose_31_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76800)))]; |
| tensor<fp16, [128]> const_171_to_fp16 = const()[name = tensor<string, []>("const_171_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93248)))]; |
| tensor<fp16, [1, 128, 16, 16]> conv2d_10_1_cast_fp16 = conv(bias = const_171_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_31_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor<string, []>("conv2d_10_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 16, 16]> add_4__xeno_compat__1_cast_fp16 = add(x = pad_0_cast_fp16, y = conv2d_10_1_cast_fp16)[name = tensor<string, []>("add_4__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_4__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_4__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93568)))]; |
| tensor<fp16, [1, 128, 16, 16]> add_4__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_4__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_4__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_4__xeno_compat__1_prelu_1_add_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, [64, 128, 1, 1]> transpose_33_to_fp16 = const()[name = tensor<string, []>("transpose_33_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93888)))]; |
| tensor<fp16, [64]> const_172_to_fp16 = const()[name = tensor<string, []>("const_172_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110336)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_11_1_cast_fp16 = conv(bias = const_172_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_33_to_fp16, x = add_4__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_11_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_11_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_11_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110528)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_11_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_11_prelu_1_add_alpha_0_to_fp16, x = conv2d_11_1_cast_fp16)[name = tensor<string, []>("conv2d_11_prelu_1_add_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]>([1, 1])]; |
| 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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_35_to_fp16 = const()[name = tensor<string, []>("transpose_35_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110720)))]; |
| tensor<fp16, [1, 64, 16, 16]> 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_35_to_fp16, x = conv2d_11_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_5x_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, 64, 1, 1]> transpose_37_to_fp16 = const()[name = tensor<string, []>("transpose_37_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111936)))]; |
| tensor<fp16, [128]> const_173_to_fp16 = const()[name = tensor<string, []>("const_173_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128384)))]; |
| tensor<fp16, [1, 128, 16, 16]> conv2d_12_1_cast_fp16 = conv(bias = const_173_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_37_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor<string, []>("conv2d_12_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 16, 16]> add_5__xeno_compat__1_cast_fp16 = add(x = add_4__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_12_1_cast_fp16)[name = tensor<string, []>("add_5__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_5__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_5__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128704)))]; |
| tensor<fp16, [1, 128, 16, 16]> add_5__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_5__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_5__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_5__xeno_compat__1_prelu_1_add_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, [64, 128, 1, 1]> transpose_39_to_fp16 = const()[name = tensor<string, []>("transpose_39_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129024)))]; |
| tensor<fp16, [64]> const_174_to_fp16 = const()[name = tensor<string, []>("const_174_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145472)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_13_1_cast_fp16 = conv(bias = const_174_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_39_to_fp16, x = add_5__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_13_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_13_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_13_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145664)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_13_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_13_prelu_1_add_alpha_0_to_fp16, x = conv2d_13_1_cast_fp16)[name = tensor<string, []>("conv2d_13_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_41_to_fp16 = const()[name = tensor<string, []>("transpose_41_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145856)))]; |
| tensor<fp16, [1, 64, 16, 16]> 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_41_to_fp16, x = conv2d_13_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_6x_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, 64, 1, 1]> transpose_43_to_fp16 = const()[name = tensor<string, []>("transpose_43_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147072)))]; |
| tensor<fp16, [128]> const_175_to_fp16 = const()[name = tensor<string, []>("const_175_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163520)))]; |
| tensor<fp16, [1, 128, 16, 16]> conv2d_14_1_cast_fp16 = conv(bias = const_175_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_43_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor<string, []>("conv2d_14_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 16, 16]> add_6__xeno_compat__1_cast_fp16 = add(x = add_5__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_14_1_cast_fp16)[name = tensor<string, []>("add_6__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_6__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_6__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163840)))]; |
| tensor<fp16, [1, 128, 16, 16]> add_6__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_6__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_6__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_6__xeno_compat__1_prelu_1_add_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, [64, 128, 1, 1]> transpose_45_to_fp16 = const()[name = tensor<string, []>("transpose_45_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164160)))]; |
| tensor<fp16, [64]> const_176_to_fp16 = const()[name = tensor<string, []>("const_176_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180608)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_15_1_cast_fp16 = conv(bias = const_176_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_45_to_fp16, x = add_6__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_15_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_15_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_15_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180800)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_15_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_15_prelu_1_add_alpha_0_to_fp16, x = conv2d_15_1_cast_fp16)[name = tensor<string, []>("conv2d_15_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_47_to_fp16 = const()[name = tensor<string, []>("transpose_47_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180992)))]; |
| tensor<fp16, [1, 64, 16, 16]> 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_47_to_fp16, x = conv2d_15_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_7x_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, 64, 1, 1]> transpose_49_to_fp16 = const()[name = tensor<string, []>("transpose_49_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182208)))]; |
| tensor<fp16, [128]> const_177_to_fp16 = const()[name = tensor<string, []>("const_177_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198656)))]; |
| tensor<fp16, [1, 128, 16, 16]> conv2d_16_1_cast_fp16 = conv(bias = const_177_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_49_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor<string, []>("conv2d_16_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 16, 16]> add_7__xeno_compat__1_cast_fp16 = add(x = add_6__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_16_1_cast_fp16)[name = tensor<string, []>("add_7__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_7__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_7__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198976)))]; |
| tensor<fp16, [1, 128, 16, 16]> add_7__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_7__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_7__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_7__xeno_compat__1_prelu_1_add_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, [64, 128, 1, 1]> transpose_51_to_fp16 = const()[name = tensor<string, []>("transpose_51_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199296)))]; |
| tensor<fp16, [64]> const_178_to_fp16 = const()[name = tensor<string, []>("const_178_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215744)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_17_1_cast_fp16 = conv(bias = const_178_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_51_to_fp16, x = add_7__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_17_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_17_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_17_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215936)))]; |
| tensor<fp16, [1, 64, 16, 16]> conv2d_17_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_17_prelu_1_add_alpha_0_to_fp16, x = conv2d_17_1_cast_fp16)[name = tensor<string, []>("conv2d_17_prelu_1_add_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]>([1, 1])]; |
| 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_53_to_fp16 = const()[name = tensor<string, []>("transpose_53_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(216128)))]; |
| tensor<fp16, [1, 64, 16, 16]> 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_53_to_fp16, x = conv2d_17_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_8x_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, [128, 64, 1, 1]> transpose_55_to_fp16 = const()[name = tensor<string, []>("transpose_55_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(217344)))]; |
| tensor<fp16, [128]> const_179_to_fp16 = const()[name = tensor<string, []>("const_179_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233792)))]; |
