diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..6ea7140f853ed615a6fe75aa1d1f6504145e2e2d --- /dev/null +++ b/README.md @@ -0,0 +1,23 @@ +# Converted Models + +This directory is the local staging area for converted runtime model artifacts. + +Layout: + +- `coreml/`: `.mlpackage` outputs produced by the local MediaPipe conversion pipeline. +- `compiled/`: compiled `.mlmodelc` directories produced by `xcrun coremlcompiler`. +- `intermediate/`: optional SavedModel and protobuf conversion outputs. This directory is ignored by git. + +The binary model artifacts in this tree are intentionally ignored by git. They are meant to be: + +1. generated locally for validation, +2. uploaded to a Hugging Face model repository, +3. pulled back down for development as needed. + +Typical workflow: + +```sh +just convert-models all +just upload-models your-org/wormhole-mediapipe-coreml +just download-models your-org/wormhole-mediapipe-coreml +``` diff --git a/compiled/face_detection_short_range.mlmodelc/analytics/coremldata.bin b/compiled/face_detection_short_range.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..103b7625dd142bc9174c8b87c0dc25c00f0273d2 --- /dev/null +++ b/compiled/face_detection_short_range.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bc234a62a6f35f4ea2808ee81d5f2a42d81b625799792c8f35e00c62e545f4bd +size 243 diff --git a/compiled/face_detection_short_range.mlmodelc/coremldata.bin b/compiled/face_detection_short_range.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..35672585670304ed81a43b53e9fa948e72bb59ce --- /dev/null +++ b/compiled/face_detection_short_range.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a6d13a825d4114de9825c2b6682ce53632ff8cdd5a49f7832a230e941be7a97d +size 295 diff --git a/compiled/face_detection_short_range.mlmodelc/metadata.json b/compiled/face_detection_short_range.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..fd53ccc7070f0e21b38ade04b6bed20a78956a1d --- /dev/null +++ b/compiled/face_detection_short_range.mlmodelc/metadata.json @@ -0,0 +1,77 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 896 × 1)", + "shortDescription" : "", + "shape" : "[1, 896, 1]", + "name" : "classificators", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 896 × 16)", + "shortDescription" : "", + "shape" : "[1, 896, 16]", + "name" : "regressors", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Concat" : 2, + "Cast" : 3, + "Conv" : 37, + "Pad" : 11, + "Relu" : 17, + "Transpose" : 5, + "Add" : 16, + "Reshape" : 4, + "MaxPool" : 3 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 128 × 128 × 3)", + "shortDescription" : "", + "shape" : "[1, 128, 128, 3]", + "name" : "input", + "type" : "MultiArray" + } + ], + "generatedClassName" : "face_detection_short_range", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/face_detection_short_range.mlmodelc/model.mil b/compiled/face_detection_short_range.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..1bc9673f15bfb4c9ed57bfbcead28b43efd4bc52 --- /dev/null +++ b/compiled/face_detection_short_range.mlmodelc/model.mil @@ -0,0 +1,411 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input) { + tensor reshape_shape = const()[name = tensor("reshape_shape"), val = tensor([1, -1, 1])]; + tensor reshape_2_shape = const()[name = tensor("reshape_2_shape"), val = tensor([1, -1, 1])]; + tensor classificators_axis = const()[name = tensor("classificators_axis"), val = tensor(1)]; + tensor reshape_1_shape = const()[name = tensor("reshape_1_shape"), val = tensor([1, -1, 16])]; + tensor reshape_3_shape = const()[name = tensor("reshape_3_shape"), val = tensor([1, -1, 16])]; + tensor regressors_axis = const()[name = tensor("regressors_axis"), val = tensor(1)]; + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_to_fp16_dtype_0 = const()[name = tensor("input_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3776)))]; + tensor input_to_fp16 = cast(dtype = input_to_fp16_dtype_0, x = input)[name = tensor("cast_13")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_to_fp16)[name = tensor("transpose_81")]; + tensor conv2d_1_cast_fp16 = conv(bias = const_39_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("conv2d_1_cast_fp16")]; + tensor activation_cast_fp16 = relu(x = conv2d_1_cast_fp16)[name = tensor("activation_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(24)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3904)))]; + tensor depthwisex_cast_fp16 = conv(dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = activation_cast_fp16)[name = tensor("depthwisex_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4416)))]; + tensor const_40_to_fp16 = const()[name = tensor("const_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5632)))]; + tensor conv2d_1_1_cast_fp16 = conv(bias = const_40_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_4_to_fp16, x = depthwisex_cast_fp16)[name = tensor("conv2d_1_1_cast_fp16")]; + tensor add__xeno_compat__1_cast_fp16 = add(x = activation_cast_fp16, y = conv2d_1_1_cast_fp16)[name = tensor("add__xeno_compat__1_cast_fp16")]; + tensor activation_1_cast_fp16 = relu(x = add__xeno_compat__1_cast_fp16)[name = tensor("activation_1_cast_fp16")]; + tensor pad_0_mode_0 = const()[name = tensor("pad_0_mode_0"), val = tensor("constant")]; + tensor const_12 = const()[name = tensor("const_12"), val = tensor([0, 0, 0, 4, 0, 0, 0, 0])]; + tensor const_0_to_fp16 = const()[name = tensor("const_0_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_0_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = pad_0_mode_0, pad = const_12, x = activation_1_cast_fp16)[name = tensor("pad_0_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(24)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5760)))]; + tensor depthwise_1x_cast_fp16 = conv(dilations = depthwise_1x_dilations_0, groups = depthwise_1x_groups_0, pad = depthwise_1x_pad_0, pad_type = depthwise_1x_pad_type_0, strides = depthwise_1x_strides_0, weight = transpose_6_to_fp16, x = activation_1_cast_fp16)[name = tensor("depthwise_1x_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6272)))]; + tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7680)))]; + tensor conv2d_2_1_cast_fp16 = conv(bias = const_41_to_fp16, dilations = Conv2D_3x_dilations_0, groups = Conv2D_3x_groups_0, pad = Conv2D_3x_pad_0, pad_type = Conv2D_3x_pad_type_0, strides = Conv2D_3x_strides_0, weight = transpose_8_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor("conv2d_2_1_cast_fp16")]; + tensor add_1__xeno_compat__1_cast_fp16 = add(x = pad_0_cast_fp16, y = conv2d_2_1_cast_fp16)[name = tensor("add_1__xeno_compat__1_cast_fp16")]; + tensor activation_2_cast_fp16 = relu(x = add_1__xeno_compat__1_cast_fp16)[name = tensor("activation_2_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("same")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor 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 = activation_2_cast_fp16)[name = tensor("max_pool_0_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(28)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_11_to_fp16 = const()[name = tensor("transpose_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7808)))]; + tensor depthwise_2x_cast_fp16 = conv(dilations = depthwise_2x_dilations_0, groups = depthwise_2x_groups_0, pad = depthwise_2x_pad_0, pad_type = depthwise_2x_pad_type_0, strides = depthwise_2x_strides_0, weight = transpose_11_to_fp16, x = activation_2_cast_fp16)[name = tensor("depthwise_2x_cast_fp16")]; + tensor pad_1_mode_0 = const()[name = tensor("pad_1_mode_0"), val = tensor("constant")]; + tensor const_18 = const()[name = tensor("const_18"), val = tensor([0, 0, 0, 4, 0, 0, 0, 0])]; + tensor const_1_to_fp16 = const()[name = tensor("const_1_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_1_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = pad_1_mode_0, pad = const_18, x = max_pool_0_cast_fp16)[name = tensor("pad_1_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_13_to_fp16 = const()[name = tensor("transpose_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8384)))]; + tensor const_42_to_fp16 = const()[name = tensor("const_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10240)))]; + tensor conv2d_3_1_cast_fp16 = conv(bias = const_42_to_fp16, dilations = Conv2D_4x_dilations_0, groups = Conv2D_4x_groups_0, pad = Conv2D_4x_pad_0, pad_type = Conv2D_4x_pad_type_0, strides = Conv2D_4x_strides_0, weight = transpose_13_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor("conv2d_3_1_cast_fp16")]; + tensor add_2__xeno_compat__1_cast_fp16 = add(x = pad_1_cast_fp16, y = conv2d_3_1_cast_fp16)[name = tensor("add_2__xeno_compat__1_cast_fp16")]; + tensor activation_3_cast_fp16 = relu(x = add_2__xeno_compat__1_cast_fp16)[name = tensor("activation_3_cast_fp16")]; + tensor pad_2_mode_0 = const()[name = tensor("pad_2_mode_0"), val = tensor("constant")]; + tensor const_16 = const()[name = tensor("const_16"), val = tensor([0, 0, 0, 4, 0, 0, 0, 0])]; + tensor const_2_to_fp16 = const()[name = tensor("const_2_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_2_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = pad_2_mode_0, pad = const_16, x = activation_3_cast_fp16)[name = tensor("pad_2_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(32)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_15_to_fp16 = const()[name = tensor("transpose_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10368)))]; + tensor depthwise_3x_cast_fp16 = conv(dilations = depthwise_3x_dilations_0, groups = depthwise_3x_groups_0, pad = depthwise_3x_pad_0, pad_type = depthwise_3x_pad_type_0, strides = depthwise_3x_strides_0, weight = transpose_15_to_fp16, x = activation_3_cast_fp16)[name = tensor("depthwise_3x_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_17_to_fp16 = const()[name = tensor("transpose_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11008)))]; + tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13376)))]; + tensor conv2d_4_1_cast_fp16 = conv(bias = const_43_to_fp16, dilations = Conv2D_5x_dilations_0, groups = Conv2D_5x_groups_0, pad = Conv2D_5x_pad_0, pad_type = Conv2D_5x_pad_type_0, strides = Conv2D_5x_strides_0, weight = transpose_17_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor("conv2d_4_1_cast_fp16")]; + tensor add_3__xeno_compat__1_cast_fp16 = add(x = pad_2_cast_fp16, y = conv2d_4_1_cast_fp16)[name = tensor("add_3__xeno_compat__1_cast_fp16")]; + tensor activation_4_cast_fp16 = relu(x = add_3__xeno_compat__1_cast_fp16)[name = tensor("activation_4_cast_fp16")]; + tensor pad_3_mode_0 = const()[name = tensor("pad_3_mode_0"), val = tensor("constant")]; + tensor const_17 = const()[name = tensor("const_17"), val = tensor([0, 0, 0, 6, 0, 0, 0, 0])]; + tensor const_3_to_fp16 = const()[name = tensor("const_3_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_3_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = pad_3_mode_0, pad = const_17, x = activation_4_cast_fp16)[name = tensor("pad_3_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(36)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_19_to_fp16 = const()[name = tensor("transpose_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13568)))]; + tensor depthwise_4x_cast_fp16 = conv(dilations = depthwise_4x_dilations_0, groups = depthwise_4x_groups_0, pad = depthwise_4x_pad_0, pad_type = depthwise_4x_pad_type_0, strides = depthwise_4x_strides_0, weight = transpose_19_to_fp16, x = activation_4_cast_fp16)[name = tensor("depthwise_4x_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_21_to_fp16 = const()[name = tensor("transpose_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14336)))]; + tensor const_44_to_fp16 = const()[name = tensor("const_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17472)))]; + tensor conv2d_5_1_cast_fp16 = conv(bias = const_44_to_fp16, dilations = Conv2D_6x_dilations_0, groups = Conv2D_6x_groups_0, pad = Conv2D_6x_pad_0, pad_type = Conv2D_6x_pad_type_0, strides = Conv2D_6x_strides_0, weight = transpose_21_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor("conv2d_5_1_cast_fp16")]; + tensor add_4__xeno_compat__1_cast_fp16 = add(x = pad_3_cast_fp16, y = conv2d_5_1_cast_fp16)[name = tensor("add_4__xeno_compat__1_cast_fp16")]; + tensor activation_5_cast_fp16 = relu(x = add_4__xeno_compat__1_cast_fp16)[name = tensor("activation_5_cast_fp16")]; + tensor max_pool_1_kernel_sizes_0 = const()[name = tensor("max_pool_1_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_1_strides_0 = const()[name = tensor("max_pool_1_strides_0"), val = tensor([2, 2])]; + tensor max_pool_1_pad_type_0 = const()[name = tensor("max_pool_1_pad_type_0"), val = tensor("same")]; + tensor max_pool_1_pad_0 = const()[name = tensor("max_pool_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_1_ceil_mode_0 = const()[name = tensor("max_pool_1_ceil_mode_0"), val = tensor(false)]; + tensor 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 = activation_5_cast_fp16)[name = tensor("max_pool_1_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(42)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_24_to_fp16 = const()[name = tensor("transpose_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17664)))]; + tensor depthwise_5x_cast_fp16 = conv(dilations = depthwise_5x_dilations_0, groups = depthwise_5x_groups_0, pad = depthwise_5x_pad_0, pad_type = depthwise_5x_pad_type_0, strides = depthwise_5x_strides_0, weight = transpose_24_to_fp16, x = activation_5_cast_fp16)[name = tensor("depthwise_5x_cast_fp16")]; + tensor pad_4_mode_0 = const()[name = tensor("pad_4_mode_0"), val = tensor("constant")]; + tensor const_21 = const()[name = tensor("const_21"), val = tensor([0, 0, 0, 6, 0, 0, 0, 0])]; + tensor const_4_to_fp16 = const()[name = tensor("const_4_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_4_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = pad_4_mode_0, pad = const_21, x = max_pool_1_cast_fp16)[name = tensor("pad_4_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_26_to_fp16 = const()[name = tensor("transpose_26_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18496)))]; + tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22592)))]; + tensor conv2d_6_1_cast_fp16 = conv(bias = const_45_to_fp16, dilations = Conv2D_7x_dilations_0, groups = Conv2D_7x_groups_0, pad = Conv2D_7x_pad_0, pad_type = Conv2D_7x_pad_type_0, strides = Conv2D_7x_strides_0, weight = transpose_26_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor("conv2d_6_1_cast_fp16")]; + tensor add_5__xeno_compat__1_cast_fp16 = add(x = pad_4_cast_fp16, y = conv2d_6_1_cast_fp16)[name = tensor("add_5__xeno_compat__1_cast_fp16")]; + tensor activation_6_cast_fp16 = relu(x = add_5__xeno_compat__1_cast_fp16)[name = tensor("activation_6_cast_fp16")]; + tensor pad_5_mode_0 = const()[name = tensor("pad_5_mode_0"), val = tensor("constant")]; + tensor const_22 = const()[name = tensor("const_22"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_5_to_fp16 = const()[name = tensor("const_5_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_5_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = pad_5_mode_0, pad = const_22, x = activation_6_cast_fp16)[name = tensor("pad_5_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(48)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_28_to_fp16 = const()[name = tensor("transpose_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22784)))]; + tensor depthwise_6x_cast_fp16 = conv(dilations = depthwise_6x_dilations_0, groups = depthwise_6x_groups_0, pad = depthwise_6x_pad_0, pad_type = depthwise_6x_pad_type_0, strides = depthwise_6x_strides_0, weight = transpose_28_to_fp16, x = activation_6_cast_fp16)[name = tensor("depthwise_6x_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_30_to_fp16 = const()[name = tensor("transpose_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23744)))]; + tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29184)))]; + tensor conv2d_7_1_cast_fp16 = conv(bias = const_46_to_fp16, dilations = Conv2D_8x_dilations_0, groups = Conv2D_8x_groups_0, pad = Conv2D_8x_pad_0, pad_type = Conv2D_8x_pad_type_0, strides = Conv2D_8x_strides_0, weight = transpose_30_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor("conv2d_7_1_cast_fp16")]; + tensor add_6__xeno_compat__1_cast_fp16 = add(x = pad_5_cast_fp16, y = conv2d_7_1_cast_fp16)[name = tensor("add_6__xeno_compat__1_cast_fp16")]; + tensor activation_7_cast_fp16 = relu(x = add_6__xeno_compat__1_cast_fp16)[name = tensor("activation_7_cast_fp16")]; + tensor pad_6_mode_0 = const()[name = tensor("pad_6_mode_0"), val = tensor("constant")]; + tensor const_23 = const()[name = tensor("const_23"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_6_to_fp16 = const()[name = tensor("const_6_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_6_cast_fp16 = pad(constant_val = const_6_to_fp16, mode = pad_6_mode_0, pad = const_23, x = activation_7_cast_fp16)[name = tensor("pad_6_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(56)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_32_to_fp16 = const()[name = tensor("transpose_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29376)))]; + tensor depthwise_7x_cast_fp16 = conv(dilations = depthwise_7x_dilations_0, groups = depthwise_7x_groups_0, pad = depthwise_7x_pad_0, pad_type = depthwise_7x_pad_type_0, strides = depthwise_7x_strides_0, weight = transpose_32_to_fp16, x = activation_7_cast_fp16)[name = tensor("depthwise_7x_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_34_to_fp16 = const()[name = tensor("transpose_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30464)))]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37696)))]; + tensor conv2d_8_1_cast_fp16 = conv(bias = const_47_to_fp16, dilations = Conv2D_9x_dilations_0, groups = Conv2D_9x_groups_0, pad = Conv2D_9x_pad_0, pad_type = Conv2D_9x_pad_type_0, strides = Conv2D_9x_strides_0, weight = transpose_34_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor("conv2d_8_1_cast_fp16")]; + tensor add_7__xeno_compat__1_cast_fp16 = add(x = pad_6_cast_fp16, y = conv2d_8_1_cast_fp16)[name = tensor("add_7__xeno_compat__1_cast_fp16")]; + tensor activation_8_cast_fp16 = relu(x = add_7__xeno_compat__1_cast_fp16)[name = tensor("activation_8_cast_fp16")]; + tensor pad_7_mode_0 = const()[name = tensor("pad_7_mode_0"), val = tensor("constant")]; + tensor const_24 = const()[name = tensor("const_24"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_7_to_fp16 = const()[name = tensor("const_7_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_7_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = pad_7_mode_0, pad = const_24, x = activation_8_cast_fp16)[name = tensor("pad_7_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(64)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_36_to_fp16 = const()[name = tensor("transpose_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37888)))]; + tensor 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_36_to_fp16, x = activation_8_cast_fp16)[name = tensor("depthwise_8x_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_38_to_fp16 = const()[name = tensor("transpose_38_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39104)))]; + tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48384)))]; + tensor conv2d_9_1_cast_fp16 = conv(bias = const_48_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_38_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor("conv2d_9_1_cast_fp16")]; + tensor add_8__xeno_compat__1_cast_fp16 = add(x = pad_7_cast_fp16, y = conv2d_9_1_cast_fp16)[name = tensor("add_8__xeno_compat__1_cast_fp16")]; + tensor activation_9_cast_fp16 = relu(x = add_8__xeno_compat__1_cast_fp16)[name = tensor("activation_9_cast_fp16")]; + tensor pad_8_mode_0 = const()[name = tensor("pad_8_mode_0"), val = tensor("constant")]; + tensor const_25 = const()[name = tensor("const_25"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_8_to_fp16 = const()[name = tensor("const_8_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_8_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = pad_8_mode_0, pad = const_25, x = activation_9_cast_fp16)[name = tensor("pad_8_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(72)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_40_to_fp16 = const()[name = tensor("transpose_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48640)))]; + tensor 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_40_to_fp16, x = activation_9_cast_fp16)[name = tensor("depthwise_9x_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_42_to_fp16 = const()[name = tensor("transpose_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50048)))]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61632)))]; + tensor conv2d_10_1_cast_fp16 = conv(bias = const_49_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_42_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor("conv2d_10_1_cast_fp16")]; + tensor add_9__xeno_compat__1_cast_fp16 = add(x = pad_8_cast_fp16, y = conv2d_10_1_cast_fp16)[name = tensor("add_9__xeno_compat__1_cast_fp16")]; + tensor activation_10_cast_fp16 = relu(x = add_9__xeno_compat__1_cast_fp16)[name = tensor("activation_10_cast_fp16")]; + tensor pad_9_mode_0 = const()[name = tensor("pad_9_mode_0"), val = tensor("constant")]; + tensor const_26 = const()[name = tensor("const_26"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_9_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = pad_9_mode_0, pad = const_26, x = activation_10_cast_fp16)[name = tensor("pad_9_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(80)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_44_to_fp16 = const()[name = tensor("transpose_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61888)))]; + tensor 