| tensor<fp16, [1, 128, 16, 16]> conv2d_18_1_cast_fp16 = conv(bias = const_179_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_55_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor<string, []>("conv2d_18_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 16, 16]> add_8__xeno_compat__1_cast_fp16 = add(x = add_7__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_18_1_cast_fp16)[name = tensor<string, []>("add_8__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_8__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_8__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234112)))]; |
| tensor<fp16, [1, 128, 16, 16]> add_8__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_8__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_8__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_8__xeno_compat__1_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, 128, 8, 8]> 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 = add_8__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_1_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]>([2, 2])]; |
| 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, [64, 128, 2, 2]> transpose_58_to_fp16 = const()[name = tensor<string, []>("transpose_58_to_fp16"), val = tensor<fp16, [64, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234432)))]; |
| tensor<fp16, [64]> const_180_to_fp16 = const()[name = tensor<string, []>("const_180_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300032)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_19_1_cast_fp16 = conv(bias = const_180_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_58_to_fp16, x = add_8__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_19_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_19_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_19_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300224)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_19_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_19_prelu_1_add_alpha_0_to_fp16, x = conv2d_19_1_cast_fp16)[name = tensor<string, []>("conv2d_19_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_60_to_fp16 = const()[name = tensor<string, []>("transpose_60_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300416)))]; |
| tensor<fp16, [1, 64, 8, 8]> 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_60_to_fp16, x = conv2d_19_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_9x_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, [128, 64, 1, 1]> transpose_62_to_fp16 = const()[name = tensor<string, []>("transpose_62_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(301632)))]; |
| tensor<fp16, [128]> const_181_to_fp16 = const()[name = tensor<string, []>("const_181_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318080)))]; |
| tensor<fp16, [1, 128, 8, 8]> conv2d_20_1_cast_fp16 = conv(bias = const_181_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_62_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor<string, []>("conv2d_20_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 8, 8]> add_9__xeno_compat__1_cast_fp16 = add(x = max_pool_1_cast_fp16, y = conv2d_20_1_cast_fp16)[name = tensor<string, []>("add_9__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_9__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_9__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318400)))]; |
| tensor<fp16, [1, 128, 8, 8]> add_9__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_9__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_9__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_9__xeno_compat__1_prelu_1_add_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, [64, 128, 1, 1]> transpose_64_to_fp16 = const()[name = tensor<string, []>("transpose_64_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318720)))]; |
| tensor<fp16, [64]> const_182_to_fp16 = const()[name = tensor<string, []>("const_182_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335168)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_21_1_cast_fp16 = conv(bias = const_182_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_64_to_fp16, x = add_9__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_21_1_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]>([1, 1])]; |
| 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, [64, 128, 1, 1]> transpose_66_to_fp16 = const()[name = tensor<string, []>("transpose_66_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335360)))]; |
| tensor<fp16, [64]> const_183_to_fp16 = const()[name = tensor<string, []>("const_183_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(351808)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_37_cast_fp16 = conv(bias = const_183_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 = transpose_66_to_fp16, x = add_9__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_37_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_37_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_37_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352000)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_37_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_37_prelu_1_add_alpha_0_to_fp16, x = conv2d_21_1_cast_fp16)[name = tensor<string, []>("conv2d_37_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_21_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_21_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352192)))]; |
| tensor<fp16, [1, 64, 8, 8]> p_re_lu_21_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_21_prelu_1_add_alpha_0_to_fp16, x = conv2d_37_cast_fp16)[name = tensor<string, []>("p_re_lu_21_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_68_to_fp16 = const()[name = tensor<string, []>("transpose_68_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352384)))]; |
| tensor<fp16, [1, 64, 8, 8]> 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_68_to_fp16, x = conv2d_37_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_10x_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]>([1, 1])]; |
| 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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_70_to_fp16 = const()[name = tensor<string, []>("transpose_70_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353600)))]; |
| tensor<fp16, [1, 64, 8, 8]> 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_70_to_fp16, x = p_re_lu_21_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_11x_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]>([1, 1])]; |
| 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, [128, 64, 1, 1]> transpose_72_to_fp16 = const()[name = tensor<string, []>("transpose_72_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(354816)))]; |
| tensor<fp16, [128]> const_184_to_fp16 = const()[name = tensor<string, []>("const_184_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(371264)))]; |
| tensor<fp16, [1, 128, 8, 8]> conv2d_22_1_cast_fp16 = conv(bias = const_184_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 = transpose_72_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor<string, []>("conv2d_22_1_cast_fp16")]; |
| tensor<string, []> Conv2D_26x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_26x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_26x_strides_0 = const()[name = tensor<string, []>("Conv2D_26x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_26x_dilations_0 = const()[name = tensor<string, []>("Conv2D_26x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_26x_groups_0 = const()[name = tensor<string, []>("Conv2D_26x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_26x_pad_0 = const()[name = tensor<string, []>("Conv2D_26x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_74_to_fp16 = const()[name = tensor<string, []>("transpose_74_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(371584)))]; |
| tensor<fp16, [128]> const_185_to_fp16 = const()[name = tensor<string, []>("const_185_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388032)))]; |
| tensor<fp16, [1, 128, 8, 8]> conv2d_38_cast_fp16 = conv(bias = const_185_to_fp16, dilations = Conv2D_26x_dilations_0, groups = Conv2D_26x_groups_0, pad = Conv2D_26x_pad_0, pad_type = Conv2D_26x_pad_type_0, strides = Conv2D_26x_strides_0, weight = transpose_74_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor<string, []>("conv2d_38_cast_fp16")]; |
| tensor<fp16, [1, 128, 8, 8]> add_10__xeno_compat__1_cast_fp16 = add(x = add_9__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_22_1_cast_fp16)[name = tensor<string, []>("add_10__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 8, 8]> add_18__xeno_compat__1_cast_fp16 = add(x = add_9__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_38_cast_fp16)[name = tensor<string, []>("add_18__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_18__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_18__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388352)))]; |
| tensor<fp16, [1, 128, 8, 8]> add_18__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_18__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_10__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_18__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_22_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_22_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388672)))]; |
| tensor<fp16, [1, 128, 8, 8]> p_re_lu_22_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_22_prelu_1_add_alpha_0_to_fp16, x = add_18__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_22_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_27x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_27x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_27x_strides_0 = const()[name = tensor<string, []>("Conv2D_27x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_27x_dilations_0 = const()[name = tensor<string, []>("Conv2D_27x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_27x_groups_0 = const()[name = tensor<string, []>("Conv2D_27x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_27x_pad_0 = const()[name = tensor<string, []>("Conv2D_27x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_76_to_fp16 = const()[name = tensor<string, []>("transpose_76_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388992)))]; |
| tensor<fp16, [64]> const_186_to_fp16 = const()[name = tensor<string, []>("const_186_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405440)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_23_1_cast_fp16 = conv(bias = const_186_to_fp16, dilations = Conv2D_27x_dilations_0, groups = Conv2D_27x_groups_0, pad = Conv2D_27x_pad_0, pad_type = Conv2D_27x_pad_type_0, strides = Conv2D_27x_strides_0, weight = transpose_76_to_fp16, x = add_18__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_23_1_cast_fp16")]; |