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_44_to_fp16, x = activation_10_cast_fp16)[name = tensor("depthwise_10x_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_46_to_fp16 = const()[name = tensor("transpose_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63424)))]; + tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77568)))]; + tensor conv2d_11_1_cast_fp16 = conv(bias = const_50_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_46_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor("conv2d_11_1_cast_fp16")]; + tensor add_10__xeno_compat__1_cast_fp16 = add(x = pad_9_cast_fp16, y = conv2d_11_1_cast_fp16)[name = tensor("add_10__xeno_compat__1_cast_fp16")]; + tensor activation_11_cast_fp16 = relu(x = add_10__xeno_compat__1_cast_fp16)[name = tensor("activation_11_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77824)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor([0x1.264p-1, 0x1.458p-3])]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_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 = conv_0_weight_0_to_fp16, x = activation_11_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor Conv2D_18_perm_0 = const()[name = tensor("Conv2D_18_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor max_pool_2_kernel_sizes_0 = const()[name = tensor("max_pool_2_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_2_strides_0 = const()[name = tensor("max_pool_2_strides_0"), val = tensor([2, 2])]; + tensor max_pool_2_pad_type_0 = const()[name = tensor("max_pool_2_pad_type_0"), val = tensor("same")]; + tensor max_pool_2_pad_0 = const()[name = tensor("max_pool_2_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_2_ceil_mode_0 = const()[name = tensor("max_pool_2_ceil_mode_0"), val = tensor(false)]; + tensor 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 = activation_11_cast_fp16)[name = tensor("max_pool_2_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(88)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_51_to_fp16 = const()[name = tensor("transpose_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78272)))]; + tensor 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_51_to_fp16, x = activation_11_cast_fp16)[name = tensor("depthwise_11x_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_1_weight_0_to_fp16 = const()[name = tensor("conv_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79936)))]; + tensor conv_1_bias_0_to_fp16 = const()[name = tensor("conv_1_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85632)))]; + tensor conv_1_cast_fp16 = conv(bias = conv_1_bias_0_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 = conv_1_weight_0_to_fp16, x = activation_11_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor Conv2D_20_perm_0 = const()[name = tensor("Conv2D_20_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor pad_10_mode_0 = const()[name = tensor("pad_10_mode_0"), val = tensor("constant")]; + tensor const_34 = const()[name = tensor("const_34"), val = tensor([0, 0, 0, 8, 0, 0, 0, 0])]; + tensor const_10_to_fp16 = const()[name = tensor("const_10_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_10_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = pad_10_mode_0, pad = const_34, x = max_pool_2_cast_fp16)[name = tensor("pad_10_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_55_to_fp16 = const()[name = tensor("transpose_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85760)))]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102720)))]; + tensor conv2d_12_1_cast_fp16 = conv(bias = const_51_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_55_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor("conv2d_12_1_cast_fp16")]; + tensor classificator_8_cast_fp16 = transpose(perm = Conv2D_18_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_80")]; + tensor reshape_cast_fp16 = reshape(shape = reshape_shape, x = classificator_8_cast_fp16)[name = tensor("reshape_cast_fp16")]; + tensor regressor_8_cast_fp16 = transpose(perm = Conv2D_20_perm_0, x = conv_1_cast_fp16)[name = tensor("transpose_79")]; + tensor reshape_1_1_cast_fp16 = reshape(shape = reshape_1_shape, x = regressor_8_cast_fp16)[name = tensor("reshape_1_1_cast_fp16")]; + tensor add_11__xeno_compat__1_cast_fp16 = add(x = pad_10_cast_fp16, y = conv2d_12_1_cast_fp16)[name = tensor("add_11__xeno_compat__1_cast_fp16")]; + tensor activation_12_cast_fp16 = relu(x = add_11__xeno_compat__1_cast_fp16)[name = tensor("activation_12_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(96)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_57_to_fp16 = const()[name = tensor("transpose_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102976)))]; + tensor 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_57_to_fp16, x = activation_12_cast_fp16)[name = tensor("depthwise_12x_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_59_to_fp16 = const()[name = tensor("transpose_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104768)))]; + tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123264)))]; + tensor conv2d_13_1_cast_fp16 = conv(bias = const_52_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_59_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor("conv2d_13_1_cast_fp16")]; + tensor add_12__xeno_compat__1_cast_fp16 = add(x = activation_12_cast_fp16, y = conv2d_13_1_cast_fp16)[name = tensor("add_12__xeno_compat__1_cast_fp16")]; + tensor activation_13_cast_fp16 = relu(x = add_12__xeno_compat__1_cast_fp16)[name = tensor("activation_13_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(96)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_61_to_fp16 = const()[name = tensor("transpose_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123520)))]; + tensor 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_61_to_fp16, x = activation_13_cast_fp16)[name = tensor("depthwise_13x_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_63_to_fp16 = const()[name = tensor("transpose_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125312)))]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143808)))]; + tensor conv2d_14_1_cast_fp16 = conv(bias = const_53_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_63_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor("conv2d_14_1_cast_fp16")]; + tensor add_13__xeno_compat__1_cast_fp16 = add(x = activation_13_cast_fp16, y = conv2d_14_1_cast_fp16)[name = tensor("add_13__xeno_compat__1_cast_fp16")]; + tensor activation_14_cast_fp16 = relu(x = add_13__xeno_compat__1_cast_fp16)[name = tensor("activation_14_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(96)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_65_to_fp16 = const()[name = tensor("transpose_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144064)))]; + tensor 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_65_to_fp16, x = activation_14_cast_fp16)[name = tensor("depthwise_14x_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_67_to_fp16 = const()[name = tensor("transpose_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145856)))]; + tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164352)))]; + tensor conv2d_15_1_cast_fp16 = conv(bias = const_54_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_67_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor("conv2d_15_1_cast_fp16")]; + tensor add_14__xeno_compat__1_cast_fp16 = add(x = activation_14_cast_fp16, y = conv2d_15_1_cast_fp16)[name = tensor("add_14__xeno_compat__1_cast_fp16")]; + tensor activation_15_cast_fp16 = relu(x = add_14__xeno_compat__1_cast_fp16)[name = tensor("activation_15_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(96)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_69_to_fp16 = const()[name = tensor("transpose_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164608)))]; + tensor 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_69_to_fp16, x = activation_15_cast_fp16)[name = tensor("depthwise_15x_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_71_to_fp16 = const()[name = tensor("transpose_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166400)))]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184896)))]; + tensor conv2d_16_1_cast_fp16 = conv(bias = const_55_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_71_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor("conv2d_16_1_cast_fp16")]; + tensor add_15__xeno_compat__1_cast_fp16 = add(x = activation_15_cast_fp16, y = conv2d_16_1_cast_fp16)[name = tensor("add_15__xeno_compat__1_cast_fp16")]; + tensor activation_16_cast_fp16 = relu(x = add_15__xeno_compat__1_cast_fp16)[name = tensor("activation_16_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_2_weight_0_to_fp16 = const()[name = tensor("conv_2_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185152)))]; + tensor conv_2_bias_0_to_fp16 = const()[name = tensor("conv_2_bias_0_to_fp16"), val = tensor([0x1.3f8p-2, -0x1.974p-4, -0x1.33p-2, -0x1.2dcp-3, 0x1.d7p-2, 0x1.23cp+0])]; + tensor conv_2_cast_fp16 = conv(bias = conv_2_bias_0_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 = conv_2_weight_0_to_fp16, x = activation_16_cast_fp16)[name = tensor("conv_2_cast_fp16")]; + tensor Conv2D_19_perm_0 = const()[name = tensor("Conv2D_19_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_3_weight_0_to_fp16 = const()[name = tensor("conv_3_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186368)))]; + tensor conv_3_bias_0_to_fp16 = const()[name = tensor("conv_3_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204864)))]; + tensor conv_3_cast_fp16 = conv(bias = conv_3_bias_0_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 = conv_3_weight_0_to_fp16, x = activation_16_cast_fp16)[name = tensor("conv_3_cast_fp16")]; + tensor Conv2D_21_perm_0 = const()[name = tensor("Conv2D_21_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor classificator_16_cast_fp16 = transpose(perm = Conv2D_19_perm_0, x = conv_2_cast_fp16)[name = tensor("transpose_78")]; + tensor reshape_2_1_cast_fp16 = reshape(shape = reshape_2_shape, x = classificator_16_cast_fp16)[name = tensor("reshape_2_1_cast_fp16")]; + tensor regressor_16_cast_fp16 = transpose(perm = Conv2D_21_perm_0, x = conv_3_cast_fp16)[name = tensor("transpose_77")]; + tensor reshape_3_1_cast_fp16 = reshape(shape = reshape_3_shape, x = regressor_16_cast_fp16)[name = tensor("reshape_3_1_cast_fp16")]; + tensor classificators_interleave_0 = const()[name = tensor("classificators_interleave_0"), val = tensor(false)]; + tensor classificators_cast_fp16 = concat(axis = classificators_axis, interleave = classificators_interleave_0, values = (reshape_cast_fp16, reshape_2_1_cast_fp16))[name = tensor("classificators_cast_fp16")]; + tensor classificators_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("classificators_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor regressors_interleave_0 = const()[name = tensor("regressors_interleave_0"), val = tensor(false)]; + tensor regressors_cast_fp16 = concat(axis = regressors_axis, interleave = regressors_interleave_0, values = (reshape_1_1_cast_fp16, reshape_3_1_cast_fp16))[name = tensor("regressors_cast_fp16")]; + tensor regressors_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("regressors_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor regressors = cast(dtype = regressors_cast_fp16_to_fp32_dtype_0, x = regressors_cast_fp16)[name = tensor("cast_11")]; + tensor classificators = cast(dtype = classificators_cast_fp16_to_fp32_dtype_0, x = classificators_cast_fp16)[name = tensor("cast_12")]; + } -> (classificators, regressors); +} \ No newline at end of file diff --git a/compiled/face_detection_short_range.mlmodelc/weights/weight.bin b/compiled/face_detection_short_range.