| tensor<string, []> Conv2D_28x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_28x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_28x_strides_0 = const()[name = tensor<string, []>("Conv2D_28x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_28x_dilations_0 = const()[name = tensor<string, []>("Conv2D_28x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_28x_groups_0 = const()[name = tensor<string, []>("Conv2D_28x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_28x_pad_0 = const()[name = tensor<string, []>("Conv2D_28x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_78_to_fp16 = const()[name = tensor<string, []>("transpose_78_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405632)))]; |
| tensor<fp16, [64]> const_187_to_fp16 = const()[name = tensor<string, []>("const_187_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422080)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_39_cast_fp16 = conv(bias = const_187_to_fp16, dilations = Conv2D_28x_dilations_0, groups = Conv2D_28x_groups_0, pad = Conv2D_28x_pad_0, pad_type = Conv2D_28x_pad_type_0, strides = Conv2D_28x_strides_0, weight = transpose_78_to_fp16, x = p_re_lu_22_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_39_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_39_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_39_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422272)))]; |
| tensor<fp16, [1, 64, 8, 8]> conv2d_39_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_39_prelu_1_add_alpha_0_to_fp16, x = conv2d_23_1_cast_fp16)[name = tensor<string, []>("conv2d_39_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_23_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_23_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422464)))]; |
| tensor<fp16, [1, 64, 8, 8]> p_re_lu_23_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_23_prelu_1_add_alpha_0_to_fp16, x = conv2d_39_cast_fp16)[name = tensor<string, []>("p_re_lu_23_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_80_to_fp16 = const()[name = tensor<string, []>("transpose_80_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422656)))]; |
| tensor<fp16, [1, 64, 8, 8]> 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_80_to_fp16, x = conv2d_39_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_12x_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_82_to_fp16 = const()[name = tensor<string, []>("transpose_82_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(423872)))]; |
| tensor<fp16, [1, 64, 8, 8]> 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_82_to_fp16, x = p_re_lu_23_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_13x_cast_fp16")]; |
| tensor<string, []> Conv2D_29x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_29x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_29x_strides_0 = const()[name = tensor<string, []>("Conv2D_29x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_29x_dilations_0 = const()[name = tensor<string, []>("Conv2D_29x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_29x_groups_0 = const()[name = tensor<string, []>("Conv2D_29x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_29x_pad_0 = const()[name = tensor<string, []>("Conv2D_29x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_84_to_fp16 = const()[name = tensor<string, []>("transpose_84_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425088)))]; |
| tensor<fp16, [128]> const_188_to_fp16 = const()[name = tensor<string, []>("const_188_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441536)))]; |
| tensor<fp16, [1, 128, 8, 8]> conv2d_24_1_cast_fp16 = conv(bias = const_188_to_fp16, dilations = Conv2D_29x_dilations_0, groups = Conv2D_29x_groups_0, pad = Conv2D_29x_pad_0, pad_type = Conv2D_29x_pad_type_0, strides = Conv2D_29x_strides_0, weight = transpose_84_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor<string, []>("conv2d_24_1_cast_fp16")]; |
| tensor<string, []> Conv2D_30x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_30x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_30x_strides_0 = const()[name = tensor<string, []>("Conv2D_30x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_30x_dilations_0 = const()[name = tensor<string, []>("Conv2D_30x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_30x_groups_0 = const()[name = tensor<string, []>("Conv2D_30x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_30x_pad_0 = const()[name = tensor<string, []>("Conv2D_30x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_86_to_fp16 = const()[name = tensor<string, []>("transpose_86_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441856)))]; |
| tensor<fp16, [128]> const_189_to_fp16 = const()[name = tensor<string, []>("const_189_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(458304)))]; |
| tensor<fp16, [1, 128, 8, 8]> conv2d_40_cast_fp16 = conv(bias = const_189_to_fp16, dilations = Conv2D_30x_dilations_0, groups = Conv2D_30x_groups_0, pad = Conv2D_30x_pad_0, pad_type = Conv2D_30x_pad_type_0, strides = Conv2D_30x_strides_0, weight = transpose_86_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor<string, []>("conv2d_40_cast_fp16")]; |
| tensor<fp16, [1, 128, 8, 8]> add_11__xeno_compat__1_cast_fp16 = add(x = add_18__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_24_1_cast_fp16)[name = tensor<string, []>("add_11__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 8, 8]> add_19__xeno_compat__1_cast_fp16 = add(x = p_re_lu_22_prelu_1_add_cast_fp16, y = conv2d_40_cast_fp16)[name = tensor<string, []>("add_19__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_19__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_19__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(458624)))]; |
| tensor<fp16, [1, 128, 8, 8]> add_19__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_19__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_11__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_19__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_24_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_24_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(458944)))]; |
| tensor<fp16, [1, 128, 8, 8]> p_re_lu_24_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_24_prelu_1_add_alpha_0_to_fp16, x = add_19__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_24_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, 128, 4, 4]> 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 = add_19__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_2_cast_fp16")]; |
| tensor<string, []> Conv2D_31x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_31x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_31x_strides_0 = const()[name = tensor<string, []>("Conv2D_31x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> Conv2D_31x_dilations_0 = const()[name = tensor<string, []>("Conv2D_31x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_31x_groups_0 = const()[name = tensor<string, []>("Conv2D_31x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_31x_pad_0 = const()[name = tensor<string, []>("Conv2D_31x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 2, 2]> transpose_89_to_fp16 = const()[name = tensor<string, []>("transpose_89_to_fp16"), val = tensor<fp16, [64, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(459264)))]; |
| tensor<fp16, [64]> const_190_to_fp16 = const()[name = tensor<string, []>("const_190_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(524864)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_25_1_cast_fp16 = conv(bias = const_190_to_fp16, dilations = Conv2D_31x_dilations_0, groups = Conv2D_31x_groups_0, pad = Conv2D_31x_pad_0, pad_type = Conv2D_31x_pad_type_0, strides = Conv2D_31x_strides_0, weight = transpose_89_to_fp16, x = add_19__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_25_1_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, 4, 4]> 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_24_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_3_cast_fp16")]; |
| tensor<string, []> Conv2D_32x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_32x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_32x_strides_0 = const()[name = tensor<string, []>("Conv2D_32x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> Conv2D_32x_dilations_0 = const()[name = tensor<string, []>("Conv2D_32x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_32x_groups_0 = const()[name = tensor<string, []>("Conv2D_32x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_32x_pad_0 = const()[name = tensor<string, []>("Conv2D_32x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 2, 2]> transpose_92_to_fp16 = const()[name = tensor<string, []>("transpose_92_to_fp16"), val = tensor<fp16, [64, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525056)))]; |
| tensor<fp16, [64]> const_191_to_fp16 = const()[name = tensor<string, []>("const_191_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(590656)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_41_cast_fp16 = conv(bias = const_191_to_fp16, dilations = Conv2D_32x_dilations_0, groups = Conv2D_32x_groups_0, pad = Conv2D_32x_pad_0, pad_type = Conv2D_32x_pad_type_0, strides = Conv2D_32x_strides_0, weight = transpose_92_to_fp16, x = p_re_lu_24_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_41_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_41_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_41_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(590848)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_41_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_41_prelu_1_add_alpha_0_to_fp16, x = conv2d_25_1_cast_fp16)[name = tensor<string, []>("conv2d_41_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_25_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_25_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(591040)))]; |
| tensor<fp16, [1, 64, 4, 4]> p_re_lu_25_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_25_prelu_1_add_alpha_0_to_fp16, x = conv2d_41_cast_fp16)[name = tensor<string, []>("p_re_lu_25_prelu_1_add_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]>([1, 1])]; |
| 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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_94_to_fp16 = const()[name = tensor<string, []>("transpose_94_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(591232)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_94_to_fp16, x = conv2d_41_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_14x_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_96_to_fp16 = const()[name = tensor<string, []>("transpose_96_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(592448)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_96_to_fp16, x = p_re_lu_25_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_15x_cast_fp16")]; |
| tensor<string, []> Conv2D_33x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_33x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_33x_strides_0 = const()[name = tensor<string, []>("Conv2D_33x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_33x_dilations_0 = const()[name = tensor<string, []>("Conv2D_33x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_33x_groups_0 = const()[name = tensor<string, []>("Conv2D_33x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_33x_pad_0 = const()[name = tensor<string, []>("Conv2D_33x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_98_to_fp16 = const()[name = tensor<string, []>("transpose_98_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(593664)))]; |
| tensor<fp16, [128]> const_192_to_fp16 = const()[name = tensor<string, []>("const_192_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(610112)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_26_1_cast_fp16 = conv(bias = const_192_to_fp16, dilations = Conv2D_33x_dilations_0, groups = Conv2D_33x_groups_0, pad = Conv2D_33x_pad_0, pad_type = Conv2D_33x_pad_type_0, strides = Conv2D_33x_strides_0, weight = transpose_98_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor<string, []>("conv2d_26_1_cast_fp16")]; |
| tensor<string, []> Conv2D_34x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_34x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_34x_strides_0 = const()[name = tensor<string, []>("Conv2D_34x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_34x_dilations_0 = const()[name = tensor<string, []>("Conv2D_34x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_34x_groups_0 = const()[name = tensor<string, []>("Conv2D_34x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_34x_pad_0 = const()[name = tensor<string, []>("Conv2D_34x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_100_to_fp16 = const()[name = tensor<string, []>("transpose_100_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(610432)))]; |
| tensor<fp16, [128]> const_193_to_fp16 = const()[name = tensor<string, []>("const_193_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(626880)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_42_cast_fp16 = conv(bias = const_193_to_fp16, dilations = Conv2D_34x_dilations_0, groups = Conv2D_34x_groups_0, pad = Conv2D_34x_pad_0, pad_type = Conv2D_34x_pad_type_0, strides = Conv2D_34x_strides_0, weight = transpose_100_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor<string, []>("conv2d_42_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_12__xeno_compat__1_cast_fp16 = add(x = max_pool_2_cast_fp16, y = conv2d_26_1_cast_fp16)[name = tensor<string, []>("add_12__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_20__xeno_compat__1_cast_fp16 = add(x = max_pool_3_cast_fp16, y = conv2d_42_cast_fp16)[name = tensor<string, []>("add_20__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_20__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_20__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627200)))]; |
| tensor<fp16, [1, 128, 4, 4]> add_20__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_20__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_12__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_20__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_26_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_26_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627520)))]; |
| tensor<fp16, [1, 128, 4, 4]> p_re_lu_26_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_26_prelu_1_add_alpha_0_to_fp16, x = add_20__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_26_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_35x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_35x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_35x_strides_0 = const()[name = tensor<string, []>("Conv2D_35x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_35x_dilations_0 = const()[name = tensor<string, []>("Conv2D_35x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_35x_groups_0 = const()[name = tensor<string, []>("Conv2D_35x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_35x_pad_0 = const()[name = tensor<string, []>("Conv2D_35x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_102_to_fp16 = const()[name = tensor<string, []>("transpose_102_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627840)))]; |
| tensor<fp16, [64]> const_194_to_fp16 = const()[name = tensor<string, []>("const_194_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644288)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_27_1_cast_fp16 = conv(bias = const_194_to_fp16, dilations = Conv2D_35x_dilations_0, groups = Conv2D_35x_groups_0, pad = Conv2D_35x_pad_0, pad_type = Conv2D_35x_pad_type_0, strides = Conv2D_35x_strides_0, weight = transpose_102_to_fp16, x = add_20__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_27_1_cast_fp16")]; |
| tensor<string, []> Conv2D_36x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_36x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_36x_strides_0 = const()[name = tensor<string, []>("Conv2D_36x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_36x_dilations_0 = const()[name = tensor<string, []>("Conv2D_36x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_36x_groups_0 = const()[name = tensor<string, []>("Conv2D_36x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_36x_pad_0 = const()[name = tensor<string, []>("Conv2D_36x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_104_to_fp16 = const()[name = tensor<string, []>("transpose_104_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644480)))]; |
| tensor<fp16, [64]> const_195_to_fp16 = const()[name = tensor<string, []>("const_195_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(660928)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_43_cast_fp16 = conv(bias = const_195_to_fp16, dilations = Conv2D_36x_dilations_0, groups = Conv2D_36x_groups_0, pad = Conv2D_36x_pad_0, pad_type = Conv2D_36x_pad_type_0, strides = Conv2D_36x_strides_0, weight = transpose_104_to_fp16, x = p_re_lu_26_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_43_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_43_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_43_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(661120)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_43_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_43_prelu_1_add_alpha_0_to_fp16, x = conv2d_27_1_cast_fp16)[name = tensor<string, []>("conv2d_43_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_27_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_27_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(661312)))]; |
| tensor<fp16, [1, 64, 4, 4]> p_re_lu_27_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_27_prelu_1_add_alpha_0_to_fp16, x = conv2d_43_cast_fp16)[name = tensor<string, []>("p_re_lu_27_prelu_1_add_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]>([1, 1])]; |
| 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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_106_to_fp16 = const()[name = tensor<string, []>("transpose_106_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(661504)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_106_to_fp16, x = conv2d_43_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_16x_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_108_to_fp16 = const()[name = tensor<string, []>("transpose_108_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(662720)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_108_to_fp16, x = p_re_lu_27_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_17x_cast_fp16")]; |
| tensor<string, []> Conv2D_44x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_44x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_44x_strides_0 = const()[name = tensor<string, []>("Conv2D_44x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_44x_dilations_0 = const()[name = tensor<string, []>("Conv2D_44x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_44x_groups_0 = const()[name = tensor<string, []>("Conv2D_44x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_44x_pad_0 = const()[name = tensor<string, []>("Conv2D_44x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_110_to_fp16 = const()[name = tensor<string, []>("transpose_110_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663936)))]; |
| tensor<fp16, [128]> const_196_to_fp16 = const()[name = tensor<string, []>("const_196_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680384)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_28_1_cast_fp16 = conv(bias = const_196_to_fp16, dilations = Conv2D_44x_dilations_0, groups = Conv2D_44x_groups_0, pad = Conv2D_44x_pad_0, pad_type = Conv2D_44x_pad_type_0, strides = Conv2D_44x_strides_0, weight = transpose_110_to_fp16, x = depthwise_16x_cast_fp16)[name = tensor<string, []>("conv2d_28_1_cast_fp16")]; |
| tensor<string, []> Conv2D_45x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_45x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_45x_strides_0 = const()[name = tensor<string, []>("Conv2D_45x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_45x_dilations_0 = const()[name = tensor<string, []>("Conv2D_45x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_45x_groups_0 = const()[name = tensor<string, []>("Conv2D_45x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_45x_pad_0 = const()[name = tensor<string, []>("Conv2D_45x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_112_to_fp16 = const()[name = tensor<string, []>("transpose_112_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680704)))]; |
| tensor<fp16, [128]> const_197_to_fp16 = const()[name = tensor<string, []>("const_197_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(697152)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_44_1_cast_fp16 = conv(bias = const_197_to_fp16, dilations = Conv2D_45x_dilations_0, groups = Conv2D_45x_groups_0, pad = Conv2D_45x_pad_0, pad_type = Conv2D_45x_pad_type_0, strides = Conv2D_45x_strides_0, weight = transpose_112_to_fp16, x = depthwise_17x_cast_fp16)[name = tensor<string, []>("conv2d_44_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_13__xeno_compat__1_cast_fp16 = add(x = add_20__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_28_1_cast_fp16)[name = tensor<string, []>("add_13__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_21__xeno_compat__1_cast_fp16 = add(x = p_re_lu_26_prelu_1_add_cast_fp16, y = conv2d_44_1_cast_fp16)[name = tensor<string, []>("add_21__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_21__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_21__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(697472)))]; |