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..98e05dc3602e993864827b494bd0aed1ee59bc99 --- /dev/null +++ b/compiled/face_detection_short_range.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:57d6801e4691739cfc3734fd554c2998c016ae19451e0a68d07fce60438753f8 +size 205120 diff --git a/compiled/face_landmark.mlmodelc/analytics/coremldata.bin b/compiled/face_landmark.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..28f4900816397d420129a7f468ebbcfdeec71608 --- /dev/null +++ b/compiled/face_landmark.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d21e8f6adc5d955a7347cd3efc2d26d881a051a94f648b88f43ab05d55cfb793 +size 243 diff --git a/compiled/face_landmark.mlmodelc/coremldata.bin b/compiled/face_landmark.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..0a3c40db7d201c12c1cece093ff39701d0150d6b --- /dev/null +++ b/compiled/face_landmark.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e538e3f76be581f137f750ae440ccff97674b5cfcd383a38a28d76292f26f616 +size 294 diff --git a/compiled/face_landmark.mlmodelc/metadata.json b/compiled/face_landmark.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..94a85ab68bdd4fc1cc966e11189f51923202d039 --- /dev/null +++ b/compiled/face_landmark.mlmodelc/metadata.json @@ -0,0 +1,75 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1 × 1 × 1404)", + "shortDescription" : "", + "shape" : "[1, 1, 1, 1404]", + "name" : "conv2d_21_1", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1 × 1 × 1)", + "shortDescription" : "", + "shape" : "[1, 1, 1, 1]", + "name" : "conv2d_31", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Cast" : 3, + "Conv" : 45, + "Prelu" : 23, + "Pad" : 3, + "Transpose" : 3, + "Add" : 20, + "MaxPool" : 5 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 192 × 192 × 3)", + "shortDescription" : "", + "shape" : "[1, 192, 192, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "face_landmark", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/face_landmark.mlmodelc/model.mil b/compiled/face_landmark.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..c9b59cd8c982ff4fa7b3ed45d9e4789bef5ce236 --- /dev/null +++ b/compiled/face_landmark.mlmodelc/model.mil @@ -0,0 +1,466 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1024)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_5")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_98")]; + tensor conv2d_1_cast_fp16 = conv(bias = const_75_to_fp16, dilations = Conv2Dx_dilations_0, groups = Conv2Dx_groups_0, pad = Conv2Dx_pad_0, pad_type = Conv2Dx_pad_type_0, strides = Conv2Dx_strides_0, weight = transpose_0_to_fp16, x = transpose_1_cast_fp16)[name = tensor("conv2d_1_cast_fp16")]; + tensor p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1152)))]; + tensor p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_1_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_1_cast_fp16)[name = tensor("p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(16)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1280)))]; + tensor depthwisex_cast_fp16 = conv(dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwisex_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1664)))]; + tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2240)))]; + tensor conv2d_2_1_cast_fp16 = conv(bias = const_76_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_4_to_fp16, x = depthwisex_cast_fp16)[name = tensor("conv2d_2_1_cast_fp16")]; + tensor add_1_cast_fp16 = add(x = p_re_lu_1_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_2_1_cast_fp16)[name = tensor("add_1_cast_fp16")]; + tensor p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2368)))]; + tensor p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_2_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_1_cast_fp16)[name = tensor("p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(16)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2496)))]; + tensor depthwise_1x_cast_fp16 = conv(dilations = depthwise_1x_dilations_0, groups = depthwise_1x_groups_0, pad = depthwise_1x_pad_0, pad_type = depthwise_1x_pad_type_0, strides = depthwise_1x_strides_0, weight = transpose_6_to_fp16, x = p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_1x_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2880)))]; + tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3456)))]; + tensor conv2d_3_1_cast_fp16 = conv(bias = const_77_to_fp16, dilations = Conv2D_3x_dilations_0, groups = Conv2D_3x_groups_0, pad = Conv2D_3x_pad_0, pad_type = Conv2D_3x_pad_type_0, strides = Conv2D_3x_strides_0, weight = transpose_8_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor("conv2d_3_1_cast_fp16")]; + tensor add_2_cast_fp16 = add(x = p_re_lu_2_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_3_1_cast_fp16)[name = tensor("add_2_cast_fp16")]; + tensor p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3584)))]; + tensor p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_3_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_2_cast_fp16)[name = tensor("p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("valid")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor max_pool_0_cast_fp16 = max_pool(ceil_mode = max_pool_0_ceil_mode_0, kernel_sizes = max_pool_0_kernel_sizes_0, pad = max_pool_0_pad_0, pad_type = max_pool_0_pad_type_0, strides = max_pool_0_strides_0, x = p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_0_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(16)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_11_to_fp16 = const()[name = tensor("transpose_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3712)))]; + tensor depthwise_2x_cast_fp16 = conv(dilations = depthwise_2x_dilations_0, groups = depthwise_2x_groups_0, pad = depthwise_2x_pad_0, pad_type = depthwise_2x_pad_type_0, strides = depthwise_2x_strides_0, weight = transpose_11_to_fp16, x = p_re_lu_3_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_2x_cast_fp16")]; + tensor pad_0_mode_0 = const()[name = tensor("pad_0_mode_0"), val = tensor("constant")]; + tensor const_32 = const()[name = tensor("const_32"), val = tensor([0, 0, 0, 16, 0, 0, 0, 0])]; + tensor const_3_to_fp16 = const()[name = tensor("const_3_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_0_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = pad_0_mode_0, pad = const_32, x = max_pool_0_cast_fp16)[name = tensor("pad_0_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_13_to_fp16 = const()[name = tensor("transpose_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4096)))]; + tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5184)))]; + tensor conv2d_4_1_cast_fp16 = conv(bias = const_78_to_fp16, dilations = Conv2D_4x_dilations_0, groups = Conv2D_4x_groups_0, pad = Conv2D_4x_pad_0, pad_type = Conv2D_4x_pad_type_0, strides = Conv2D_4x_strides_0, weight = transpose_13_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor("conv2d_4_1_cast_fp16")]; + tensor add_3_cast_fp16 = add(x = pad_0_cast_fp16, y = conv2d_4_1_cast_fp16)[name = tensor("add_3_cast_fp16")]; + tensor p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5312)))]; + tensor p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_4_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_3_cast_fp16)[name = tensor("p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(32)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_15_to_fp16 = const()[name = tensor("transpose_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5440)))]; + tensor depthwise_3x_cast_fp16 = conv(dilations = depthwise_3x_dilations_0, groups = depthwise_3x_groups_0, pad = depthwise_3x_pad_0, pad_type = depthwise_3x_pad_type_0, strides = depthwise_3x_strides_0, weight = transpose_15_to_fp16, x = p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_3x_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_17_to_fp16 = const()[name = tensor("transpose_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6080)))]; + tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8192)))]; + tensor conv2d_5_1_cast_fp16 = conv(bias = const_79_to_fp16, dilations = Conv2D_5x_dilations_0, groups = Conv2D_5x_groups_0, pad = Conv2D_5x_pad_0, pad_type = Conv2D_5x_pad_type_0, strides = Conv2D_5x_strides_0, weight = transpose_17_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor("conv2d_5_1_cast_fp16")]; + tensor add_4_cast_fp16 = add(x = p_re_lu_4_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_5_1_cast_fp16)[name = tensor("add_4_cast_fp16")]; + tensor p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8320)))]; + tensor p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_5_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_4_cast_fp16)[name = tensor("p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(32)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_19_to_fp16 = const()[name = tensor("transpose_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8448)))]; + tensor depthwise_4x_cast_fp16 = conv(dilations = depthwise_4x_dilations_0, groups = depthwise_4x_groups_0, pad = depthwise_4x_pad_0, pad_type = depthwise_4x_pad_type_0, strides = depthwise_4x_strides_0, weight = transpose_19_to_fp16, x = p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_4x_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_21_to_fp16 = const()[name = tensor("transpose_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9088)))]; + tensor const_80_to_fp16 = const()[name = tensor("const_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11200)))]; + tensor conv2d_6_1_cast_fp16 = conv(bias = const_80_to_fp16, dilations = Conv2D_6x_dilations_0, groups = Conv2D_6x_groups_0, pad = Conv2D_6x_pad_0, pad_type = Conv2D_6x_pad_type_0, strides = Conv2D_6x_strides_0, weight = transpose_21_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor("conv2d_6_1_cast_fp16")]; + tensor add_5_cast_fp16 = add(x = p_re_lu_5_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_6_1_cast_fp16)[name = tensor("add_5_cast_fp16")]; + tensor p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11328)))]; + tensor