| tensor<fp16, [1, 128, 4, 4]> add_21__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_21__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_13__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_21__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_28_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_28_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(697792)))]; |
| tensor<fp16, [1, 128, 4, 4]> p_re_lu_28_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_28_prelu_1_add_alpha_0_to_fp16, x = add_21__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_28_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_46x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_46x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_46x_strides_0 = const()[name = tensor<string, []>("Conv2D_46x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_46x_dilations_0 = const()[name = tensor<string, []>("Conv2D_46x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_46x_groups_0 = const()[name = tensor<string, []>("Conv2D_46x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_46x_pad_0 = const()[name = tensor<string, []>("Conv2D_46x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_114_to_fp16 = const()[name = tensor<string, []>("transpose_114_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(698112)))]; |
| tensor<fp16, [64]> const_198_to_fp16 = const()[name = tensor<string, []>("const_198_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(714560)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_29_1_cast_fp16 = conv(bias = const_198_to_fp16, dilations = Conv2D_46x_dilations_0, groups = Conv2D_46x_groups_0, pad = Conv2D_46x_pad_0, pad_type = Conv2D_46x_pad_type_0, strides = Conv2D_46x_strides_0, weight = transpose_114_to_fp16, x = add_21__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_29_1_cast_fp16")]; |
| tensor<string, []> Conv2D_47x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_47x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_47x_strides_0 = const()[name = tensor<string, []>("Conv2D_47x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_47x_dilations_0 = const()[name = tensor<string, []>("Conv2D_47x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_47x_groups_0 = const()[name = tensor<string, []>("Conv2D_47x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_47x_pad_0 = const()[name = tensor<string, []>("Conv2D_47x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_116_to_fp16 = const()[name = tensor<string, []>("transpose_116_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(714752)))]; |
| tensor<fp16, [64]> const_199_to_fp16 = const()[name = tensor<string, []>("const_199_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(731200)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_45_1_cast_fp16 = conv(bias = const_199_to_fp16, dilations = Conv2D_47x_dilations_0, groups = Conv2D_47x_groups_0, pad = Conv2D_47x_pad_0, pad_type = Conv2D_47x_pad_type_0, strides = Conv2D_47x_strides_0, weight = transpose_116_to_fp16, x = p_re_lu_28_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_45_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_45_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_45_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(731392)))]; |
| tensor<fp16, [1, 64, 4, 4]> conv2d_45_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_45_prelu_1_add_alpha_0_to_fp16, x = conv2d_29_1_cast_fp16)[name = tensor<string, []>("conv2d_45_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_29_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_29_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(731584)))]; |
| tensor<fp16, [1, 64, 4, 4]> p_re_lu_29_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_29_prelu_1_add_alpha_0_to_fp16, x = conv2d_45_1_cast_fp16)[name = tensor<string, []>("p_re_lu_29_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_118_to_fp16 = const()[name = tensor<string, []>("transpose_118_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(731776)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_118_to_fp16, x = conv2d_45_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_18x_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, []>(64)]; |
| 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, [64, 1, 3, 3]> transpose_120_to_fp16 = const()[name = tensor<string, []>("transpose_120_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(732992)))]; |
| tensor<fp16, [1, 64, 4, 4]> 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_120_to_fp16, x = p_re_lu_29_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_19x_cast_fp16")]; |
| tensor<string, []> Conv2D_48x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_48x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_48x_strides_0 = const()[name = tensor<string, []>("Conv2D_48x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_48x_dilations_0 = const()[name = tensor<string, []>("Conv2D_48x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_48x_groups_0 = const()[name = tensor<string, []>("Conv2D_48x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_48x_pad_0 = const()[name = tensor<string, []>("Conv2D_48x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_122_to_fp16 = const()[name = tensor<string, []>("transpose_122_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(734208)))]; |
| tensor<fp16, [128]> const_200_to_fp16 = const()[name = tensor<string, []>("const_200_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(750656)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_30_1_cast_fp16 = conv(bias = const_200_to_fp16, dilations = Conv2D_48x_dilations_0, groups = Conv2D_48x_groups_0, pad = Conv2D_48x_pad_0, pad_type = Conv2D_48x_pad_type_0, strides = Conv2D_48x_strides_0, weight = transpose_122_to_fp16, x = depthwise_18x_cast_fp16)[name = tensor<string, []>("conv2d_30_1_cast_fp16")]; |
| tensor<string, []> Conv2D_49x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_49x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_49x_strides_0 = const()[name = tensor<string, []>("Conv2D_49x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_49x_dilations_0 = const()[name = tensor<string, []>("Conv2D_49x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_49x_groups_0 = const()[name = tensor<string, []>("Conv2D_49x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_49x_pad_0 = const()[name = tensor<string, []>("Conv2D_49x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_124_to_fp16 = const()[name = tensor<string, []>("transpose_124_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(750976)))]; |
| tensor<fp16, [128]> const_201_to_fp16 = const()[name = tensor<string, []>("const_201_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(767424)))]; |
| tensor<fp16, [1, 128, 4, 4]> conv2d_46_1_cast_fp16 = conv(bias = const_201_to_fp16, dilations = Conv2D_49x_dilations_0, groups = Conv2D_49x_groups_0, pad = Conv2D_49x_pad_0, pad_type = Conv2D_49x_pad_type_0, strides = Conv2D_49x_strides_0, weight = transpose_124_to_fp16, x = depthwise_19x_cast_fp16)[name = tensor<string, []>("conv2d_46_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_14__xeno_compat__1_cast_fp16 = add(x = add_21__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_30_1_cast_fp16)[name = tensor<string, []>("add_14__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 4, 4]> add_22__xeno_compat__1_cast_fp16 = add(x = p_re_lu_28_prelu_1_add_cast_fp16, y = conv2d_46_1_cast_fp16)[name = tensor<string, []>("add_22__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_22__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_22__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(767744)))]; |
| tensor<fp16, [1, 128, 4, 4]> add_22__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_22__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_14__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_22__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_30_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_30_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768064)))]; |
| tensor<fp16, [1, 128, 4, 4]> p_re_lu_30_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_30_prelu_1_add_alpha_0_to_fp16, x = add_22__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_30_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, 2, 2]> 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 = add_22__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_4_cast_fp16")]; |
| tensor<string, []> Conv2D_50x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_50x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_50x_strides_0 = const()[name = tensor<string, []>("Conv2D_50x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> Conv2D_50x_dilations_0 = const()[name = tensor<string, []>("Conv2D_50x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_50x_groups_0 = const()[name = tensor<string, []>("Conv2D_50x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_50x_pad_0 = const()[name = tensor<string, []>("Conv2D_50x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 2, 2]> transpose_127_to_fp16 = const()[name = tensor<string, []>("transpose_127_to_fp16"), val = tensor<fp16, [64, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768384)))]; |
| tensor<fp16, [64]> const_202_to_fp16 = const()[name = tensor<string, []>("const_202_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(833984)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_31_1_cast_fp16 = conv(bias = const_202_to_fp16, dilations = Conv2D_50x_dilations_0, groups = Conv2D_50x_groups_0, pad = Conv2D_50x_pad_0, pad_type = Conv2D_50x_pad_type_0, strides = Conv2D_50x_strides_0, weight = transpose_127_to_fp16, x = add_22__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_31_1_cast_fp16")]; |
| tensor<int32, [2]> max_pool_5_kernel_sizes_0 = const()[name = tensor<string, []>("max_pool_5_kernel_sizes_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> max_pool_5_strides_0 = const()[name = tensor<string, []>("max_pool_5_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<string, []> max_pool_5_pad_type_0 = const()[name = tensor<string, []>("max_pool_5_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [4]> max_pool_5_pad_0 = const()[name = tensor<string, []>("max_pool_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<bool, []> max_pool_5_ceil_mode_0 = const()[name = tensor<string, []>("max_pool_5_ceil_mode_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [1, 128, 2, 2]> max_pool_5_cast_fp16 = max_pool(ceil_mode = max_pool_5_ceil_mode_0, kernel_sizes = max_pool_5_kernel_sizes_0, pad = max_pool_5_pad_0, pad_type = max_pool_5_pad_type_0, strides = max_pool_5_strides_0, x = p_re_lu_30_prelu_1_add_cast_fp16)[name = tensor<string, []>("max_pool_5_cast_fp16")]; |
| tensor<string, []> Conv2D_51x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_51x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_51x_strides_0 = const()[name = tensor<string, []>("Conv2D_51x_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> Conv2D_51x_dilations_0 = const()[name = tensor<string, []>("Conv2D_51x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_51x_groups_0 = const()[name = tensor<string, []>("Conv2D_51x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_51x_pad_0 = const()[name = tensor<string, []>("Conv2D_51x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 2, 2]> transpose_130_to_fp16 = const()[name = tensor<string, []>("transpose_130_to_fp16"), val = tensor<fp16, [64, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(834176)))]; |
| tensor<fp16, [64]> const_203_to_fp16 = const()[name = tensor<string, []>("const_203_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(899776)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_47_1_cast_fp16 = conv(bias = const_203_to_fp16, dilations = Conv2D_51x_dilations_0, groups = Conv2D_51x_groups_0, pad = Conv2D_51x_pad_0, pad_type = Conv2D_51x_pad_type_0, strides = Conv2D_51x_strides_0, weight = transpose_130_to_fp16, x = p_re_lu_30_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_47_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_47_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_47_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(899968)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_47_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_47_prelu_1_add_alpha_0_to_fp16, x = conv2d_31_1_cast_fp16)[name = tensor<string, []>("conv2d_47_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_31_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_31_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900160)))]; |
| tensor<fp16, [1, 64, 2, 2]> p_re_lu_31_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_31_prelu_1_add_alpha_0_to_fp16, x = conv2d_47_1_cast_fp16)[name = tensor<string, []>("p_re_lu_31_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_20x_pad_type_0 = const()[name = tensor<string, []>("depthwise_20x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_20x_strides_0 = const()[name = tensor<string, []>("depthwise_20x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_20x_dilations_0 = const()[name = tensor<string, []>("depthwise_20x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_20x_groups_0 = const()[name = tensor<string, []>("depthwise_20x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_20x_pad_0 = const()[name = tensor<string, []>("depthwise_20x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_132_to_fp16 = const()[name = tensor<string, []>("transpose_132_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900352)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_20x_cast_fp16 = conv(dilations = depthwise_20x_dilations_0, groups = depthwise_20x_groups_0, pad = depthwise_20x_pad_0, pad_type = depthwise_20x_pad_type_0, strides = depthwise_20x_strides_0, weight = transpose_132_to_fp16, x = conv2d_47_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_20x_cast_fp16")]; |
| tensor<string, []> depthwise_21x_pad_type_0 = const()[name = tensor<string, []>("depthwise_21x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_21x_strides_0 = const()[name = tensor<string, []>("depthwise_21x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_21x_dilations_0 = const()[name = tensor<string, []>("depthwise_21x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_21x_groups_0 = const()[name = tensor<string, []>("depthwise_21x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_21x_pad_0 = const()[name = tensor<string, []>("depthwise_21x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_134_to_fp16 = const()[name = tensor<string, []>("transpose_134_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(901568)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_21x_cast_fp16 = conv(dilations = depthwise_21x_dilations_0, groups = depthwise_21x_groups_0, pad = depthwise_21x_pad_0, pad_type = depthwise_21x_pad_type_0, strides = depthwise_21x_strides_0, weight = transpose_134_to_fp16, x = p_re_lu_31_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_21x_cast_fp16")]; |
| tensor<string, []> Conv2D_52x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_52x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_52x_strides_0 = const()[name = tensor<string, []>("Conv2D_52x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_52x_dilations_0 = const()[name = tensor<string, []>("Conv2D_52x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_52x_groups_0 = const()[name = tensor<string, []>("Conv2D_52x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_52x_pad_0 = const()[name = tensor<string, []>("Conv2D_52x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_136_to_fp16 = const()[name = tensor<string, []>("transpose_136_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(902784)))]; |
| tensor<fp16, [128]> const_204_to_fp16 = const()[name = tensor<string, []>("const_204_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(919232)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_32_1_cast_fp16 = conv(bias = const_204_to_fp16, dilations = Conv2D_52x_dilations_0, groups = Conv2D_52x_groups_0, pad = Conv2D_52x_pad_0, pad_type = Conv2D_52x_pad_type_0, strides = Conv2D_52x_strides_0, weight = transpose_136_to_fp16, x = depthwise_20x_cast_fp16)[name = tensor<string, []>("conv2d_32_1_cast_fp16")]; |
| tensor<string, []> Conv2D_53x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_53x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_53x_strides_0 = const()[name = tensor<string, []>("Conv2D_53x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_53x_dilations_0 = const()[name = tensor<string, []>("Conv2D_53x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_53x_groups_0 = const()[name = tensor<string, []>("Conv2D_53x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_53x_pad_0 = const()[name = tensor<string, []>("Conv2D_53x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_138_to_fp16 = const()[name = tensor<string, []>("transpose_138_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(919552)))]; |
| tensor<fp16, [128]> const_205_to_fp16 = const()[name = tensor<string, []>("const_205_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(936000)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_48_1_cast_fp16 = conv(bias = const_205_to_fp16, dilations = Conv2D_53x_dilations_0, groups = Conv2D_53x_groups_0, pad = Conv2D_53x_pad_0, pad_type = Conv2D_53x_pad_type_0, strides = Conv2D_53x_strides_0, weight = transpose_138_to_fp16, x = depthwise_21x_cast_fp16)[name = tensor<string, []>("conv2d_48_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_15__xeno_compat__1_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_32_1_cast_fp16)[name = tensor<string, []>("add_15__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_23__xeno_compat__1_cast_fp16 = add(x = max_pool_5_cast_fp16, y = conv2d_48_1_cast_fp16)[name = tensor<string, []>("add_23__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_23__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_23__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(936320)))]; |
| tensor<fp16, [1, 128, 2, 2]> add_23__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_23__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_15__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_23__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_32_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_32_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(936640)))]; |
| tensor<fp16, [1, 128, 2, 2]> p_re_lu_32_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_32_prelu_1_add_alpha_0_to_fp16, x = add_23__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_32_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_54x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_54x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_54x_strides_0 = const()[name = tensor<string, []>("Conv2D_54x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_54x_dilations_0 = const()[name = tensor<string, []>("Conv2D_54x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_54x_groups_0 = const()[name = tensor<string, []>("Conv2D_54x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_54x_pad_0 = const()[name = tensor<string, []>("Conv2D_54x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_140_to_fp16 = const()[name = tensor<string, []>("transpose_140_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(936960)))]; |
| tensor<fp16, [64]> const_206_to_fp16 = const()[name = tensor<string, []>("const_206_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953408)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_33_1_cast_fp16 = conv(bias = const_206_to_fp16, dilations = Conv2D_54x_dilations_0, groups = Conv2D_54x_groups_0, pad = Conv2D_54x_pad_0, pad_type = Conv2D_54x_pad_type_0, strides = Conv2D_54x_strides_0, weight = transpose_140_to_fp16, x = add_23__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_33_1_cast_fp16")]; |
| tensor<string, []> Conv2D_55x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_55x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_55x_strides_0 = const()[name = tensor<string, []>("Conv2D_55x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_55x_dilations_0 = const()[name = tensor<string, []>("Conv2D_55x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_55x_groups_0 = const()[name = tensor<string, []>("Conv2D_55x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_55x_pad_0 = const()[name = tensor<string, []>("Conv2D_55x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_142_to_fp16 = const()[name = tensor<string, []>("transpose_142_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953600)))]; |