p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_6_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_5_cast_fp16)[name = tensor("p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_1_kernel_sizes_0 = const()[name = tensor("max_pool_1_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_1_strides_0 = const()[name = tensor("max_pool_1_strides_0"), val = tensor([2, 2])]; + tensor max_pool_1_pad_type_0 = const()[name = tensor("max_pool_1_pad_type_0"), val = tensor("valid")]; + tensor max_pool_1_pad_0 = const()[name = tensor("max_pool_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_1_ceil_mode_0 = const()[name = tensor("max_pool_1_ceil_mode_0"), val = tensor(false)]; + tensor max_pool_1_cast_fp16 = max_pool(ceil_mode = max_pool_1_ceil_mode_0, kernel_sizes = max_pool_1_kernel_sizes_0, pad = max_pool_1_pad_0, pad_type = max_pool_1_pad_type_0, strides = max_pool_1_strides_0, x = p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_1_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(32)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_24_to_fp16 = const()[name = tensor("transpose_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11456)))]; + tensor depthwise_5x_cast_fp16 = conv(dilations = depthwise_5x_dilations_0, groups = depthwise_5x_groups_0, pad = depthwise_5x_pad_0, pad_type = depthwise_5x_pad_type_0, strides = depthwise_5x_strides_0, weight = transpose_24_to_fp16, x = p_re_lu_6_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_5x_cast_fp16")]; + tensor pad_1_mode_0 = const()[name = tensor("pad_1_mode_0"), val = tensor("constant")]; + tensor const_43 = const()[name = tensor("const_43"), val = tensor([0, 0, 0, 32, 0, 0, 0, 0])]; + tensor const_7_to_fp16 = const()[name = tensor("const_7_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_1_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = pad_1_mode_0, pad = const_43, x = max_pool_1_cast_fp16)[name = tensor("pad_1_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_26_to_fp16 = const()[name = tensor("transpose_26_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12096)))]; + tensor const_81_to_fp16 = const()[name = tensor("const_81_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16256)))]; + tensor conv2d_7_1_cast_fp16 = conv(bias = const_81_to_fp16, dilations = Conv2D_7x_dilations_0, groups = Conv2D_7x_groups_0, pad = Conv2D_7x_pad_0, pad_type = Conv2D_7x_pad_type_0, strides = Conv2D_7x_strides_0, weight = transpose_26_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor("conv2d_7_1_cast_fp16")]; + tensor add_6_cast_fp16 = add(x = pad_1_cast_fp16, y = conv2d_7_1_cast_fp16)[name = tensor("add_6_cast_fp16")]; + tensor p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16448)))]; + tensor p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_7_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_6_cast_fp16)[name = tensor("p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(64)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_28_to_fp16 = const()[name = tensor("transpose_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16640)))]; + tensor depthwise_6x_cast_fp16 = conv(dilations = depthwise_6x_dilations_0, groups = depthwise_6x_groups_0, pad = depthwise_6x_pad_0, pad_type = depthwise_6x_pad_type_0, strides = depthwise_6x_strides_0, weight = transpose_28_to_fp16, x = p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_6x_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_30_to_fp16 = const()[name = tensor("transpose_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17856)))]; + tensor const_82_to_fp16 = const()[name = tensor("const_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26112)))]; + tensor conv2d_8_1_cast_fp16 = conv(bias = const_82_to_fp16, dilations = Conv2D_8x_dilations_0, groups = Conv2D_8x_groups_0, pad = Conv2D_8x_pad_0, pad_type = Conv2D_8x_pad_type_0, strides = Conv2D_8x_strides_0, weight = transpose_30_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor("conv2d_8_1_cast_fp16")]; + tensor add_7_cast_fp16 = add(x = p_re_lu_7_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_8_1_cast_fp16)[name = tensor("add_7_cast_fp16")]; + tensor p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26304)))]; + tensor p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_8_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_7_cast_fp16)[name = tensor("p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(64)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_32_to_fp16 = const()[name = tensor("transpose_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26496)))]; + tensor depthwise_7x_cast_fp16 = conv(dilations = depthwise_7x_dilations_0, groups = depthwise_7x_groups_0, pad = depthwise_7x_pad_0, pad_type = depthwise_7x_pad_type_0, strides = depthwise_7x_strides_0, weight = transpose_32_to_fp16, x = p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_7x_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_34_to_fp16 = const()[name = tensor("transpose_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27712)))]; + tensor const_83_to_fp16 = const()[name = tensor("const_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35968)))]; + tensor conv2d_9_1_cast_fp16 = conv(bias = const_83_to_fp16, dilations = Conv2D_9x_dilations_0, groups = Conv2D_9x_groups_0, pad = Conv2D_9x_pad_0, pad_type = Conv2D_9x_pad_type_0, strides = Conv2D_9x_strides_0, weight = transpose_34_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor("conv2d_9_1_cast_fp16")]; + tensor add_8_cast_fp16 = add(x = p_re_lu_8_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_9_1_cast_fp16)[name = tensor("add_8_cast_fp16")]; + tensor p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36160)))]; + tensor p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_9_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_8_cast_fp16)[name = tensor("p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_2_kernel_sizes_0 = const()[name = tensor("max_pool_2_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_2_strides_0 = const()[name = tensor("max_pool_2_strides_0"), val = tensor([2, 2])]; + tensor max_pool_2_pad_type_0 = const()[name = tensor("max_pool_2_pad_type_0"), val = tensor("valid")]; + tensor max_pool_2_pad_0 = const()[name = tensor("max_pool_2_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_2_ceil_mode_0 = const()[name = tensor("max_pool_2_ceil_mode_0"), val = tensor(false)]; + tensor max_pool_2_cast_fp16 = max_pool(ceil_mode = max_pool_2_ceil_mode_0, kernel_sizes = max_pool_2_kernel_sizes_0, pad = max_pool_2_pad_0, pad_type = max_pool_2_pad_type_0, strides = max_pool_2_strides_0, x = p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_2_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(64)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_37_to_fp16 = const()[name = tensor("transpose_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36352)))]; + tensor depthwise_8x_cast_fp16 = conv(dilations = depthwise_8x_dilations_0, groups = depthwise_8x_groups_0, pad = depthwise_8x_pad_0, pad_type = depthwise_8x_pad_type_0, strides = depthwise_8x_strides_0, weight = transpose_37_to_fp16, x = p_re_lu_9_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_8x_cast_fp16")]; + tensor pad_2_mode_0 = const()[name = tensor("pad_2_mode_0"), val = tensor("constant")]; + tensor const_50 = const()[name = tensor("const_50"), val = tensor([0, 0, 0, 64, 0, 0, 0, 0])]; + tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_2_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = pad_2_mode_0, pad = const_50, x = max_pool_2_cast_fp16)[name = tensor("pad_2_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_39_to_fp16 = const()[name = tensor("transpose_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37568)))]; + tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54016)))]; + tensor conv2d_10_1_cast_fp16 = conv(bias = const_84_to_fp16, dilations = Conv2D_10x_dilations_0, groups = Conv2D_10x_groups_0, pad = Conv2D_10x_pad_0, pad_type = Conv2D_10x_pad_type_0, strides = Conv2D_10x_strides_0, weight = transpose_39_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor("conv2d_10_1_cast_fp16")]; + tensor add_9_cast_fp16 = add(x = pad_2_cast_fp16, y = conv2d_10_1_cast_fp16)[name = tensor("add_9_cast_fp16")]; + tensor p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54336)))]; + tensor p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_10_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_9_cast_fp16)[name = tensor("p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(128)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_41_to_fp16 = const()[name = tensor("transpose_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54656)))]; + tensor depthwise_9x_cast_fp16 = conv(dilations = depthwise_9x_dilations_0, groups = depthwise_9x_groups_0, pad = depthwise_9x_pad_0, pad_type = depthwise_9x_pad_type_0, strides = depthwise_9x_strides_0, weight = transpose_41_to_fp16, x = p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_9x_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_43_to_fp16 = const()[name = tensor("transpose_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57024)))]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89856)))]; + tensor conv2d_11_1_cast_fp16 = conv(bias = const_85_to_fp16, dilations = Conv2D_11x_dilations_0, groups = Conv2D_11x_groups_0, pad = Conv2D_11x_pad_0, pad_type = Conv2D_11x_pad_type_0, strides = Conv2D_11x_strides_0, weight = transpose_43_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor("conv2d_11_1_cast_fp16")]; + tensor add_10_cast_fp16 = add(x = p_re_lu_10_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_11_1_cast_fp16)[name = tensor("add_10_cast_fp16")]; + tensor p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90176)))]; + tensor p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_11_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_10_cast_fp16)[name = tensor("p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(128)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_45_to_fp16 = const()[name = tensor("transpose_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90496)))]; + tensor depthwise_10x_cast_fp16 = conv(dilations = depthwise_10x_dilations_0, groups = depthwise_10x_groups_0, pad = depthwise_10x_pad_0, pad_type = depthwise_10x_pad_type_0, strides = depthwise_10x_strides_0, weight = transpose_45_to_fp16, x = p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_10x_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_47_to_fp16 = const()[name = tensor("transpose_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92864)))]; + tensor const_86_to_fp16 = const()[name = tensor("const_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125696)))]; + tensor conv2d_12_1_cast_fp16 = conv(bias = const_86_to_fp16, dilations = Conv2D_12x_dilations_0, groups = Conv2D_12x_groups_0, pad = Conv2D_12x_pad_0, pad_type = Conv2D_12x_pad_type_0, strides = Conv2D_12x_strides_0, weight = transpose_47_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor("conv2d_12_1_cast_fp16")]; + tensor add_11_cast_fp16 = add(x = p_re_lu_11_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_12_1_cast_fp16)[name = tensor("add_11_cast_fp16")]; + tensor p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126016)))]; + tensor p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_12_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_11_cast_fp16)[name = tensor("p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_3_kernel_sizes_0 = const()[name = tensor("max_pool_3_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_3_strides_0 = const()[name = tensor("max_pool_3_strides_0"), val = tensor([2, 2])]; + tensor max_pool_3_pad_type_0 = const()[name = tensor("max_pool_3_pad_type_0"), val = tensor("valid")]; + tensor max_pool_3_pad_0 = const()[name = tensor("max_pool_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_3_ceil_mode_0 = const()[name = tensor("max_pool_3_ceil_mode_0"), val = tensor(false)]; + tensor max_pool_3_cast_fp16 = max_pool(ceil_mode = max_pool_3_ceil_mode_0, kernel_sizes = max_pool_3_kernel_sizes_0, pad = max_pool_3_pad_0, pad_type = max_pool_3_pad_type_0, strides = max_pool_3_strides_0, x = p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_3_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(128)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_50_to_fp16 = const()[name = tensor("transpose_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126336)))]; + tensor depthwise_11x_cast_fp16 = conv(dilations = depthwise_11x_dilations_0, groups = depthwise_11x_groups_0, pad = depthwise_11x_pad_0, pad_type = depthwise_11x_pad_type_0, strides = depthwise_11x_strides_0, weight = transpose_50_to_fp16, x = p_re_lu_12_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_11x_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_52_to_fp16 = const()[name = tensor("transpose_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128704)))]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161536)))]; + tensor conv2d_13_1_cast_fp16 = conv(bias = const_87_to_fp16, dilations = Conv2D_13x_dilations_0, groups = Conv2D_13x_groups_0, pad = Conv2D_13x_pad_0, pad_type = Conv2D_13x_pad_type_0, strides = Conv2D_13x_strides_0, weight = transpose_52_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor("conv2d_13_1_cast_fp16")]; + tensor add_12_cast_fp16 = add(x = max_pool_3_cast_fp16, y = conv2d_13_1_cast_fp16)[name = tensor("add_12_cast_fp16")]; + tensor p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161856)))]; + tensor p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_13_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_12_cast_fp16)[name = tensor("p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(128)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_54_to_fp16 = const()[name = tensor("transpose_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162176)))]; + tensor depthwise_12x_cast_fp16 = conv(dilations = depthwise_12x_dilations_0, groups = depthwise_12x_groups_0, pad = depthwise_12x_pad_0, pad_type = depthwise_12x_pad_type_0, strides = depthwise_12x_strides_0, weight = transpose_54_to_fp16, x = p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_12x_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_56_to_fp16 = const()[name = tensor("transpose_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164544)))]; + tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197376)))]; + tensor conv2d_14_1_cast_fp16 = conv(bias = const_88_to_fp16, dilations = Conv2D_14x_dilations_0, groups = Conv2D_14x_groups_0, pad = Conv2D_14x_pad_0, pad_type = Conv2D_14x_pad_type_0, strides = Conv2D_14x_strides_0, weight = transpose_56_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor("conv2d_14_1_cast_fp16")]; + tensor add_13_cast_fp16 = add(x = p_re_lu_13_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_14_1_cast_fp16)[name = tensor("add_13_cast_fp16")]; + tensor p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197696)))]; + tensor p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_14_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_13_cast_fp16)[name = tensor("p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(128)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_58_to_fp16 = const()[name = tensor("transpose_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198016)))]; + tensor depthwise_13x_cast_fp16 = conv(dilations = depthwise_13x_dilations_0, groups = depthwise_13x_groups_0, pad = depthwise_13x_pad_0, pad_type = depthwise_13x_pad_type_0, strides = depthwise_13x_strides_0, weight = transpose_58_to_fp16, x = p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_13x_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_60_to_fp16 = const()[name = tensor("transpose_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200384)))]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233216)))]; + tensor conv2d_15_1_cast_fp16 = conv(bias = const_89_to_fp16, dilations = Conv2D_15x_dilations_0, groups = Conv2D_15x_groups_0, pad = Conv2D_15x_pad_0, pad_type = Conv2D_15x_pad_type_0, strides = Conv2D_15x_strides_0, weight = transpose_60_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor("conv2d_15_1_cast_fp16")]; + tensor add_14_cast_fp16 = add(x = p_re_lu_14_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_15_1_cast_fp16)[name = tensor("add_14_cast_fp16")]; + tensor p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233536)))]; + tensor p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_15_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_14_cast_fp16)[name = tensor("p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_4_kernel_sizes_0 = const()[name = tensor("max_pool_4_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_4_strides_0 = const()[name = tensor("max_pool_4_strides_0"), val = tensor([2, 2])]; + tensor max_pool_4_pad_type_0 = const()[name = tensor("max_pool_4_pad_type_0"), val = tensor("valid")]; + tensor max_pool_4_pad_0 = const()[name = tensor("max_pool_4_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_4_ceil_mode_0 = const()[name = tensor("max_pool_4_ceil_mode_0"), val = tensor(false)]; + tensor max_pool_4_cast_fp16 = max_pool(ceil_mode = max_pool_4_ceil_mode_0, kernel_sizes = max_pool_4_kernel_sizes_0, pad = max_pool_4_pad_0, pad_type = max_pool_4_pad_type_0, strides = max_pool_4_strides_0, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_4_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(128)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_63_to_fp16 = const()[name = tensor("transpose_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233856)))]; + tensor depthwise_14x_cast_fp16 = conv(dilations = depthwise_14x_dilations_0, groups = depthwise_14x_groups_0, pad = depthwise_14x_pad_0, pad_type = depthwise_14x_pad_type_0, strides = depthwise_14x_strides_0, weight = transpose_63_to_fp16, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_14x_cast_fp16")]; + tensor depthwise_16x_pad_type_0 = const()[name = tensor("depthwise_16x_pad_type_0"), val = tensor("same")]; + tensor depthwise_16x_strides_0 = const()[name = tensor("depthwise_16x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_16x_dilations_0 = const()[name = tensor("depthwise_16x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_16x_groups_0 = const()[name = tensor("depthwise_16x_groups_0"), val = tensor(128)]; + tensor depthwise_16x_pad_0 = const()[name = tensor("depthwise_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_66_to_fp16 = const()[name = tensor("transpose_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236224)))]; + tensor depthwise_16x_cast_fp16 = conv(dilations = depthwise_16x_dilations_0, groups = depthwise_16x_groups_0, pad = depthwise_16x_pad_0, pad_type = depthwise_16x_pad_type_0, strides = depthwise_16x_strides_0, weight = transpose_66_to_fp16, x = p_re_lu_15_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_16x_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_68_to_fp16 = const()[name = tensor("transpose_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238592)))]; + tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271424)))]; + tensor conv2d_16_1_cast_fp16 = conv(bias = const_90_to_fp16, dilations = Conv2D_16x_dilations_0, groups = Conv2D_16x_groups_0, pad = Conv2D_16x_pad_0, pad_type = Conv2D_16x_pad_type_0, strides = Conv2D_16x_strides_0, weight = transpose_68_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor("conv2d_16_1_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_70_to_fp16 = const()[name = tensor("transpose_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271744)))]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304576)))]; + tensor conv2d_28_cast_fp16 = conv(bias = const_91_to_fp16, dilations = Conv2D_18x_dilations_0, groups = Conv2D_18x_groups_0, pad = Conv2D_18x_pad_0, pad_type = Conv2D_18x_pad_type_0, strides = Conv2D_18x_strides_0, weight = transpose_70_to_fp16, x = depthwise_16x_cast_fp16)[name = tensor("conv2d_28_cast_fp16")]; + tensor add_15_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_16_1_cast_fp16)[name = tensor("add_15_cast_fp16")]; + tensor add_23_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_28_cast_fp16)[name = tensor("add_23_cast_fp16")]; + tensor p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304896)))]; + tensor p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_16_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_15_cast_fp16)[name = tensor("p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305216)))]; + tensor p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_26_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_23_cast_fp16)[name = tensor("p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(128)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_72_to_fp16 = const()[name = tensor("transpose_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305536)))]; + tensor depthwise_15x_cast_fp16 = conv(dilations = depthwise_15x_dilations_0, groups = depthwise_15x_groups_0, pad = depthwise_15x_pad_0, pad_type = depthwise_15x_pad_type_0, strides = depthwise_15x_strides_0, weight = transpose_72_to_fp16, x = p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_15x_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_74_to_fp16 = const()[name = tensor("transpose_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307904)))]; + tensor const_92_to_fp16 = const()[name = tensor("const_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316160)))]; + tensor conv2d_29_cast_fp16 = conv(bias = const_92_to_fp16, dilations = Conv2D_20x_dilations_0, groups = Conv2D_20x_groups_0, pad = Conv2D_20x_pad_0, pad_type = Conv2D_20x_pad_type_0, strides = Conv2D_20x_strides_0, weight = transpose_74_to_fp16, x = p_re_lu_26_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv2d_29_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_76_to_fp16 = const()[name = tensor("transpose_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316288)))]; + tensor const_93_to_fp16 = const()[name = tensor("const_93_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349120)))]; + tensor conv2d_17_1_cast_fp16 = conv(bias = const_93_to_fp16, dilations = Conv2D_17x_dilations_0, groups = Conv2D_17x_groups_0, pad = Conv2D_17x_pad_0, pad_type = Conv2D_17x_pad_type_0, strides = Conv2D_17x_strides_0, weight = transpose_76_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor("conv2d_17_1_cast_fp16")]; + tensor add_16_cast_fp16 = add(x = p_re_lu_16_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_17_1_cast_fp16)[name = tensor("add_16_cast_fp16")]; + tensor p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349440)))]; + tensor p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_27_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_29_cast_fp16)[name = tensor("p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_18x_pad_type_0 = const()[name = tensor("depthwise_18x_pad_type_0"), val = tensor("same")]; + tensor depthwise_18x_strides_0 = const()[name = tensor("depthwise_18x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_18x_dilations_0 = const()[name = tensor("depthwise_18x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_18x_groups_0 = const()[name = tensor("depthwise_18x_groups_0"), val = tensor(32)]; + tensor depthwise_18x_pad_0 = const()[name = tensor("depthwise_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_78_to_fp16 = const()[name = tensor("transpose_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349568)))]; + tensor depthwise_18x_cast_fp16 = conv(dilations = depthwise_18x_dilations_0, groups = depthwise_18x_groups_0, pad = depthwise_18x_pad_0, pad_type = depthwise_18x_pad_type_0, strides = depthwise_18x_strides_0, weight = transpose_78_to_fp16, x = p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_18x_cast_fp16")]; + tensor p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350208)))]; + tensor p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_17_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_16_cast_fp16)[name = tensor("p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_80_to_fp16 = const()[name = tensor("transpose_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350528)))]; + tensor const_94_to_fp16 = const()[name = tensor("const_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352640)))]; + tensor conv2d_30_cast_fp16 = conv(bias = const_94_to_fp16, dilations = Conv2D_22x_dilations_0, groups = Conv2D_22x_groups_0, pad = Conv2D_22x_pad_0, pad_type = Conv2D_22x_pad_type_0, strides = Conv2D_22x_strides_0, weight = transpose_80_to_fp16, x = depthwise_18x_cast_fp16)[name = tensor("conv2d_30_cast_fp16")]; + tensor depthwise_17x_pad_type_0 = const()[name = tensor("depthwise_17x_pad_type_0"), val = tensor("same")]; + tensor depthwise_17x_strides_0 = const()[name = tensor("depthwise_17x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_17x_dilations_0 = const()[name = tensor("depthwise_17x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_17x_groups_0 = const()[name = tensor("depthwise_17x_groups_0"), val = tensor(128)]; + tensor depthwise_17x_pad_0 = const()[name = tensor("depthwise_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_82_to_fp16 = const()[name = tensor("transpose_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352768)))]; + tensor depthwise_17x_cast_fp16 = conv(dilations = depthwise_17x_dilations_0, groups = depthwise_17x_groups_0, pad = depthwise_17x_pad_0, pad_type = depthwise_17x_pad_type_0, strides = depthwise_17x_strides_0, weight = transpose_82_to_fp16, x = p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_17x_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_84_to_fp16 = const()[name = tensor("transpose_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(355136)))]; + tensor const_95_to_fp16 = const()[name = tensor("const_95_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387968)))]; + tensor conv2d_18_1_cast_fp16 = conv(bias = const_95_to_fp16, dilations = Conv2D_19x_dilations_0, groups = Conv2D_19x_groups_0, pad = Conv2D_19x_pad_0, pad_type = Conv2D_19x_pad_type_0, strides = Conv2D_19x_strides_0, weight = transpose_84_to_fp16, x = depthwise_17x_cast_fp16)[name = tensor("conv2d_18_1_cast_fp16")]; + tensor add_24_cast_fp16 = add(x = p_re_lu_27_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_30_cast_fp16)[name = tensor("add_24_cast_fp16")]; + tensor add_17_cast_fp16 = add(x = p_re_lu_17_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_18_1_cast_fp16)[name = tensor("add_17_cast_fp16")]; + tensor p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388288)))]; + tensor p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_28_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_24_cast_fp16)[name = tensor("p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([3, 3])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388416)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor([-0x1.36cp-2])]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, dilations = Conv2D_24x_dilations_0, groups = Conv2D_24x_groups_0, pad = Conv2D_24x_pad_0, pad_type = Conv2D_24x_pad_type_0, strides = Conv2D_24x_strides_0, weight = conv_0_weight_0_to_fp16, x = p_re_lu_28_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor Conv2D_24_perm_0 = const()[name = tensor("Conv2D_24_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor conv2d_31_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("conv2d_31_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389056)))]; + tensor p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_18_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_17_cast_fp16)[name = tensor("p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_88_to_fp16 = const()[name = tensor("transpose_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389376)))]; + tensor const_96_to_fp16 = const()[name = tensor("const_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397632)))]; + tensor conv2d_19_1_cast_fp16 = conv(bias = const_96_to_fp16, dilations = Conv2D_21x_dilations_0, groups = Conv2D_21x_groups_0, pad = Conv2D_21x_pad_0, pad_type = Conv2D_21x_pad_type_0, strides = Conv2D_21x_strides_0, weight = transpose_88_to_fp16, x = p_re_lu_18_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv2d_19_1_cast_fp16")]; + tensor p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397760)))]; + tensor p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_19_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = conv2d_19_1_cast_fp16)[name = tensor("p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_19x_pad_type_0 = const()[name = tensor("depthwise_19x_pad_type_0"), val = tensor("same")]; + tensor depthwise_19x_strides_0 = const()[name = tensor("depthwise_19x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_19x_dilations_0 = const()[name = tensor("depthwise_19x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_19x_groups_0 = const()[name = tensor("depthwise_19x_groups_0"), val = tensor(32)]; + tensor depthwise_19x_pad_0 = const()[name = tensor("depthwise_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_90_to_fp16 = const()[name = tensor("transpose_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397888)))]; + tensor depthwise_19x_cast_fp16 = conv(dilations = depthwise_19x_dilations_0, groups = depthwise_19x_groups_0, pad = depthwise_19x_pad_0, pad_type = depthwise_19x_pad_type_0, strides = depthwise_19x_strides_0, weight = transpose_90_to_fp16, x = p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_19x_cast_fp16")]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_92_to_fp16 = const()[name = tensor("transpose_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(398528)))]; + tensor const_97_to_fp16 = const()[name = tensor("const_97_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400640)))]; + tensor conv2d_20_1_cast_fp16 = conv(bias = const_97_to_fp16, dilations = Conv2D_23x_dilations_0, groups = Conv2D_23x_groups_0, pad = Conv2D_23x_pad_0, pad_type = Conv2D_23x_pad_type_0, strides = Conv2D_23x_strides_0, weight = transpose_92_to_fp16, x = depthwise_19x_cast_fp16)[name = tensor("conv2d_20_1_cast_fp16")]; + tensor add_18_cast_fp16 = add(x = p_re_lu_19_Alpha_dequantize_prelu_1_add_cast_fp16, y = conv2d_20_1_cast_fp16)[name = tensor("add_18_cast_fp16")]; + tensor p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400768)))]; + tensor p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = p_re_lu_20_Alpha_dequantize_prelu_1_add_alpha_0_to_fp16, x = add_18_cast_fp16)[name = tensor("p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([3, 3])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_1_weight_0_to_fp16 = const()[name = tensor("conv_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400896)))]; + tensor conv_1_bias_0_to_fp16 = const()[name = tensor("conv_1_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1209664)))]; + tensor conv_1_cast_fp16 = conv(bias = conv_1_bias_0_to_fp16, dilations = Conv2D_25x_dilations_0, groups = Conv2D_25x_groups_0, pad = Conv2D_25x_pad_0, pad_type = Conv2D_25x_pad_type_0, strides = Conv2D_25x_strides_0, weight = conv_1_weight_0_to_fp16, x = p_re_lu_20_Alpha_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor Conv2D_25_perm_0 = const()[name = tensor("Conv2D_25_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor conv2d_21_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("conv2d_21_1_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor conv2d_21_1_cast_fp16 = transpose(perm = Conv2D_25_perm_0, x = conv_1_cast_fp16)[name = tensor("transpose_96")]; + tensor conv2d_21_1 = cast(dtype = conv2d_21_1_cast_fp16_to_fp32_dtype_0, x = conv2d_21_1_cast_fp16)[name = tensor("cast_3")]; + tensor conv2d_31_cast_fp16 = transpose(perm = Conv2D_24_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_97")]; + tensor conv2d_31 = cast(dtype = conv2d_31_cast_fp16_to_fp32_dtype_0, x = conv2d_31_cast_fp16)[name = tensor("cast_4")]; + } -> (conv2d_21_1, conv2d_31); +} \ No newline at end of file diff --git a/compiled/face_landmark.mlmodelc/weights/weight.bin b/compiled/face_landmark.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..3bc41206850333aa2680a5fb7c26c27178f5ede7 --- /dev/null +++ b/compiled/face_landmark.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:da5fc514baaf96f67f0931b5ed66f1d62b685121198f1f56f96effba8296c614 +size 1212536 diff --git a/compiled/hand_landmark_full.mlmodelc/analytics/coremldata.bin b/compiled/hand_landmark_full.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..f7a23bfed13e86c980c3fb0524dc86aa7b2b5006 --- /dev/null +++ b/compiled/hand_landmark_full.