| tensor<fp16, [64]> const_207_to_fp16 = const()[name = tensor<string, []>("const_207_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(970048)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_49_1_cast_fp16 = conv(bias = const_207_to_fp16, dilations = Conv2D_55x_dilations_0, groups = Conv2D_55x_groups_0, pad = Conv2D_55x_pad_0, pad_type = Conv2D_55x_pad_type_0, strides = Conv2D_55x_strides_0, weight = transpose_142_to_fp16, x = p_re_lu_32_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_49_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_49_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_49_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(970240)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_49_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_49_prelu_1_add_alpha_0_to_fp16, x = conv2d_33_1_cast_fp16)[name = tensor<string, []>("conv2d_49_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_33_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_33_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(970432)))]; |
| tensor<fp16, [1, 64, 2, 2]> p_re_lu_33_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_33_prelu_1_add_alpha_0_to_fp16, x = conv2d_49_1_cast_fp16)[name = tensor<string, []>("p_re_lu_33_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_22x_pad_type_0 = const()[name = tensor<string, []>("depthwise_22x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_22x_strides_0 = const()[name = tensor<string, []>("depthwise_22x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_22x_dilations_0 = const()[name = tensor<string, []>("depthwise_22x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_22x_groups_0 = const()[name = tensor<string, []>("depthwise_22x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_22x_pad_0 = const()[name = tensor<string, []>("depthwise_22x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_144_to_fp16 = const()[name = tensor<string, []>("transpose_144_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(970624)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_22x_cast_fp16 = conv(dilations = depthwise_22x_dilations_0, groups = depthwise_22x_groups_0, pad = depthwise_22x_pad_0, pad_type = depthwise_22x_pad_type_0, strides = depthwise_22x_strides_0, weight = transpose_144_to_fp16, x = conv2d_49_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_22x_cast_fp16")]; |
| tensor<string, []> depthwise_23x_pad_type_0 = const()[name = tensor<string, []>("depthwise_23x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_23x_strides_0 = const()[name = tensor<string, []>("depthwise_23x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_23x_dilations_0 = const()[name = tensor<string, []>("depthwise_23x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_23x_groups_0 = const()[name = tensor<string, []>("depthwise_23x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_23x_pad_0 = const()[name = tensor<string, []>("depthwise_23x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_146_to_fp16 = const()[name = tensor<string, []>("transpose_146_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971840)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_23x_cast_fp16 = conv(dilations = depthwise_23x_dilations_0, groups = depthwise_23x_groups_0, pad = depthwise_23x_pad_0, pad_type = depthwise_23x_pad_type_0, strides = depthwise_23x_strides_0, weight = transpose_146_to_fp16, x = p_re_lu_33_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_23x_cast_fp16")]; |
| tensor<string, []> Conv2D_56x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_56x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_56x_strides_0 = const()[name = tensor<string, []>("Conv2D_56x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_56x_dilations_0 = const()[name = tensor<string, []>("Conv2D_56x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_56x_groups_0 = const()[name = tensor<string, []>("Conv2D_56x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_56x_pad_0 = const()[name = tensor<string, []>("Conv2D_56x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_148_to_fp16 = const()[name = tensor<string, []>("transpose_148_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(973056)))]; |
| tensor<fp16, [128]> const_208_to_fp16 = const()[name = tensor<string, []>("const_208_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(989504)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_34_1_cast_fp16 = conv(bias = const_208_to_fp16, dilations = Conv2D_56x_dilations_0, groups = Conv2D_56x_groups_0, pad = Conv2D_56x_pad_0, pad_type = Conv2D_56x_pad_type_0, strides = Conv2D_56x_strides_0, weight = transpose_148_to_fp16, x = depthwise_22x_cast_fp16)[name = tensor<string, []>("conv2d_34_1_cast_fp16")]; |
| tensor<string, []> Conv2D_57x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_57x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_57x_strides_0 = const()[name = tensor<string, []>("Conv2D_57x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_57x_dilations_0 = const()[name = tensor<string, []>("Conv2D_57x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_57x_groups_0 = const()[name = tensor<string, []>("Conv2D_57x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_57x_pad_0 = const()[name = tensor<string, []>("Conv2D_57x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_150_to_fp16 = const()[name = tensor<string, []>("transpose_150_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(989824)))]; |
| tensor<fp16, [128]> const_209_to_fp16 = const()[name = tensor<string, []>("const_209_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1006272)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_50_1_cast_fp16 = conv(bias = const_209_to_fp16, dilations = Conv2D_57x_dilations_0, groups = Conv2D_57x_groups_0, pad = Conv2D_57x_pad_0, pad_type = Conv2D_57x_pad_type_0, strides = Conv2D_57x_strides_0, weight = transpose_150_to_fp16, x = depthwise_23x_cast_fp16)[name = tensor<string, []>("conv2d_50_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_16__xeno_compat__1_cast_fp16 = add(x = add_23__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_34_1_cast_fp16)[name = tensor<string, []>("add_16__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_24__xeno_compat__1_cast_fp16 = add(x = p_re_lu_32_prelu_1_add_cast_fp16, y = conv2d_50_1_cast_fp16)[name = tensor<string, []>("add_24__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_24__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_24__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1006592)))]; |
| tensor<fp16, [1, 128, 2, 2]> add_24__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_24__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_16__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_24__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_34_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_34_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1006912)))]; |
| tensor<fp16, [1, 128, 2, 2]> p_re_lu_34_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_34_prelu_1_add_alpha_0_to_fp16, x = add_24__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_34_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_58x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_58x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_58x_strides_0 = const()[name = tensor<string, []>("Conv2D_58x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_58x_dilations_0 = const()[name = tensor<string, []>("Conv2D_58x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_58x_groups_0 = const()[name = tensor<string, []>("Conv2D_58x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_58x_pad_0 = const()[name = tensor<string, []>("Conv2D_58x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_152_to_fp16 = const()[name = tensor<string, []>("transpose_152_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1007232)))]; |
| tensor<fp16, [64]> const_210_to_fp16 = const()[name = tensor<string, []>("const_210_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1023680)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_35_1_cast_fp16 = conv(bias = const_210_to_fp16, dilations = Conv2D_58x_dilations_0, groups = Conv2D_58x_groups_0, pad = Conv2D_58x_pad_0, pad_type = Conv2D_58x_pad_type_0, strides = Conv2D_58x_strides_0, weight = transpose_152_to_fp16, x = add_24__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_35_1_cast_fp16")]; |
| tensor<string, []> Conv2D_59x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_59x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_59x_strides_0 = const()[name = tensor<string, []>("Conv2D_59x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_59x_dilations_0 = const()[name = tensor<string, []>("Conv2D_59x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_59x_groups_0 = const()[name = tensor<string, []>("Conv2D_59x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_59x_pad_0 = const()[name = tensor<string, []>("Conv2D_59x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 128, 1, 1]> transpose_154_to_fp16 = const()[name = tensor<string, []>("transpose_154_to_fp16"), val = tensor<fp16, [64, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1023872)))]; |
| tensor<fp16, [64]> const_211_to_fp16 = const()[name = tensor<string, []>("const_211_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1040320)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_51_1_cast_fp16 = conv(bias = const_211_to_fp16, dilations = Conv2D_59x_dilations_0, groups = Conv2D_59x_groups_0, pad = Conv2D_59x_pad_0, pad_type = Conv2D_59x_pad_type_0, strides = Conv2D_59x_strides_0, weight = transpose_154_to_fp16, x = p_re_lu_34_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv2d_51_1_cast_fp16")]; |
| tensor<fp16, [64]> conv2d_51_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("conv2d_51_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1040512)))]; |
| tensor<fp16, [1, 64, 2, 2]> conv2d_51_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_51_prelu_1_add_alpha_0_to_fp16, x = conv2d_35_1_cast_fp16)[name = tensor<string, []>("conv2d_51_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [64]> p_re_lu_35_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_35_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1040704)))]; |
| tensor<fp16, [1, 64, 2, 2]> p_re_lu_35_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_35_prelu_1_add_alpha_0_to_fp16, x = conv2d_51_1_cast_fp16)[name = tensor<string, []>("p_re_lu_35_prelu_1_add_cast_fp16")]; |
| tensor<string, []> depthwise_24x_pad_type_0 = const()[name = tensor<string, []>("depthwise_24x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_24x_strides_0 = const()[name = tensor<string, []>("depthwise_24x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_24x_dilations_0 = const()[name = tensor<string, []>("depthwise_24x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_24x_groups_0 = const()[name = tensor<string, []>("depthwise_24x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_24x_pad_0 = const()[name = tensor<string, []>("depthwise_24x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_156_to_fp16 = const()[name = tensor<string, []>("transpose_156_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1040896)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_24x_cast_fp16 = conv(dilations = depthwise_24x_dilations_0, groups = depthwise_24x_groups_0, pad = depthwise_24x_pad_0, pad_type = depthwise_24x_pad_type_0, strides = depthwise_24x_strides_0, weight = transpose_156_to_fp16, x = conv2d_51_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_24x_cast_fp16")]; |
| tensor<string, []> depthwise_25x_pad_type_0 = const()[name = tensor<string, []>("depthwise_25x_pad_type_0"), val = tensor<string, []>("same")]; |
| tensor<int32, [2]> depthwise_25x_strides_0 = const()[name = tensor<string, []>("depthwise_25x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> depthwise_25x_dilations_0 = const()[name = tensor<string, []>("depthwise_25x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> depthwise_25x_groups_0 = const()[name = tensor<string, []>("depthwise_25x_groups_0"), val = tensor<int32, []>(64)]; |
| tensor<int32, [4]> depthwise_25x_pad_0 = const()[name = tensor<string, []>("depthwise_25x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [64, 1, 3, 3]> transpose_158_to_fp16 = const()[name = tensor<string, []>("transpose_158_to_fp16"), val = tensor<fp16, [64, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1042112)))]; |
| tensor<fp16, [1, 64, 2, 2]> depthwise_25x_cast_fp16 = conv(dilations = depthwise_25x_dilations_0, groups = depthwise_25x_groups_0, pad = depthwise_25x_pad_0, pad_type = depthwise_25x_pad_type_0, strides = depthwise_25x_strides_0, weight = transpose_158_to_fp16, x = p_re_lu_35_prelu_1_add_cast_fp16)[name = tensor<string, []>("depthwise_25x_cast_fp16")]; |
| tensor<string, []> Conv2D_60x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_60x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_60x_strides_0 = const()[name = tensor<string, []>("Conv2D_60x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_60x_dilations_0 = const()[name = tensor<string, []>("Conv2D_60x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_60x_groups_0 = const()[name = tensor<string, []>("Conv2D_60x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_60x_pad_0 = const()[name = tensor<string, []>("Conv2D_60x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_160_to_fp16 = const()[name = tensor<string, []>("transpose_160_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1043328)))]; |
| tensor<fp16, [128]> const_212_to_fp16 = const()[name = tensor<string, []>("const_212_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1059776)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_36_1_cast_fp16 = conv(bias = const_212_to_fp16, dilations = Conv2D_60x_dilations_0, groups = Conv2D_60x_groups_0, pad = Conv2D_60x_pad_0, pad_type = Conv2D_60x_pad_type_0, strides = Conv2D_60x_strides_0, weight = transpose_160_to_fp16, x = depthwise_24x_cast_fp16)[name = tensor<string, []>("conv2d_36_1_cast_fp16")]; |
| tensor<string, []> Conv2D_61x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_61x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_61x_strides_0 = const()[name = tensor<string, []>("Conv2D_61x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_61x_dilations_0 = const()[name = tensor<string, []>("Conv2D_61x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_61x_groups_0 = const()[name = tensor<string, []>("Conv2D_61x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_61x_pad_0 = const()[name = tensor<string, []>("Conv2D_61x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [128, 64, 1, 1]> transpose_162_to_fp16 = const()[name = tensor<string, []>("transpose_162_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1060096)))]; |
| tensor<fp16, [128]> const_213_to_fp16 = const()[name = tensor<string, []>("const_213_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1076544)))]; |
| tensor<fp16, [1, 128, 2, 2]> conv2d_52_1_cast_fp16 = conv(bias = const_213_to_fp16, dilations = Conv2D_61x_dilations_0, groups = Conv2D_61x_groups_0, pad = Conv2D_61x_pad_0, pad_type = Conv2D_61x_pad_type_0, strides = Conv2D_61x_strides_0, weight = transpose_162_to_fp16, x = depthwise_25x_cast_fp16)[name = tensor<string, []>("conv2d_52_1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_17__xeno_compat__1_cast_fp16 = add(x = add_24__xeno_compat__1_prelu_1_add_cast_fp16, y = conv2d_36_1_cast_fp16)[name = tensor<string, []>("add_17__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [1, 128, 2, 2]> add_25__xeno_compat__1_cast_fp16 = add(x = p_re_lu_34_prelu_1_add_cast_fp16, y = conv2d_52_1_cast_fp16)[name = tensor<string, []>("add_25__xeno_compat__1_cast_fp16")]; |
| tensor<fp16, [128]> add_25__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("add_25__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1076864)))]; |
| tensor<fp16, [1, 128, 2, 2]> add_25__xeno_compat__1_prelu_1_add_cast_fp16 = prelu(alpha = add_25__xeno_compat__1_prelu_1_add_alpha_0_to_fp16, x = add_17__xeno_compat__1_cast_fp16)[name = tensor<string, []>("add_25__xeno_compat__1_prelu_1_add_cast_fp16")]; |
| tensor<fp16, [128]> p_re_lu_36_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor<string, []>("p_re_lu_36_prelu_1_add_alpha_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077184)))]; |
| tensor<fp16, [1, 128, 2, 2]> p_re_lu_36_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_36_prelu_1_add_alpha_0_to_fp16, x = add_25__xeno_compat__1_cast_fp16)[name = tensor<string, []>("p_re_lu_36_prelu_1_add_cast_fp16")]; |
| tensor<string, []> Conv2D_62x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_62x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_62x_strides_0 = const()[name = tensor<string, []>("Conv2D_62x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_62x_dilations_0 = const()[name = tensor<string, []>("Conv2D_62x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_62x_groups_0 = const()[name = tensor<string, []>("Conv2D_62x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_62x_pad_0 = const()[name = tensor<string, []>("Conv2D_62x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [213, 128, 2, 2]> conv_0_weight_0_to_fp16 = const()[name = tensor<string, []>("conv_0_weight_0_to_fp16"), val = tensor<fp16, [213, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077504)))]; |
| tensor<fp16, [213]> conv_0_bias_0_to_fp16 = const()[name = tensor<string, []>("conv_0_bias_0_to_fp16"), val = tensor<fp16, [213]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1295680)))]; |
| tensor<fp16, [1, 213, 1, 1]> conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, dilations = Conv2D_62x_dilations_0, groups = Conv2D_62x_groups_0, pad = Conv2D_62x_pad_0, pad_type = Conv2D_62x_pad_type_0, strides = Conv2D_62x_strides_0, weight = conv_0_weight_0_to_fp16, x = add_25__xeno_compat__1_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv_0_cast_fp16")]; |
| tensor<int32, [4]> Conv2D_62_perm_0 = const()[name = tensor<string, []>("Conv2D_62_perm_0"), val = tensor<int32, [4]>([0, 2, 3, 1])]; |
| tensor<string, []> Conv2D_63x_pad_type_0 = const()[name = tensor<string, []>("Conv2D_63x_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> Conv2D_63x_strides_0 = const()[name = tensor<string, []>("Conv2D_63x_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> Conv2D_63x_dilations_0 = const()[name = tensor<string, []>("Conv2D_63x_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> Conv2D_63x_groups_0 = const()[name = tensor<string, []>("Conv2D_63x_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<int32, [4]> Conv2D_63x_pad_0 = const()[name = tensor<string, []>("Conv2D_63x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<fp16, [15, 128, 2, 2]> conv_1_weight_0_to_fp16 = const()[name = tensor<string, []>("conv_1_weight_0_to_fp16"), val = tensor<fp16, [15, 128, 2, 2]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1296192)))]; |
| tensor<fp16, [15]> conv_1_bias_0_to_fp16 = const()[name = tensor<string, []>("conv_1_bias_0_to_fp16"), val = tensor<fp16, [15]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1311616)))]; |
| tensor<fp16, [1, 15, 1, 1]> conv_1_cast_fp16 = conv(bias = conv_1_bias_0_to_fp16, dilations = Conv2D_63x_dilations_0, groups = Conv2D_63x_groups_0, pad = Conv2D_63x_pad_0, pad_type = Conv2D_63x_pad_type_0, strides = Conv2D_63x_strides_0, weight = conv_1_weight_0_to_fp16, x = p_re_lu_36_prelu_1_add_cast_fp16)[name = tensor<string, []>("conv_1_cast_fp16")]; |
| tensor<int32, [4]> Conv2D_63_perm_0 = const()[name = tensor<string, []>("Conv2D_63_perm_0"), val = tensor<int32, [4]>([0, 2, 3, 1])]; |
| tensor<fp16, [1, 1, 1, 213]> conv_eyes_contours_and_brows_cast_fp16 = transpose(perm = Conv2D_62_perm_0, x = conv_0_cast_fp16)[name = tensor<string, []>("transpose_169")]; |
| tensor<fp16, [1, 213]> output_eyes_contours_and_brows_cast_fp16 = reshape(shape = output_eyes_contours_and_brows_shape, x = conv_eyes_contours_and_brows_cast_fp16)[name = tensor<string, []>("output_eyes_contours_and_brows_cast_fp16")]; |
| tensor<string, []> output_eyes_contours_and_brows_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("output_eyes_contours_and_brows_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")]; |
| tensor<fp16, [1, 1, 1, 15]> conv_iris_cast_fp16 = transpose(perm = Conv2D_63_perm_0, x = conv_1_cast_fp16)[name = tensor<string, []>("transpose_168")]; |
| tensor<fp16, [1, 15]> output_iris_cast_fp16 = reshape(shape = output_iris_shape, x = conv_iris_cast_fp16)[name = tensor<string, []>("output_iris_cast_fp16")]; |
| tensor<string, []> output_iris_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("output_iris_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")]; |
| tensor<fp32, [1, 15]> output_iris = cast(dtype = output_iris_cast_fp16_to_fp32_dtype_0, x = output_iris_cast_fp16)[name = tensor<string, []>("cast_1")]; |
| tensor<fp32, [1, 213]> output_eyes_contours_and_brows = cast(dtype = output_eyes_contours_and_brows_cast_fp16_to_fp32_dtype_0, x = output_eyes_contours_and_brows_cast_fp16)[name = tensor<string, []>("cast_2")]; |
| } -> (output_eyes_contours_and_brows, output_iris); |
| } |