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a268f08e6318faca3190d18820d653431479563f8b53f50e79eef4fb99c44075 +size 243 diff --git a/compiled/hand_landmark_full.mlmodelc/coremldata.bin b/compiled/hand_landmark_full.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..3ce43758dffc7b42755ec7dd7a2ba89716a5cfb1 --- /dev/null +++ b/compiled/hand_landmark_full.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:13c78e7135cac87c82adf0148bcaa8096899884712491f298b4e6f4ed54efef4 +size 339 diff --git a/compiled/hand_landmark_full.mlmodelc/metadata.json b/compiled/hand_landmark_full.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..7c399ec8ca0b3dcc3cc123c0a373a620990eea2f --- /dev/null +++ b/compiled/hand_landmark_full.mlmodelc/metadata.json @@ -0,0 +1,96 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 63)", + "shortDescription" : "", + "shape" : "[1, 63]", + "name" : "Identity", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1)", + "shortDescription" : "", + "shape" : "[1, 1]", + "name" : "Identity_1", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1)", + "shortDescription" : "", + "shape" : "[1, 1]", + "name" : "Identity_2", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 63)", + "shortDescription" : "", + "shape" : "[1, 63]", + "name" : "Identity_3", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Linear" : 4, + "Relu6" : 32, + "Cast" : 5, + "Conv" : 47, + "Sigmoid" : 2, + "Transpose" : 2, + "Add" : 9, + "ReduceMean" : 1 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 224 × 224 × 3)", + "shortDescription" : "", + "shape" : "[1, 224, 224, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "hand_landmark_full", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/hand_landmark_full.mlmodelc/model.mil b/compiled/hand_landmark_full.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..339e4e51f33074697c0a0302a18ec47560175f32 --- /dev/null +++ b/compiled/hand_landmark_full.mlmodelc/model.mil @@ -0,0 +1,454 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1472)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_4")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_99")]; + tensor Add_cast_fp16 = conv(bias = const_46_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("Add_cast_fp16")]; + tensor model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16 = relu6(x = Add_cast_fp16)[name = tensor("model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(24)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1600)))]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2112)))]; + tensor Add_1_cast_fp16 = conv(bias = const_47_to_fp16, dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16)[name = tensor("Add_1_cast_fp16")]; + tensor model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_cast_fp16 = relu6(x = Add_1_cast_fp16)[name = tensor("model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_cast_fp16")]; + tensor Conv2D_1x_pad_type_0 = const()[name = tensor("Conv2D_1x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_1x_strides_0 = const()[name = tensor("Conv2D_1x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_dilations_0 = const()[name = tensor("Conv2D_1x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_groups_0 = const()[name = tensor("Conv2D_1x_groups_0"), val = tensor(1)]; + tensor Conv2D_1x_pad_0 = const()[name = tensor("Conv2D_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2240)))]; + tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3072)))]; + tensor model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_1_Conv2D1_cast_fp16 = conv(bias = const_48_to_fp16, dilations = Conv2D_1x_dilations_0, groups = Conv2D_1x_groups_0, pad = Conv2D_1x_pad_0, pad_type = Conv2D_1x_pad_type_0, strides = Conv2D_1x_strides_0, weight = transpose_4_to_fp16, x = model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_5_Conv2D_cast_fp16)[name = tensor("model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_1_Conv2D1_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3200)))]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5312)))]; + tensor Add_2_cast_fp16 = conv(bias = const_49_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_6_to_fp16, x = model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_1_Conv2D1_cast_fp16)[name = tensor("Add_2_cast_fp16")]; + tensor model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_2_Conv2D_cast_fp16 = relu6(x = Add_2_cast_fp16)[name = tensor("model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_2_Conv2D_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(64)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5504)))]; + tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6720)))]; + tensor Add_3_cast_fp16 = conv(bias = const_50_to_fp16, 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_8_to_fp16, x = model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_2_Conv2D_cast_fp16)[name = tensor("Add_3_cast_fp16")]; + tensor model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_cast_fp16 = relu6(x = Add_3_cast_fp16)[name = tensor("model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_10_to_fp16 = const()[name = tensor("transpose_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6912)))]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10048)))]; + tensor model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16 = conv(bias = const_51_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_10_to_fp16, x = model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_12_to_fp16 = const()[name = tensor("transpose_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10176)))]; + tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17152)))]; + tensor Add_4_cast_fp16 = conv(bias = const_52_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_12_to_fp16, x = model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16)[name = tensor("Add_4_cast_fp16")]; + tensor model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16 = relu6(x = Add_4_cast_fp16)[name = tensor("model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(144)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_14_to_fp16 = const()[name = tensor("transpose_14_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17536)))]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20224)))]; + tensor Add_5_cast_fp16 = conv(bias = const_53_to_fp16, 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_14_to_fp16, x = model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16)[name = tensor("Add_5_cast_fp16")]; + tensor model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16 = relu6(x = Add_5_cast_fp16)[name = tensor("model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_16_to_fp16 = const()[name = tensor("transpose_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20608)))]; + tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27584)))]; + tensor model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16 = conv(bias = const_54_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_16_to_fp16, x = model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16")]; + tensor model_1_model_add_add_cast_fp16 = add(x = model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_add_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_18_to_fp16 = const()[name = tensor("transpose_18_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27712)))]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34688)))]; + tensor Add_6_cast_fp16 = conv(bias = const_55_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_18_to_fp16, x = model_1_model_add_add_cast_fp16)[name = tensor("Add_6_cast_fp16")]; + tensor model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16 = relu6(x = Add_6_cast_fp16)[name = tensor("model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(144)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_20_to_fp16 = const()[name = tensor("transpose_20_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35072)))]; + tensor const_56_to_fp16 = const()[name = tensor("const_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42368)))]; + tensor Add_7_cast_fp16 = conv(bias = const_56_to_fp16, 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_20_to_fp16, x = model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16)[name = tensor("Add_7_cast_fp16")]; + tensor model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16 = relu6(x = Add_7_cast_fp16)[name = tensor("model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_22_to_fp16 = const()[name = tensor("transpose_22_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42752)))]; + tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54336)))]; + tensor model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16 = conv(bias = const_57_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_22_to_fp16, x = model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_24_to_fp16 = const()[name = tensor("transpose_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54528)))]; + tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73792)))]; + tensor Add_8_cast_fp16 = conv(bias = const_58_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_24_to_fp16, x = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("Add_8_cast_fp16")]; + tensor model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16 = relu6(x = Add_8_cast_fp16)[name = tensor("model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(240)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_26_to_fp16 = const()[name = tensor("transpose_26_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74368)))]; + tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86464)))]; + tensor Add_9_cast_fp16 = conv(bias = const_59_to_fp16, 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_26_to_fp16, x = model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16)[name = tensor("Add_9_cast_fp16")]; + tensor model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16 = relu6(x = Add_9_cast_fp16)[name = tensor("model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_28_to_fp16 = const()[name = tensor("transpose_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87040)))]; + tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106304)))]; + tensor model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16 = conv(bias = const_60_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_28_to_fp16, x = model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16")]; + tensor model_1_model_add_1_add_cast_fp16 = add(x = model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_1_add_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_30_to_fp16 = const()[name = tensor("transpose_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106496)))]; + tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125760)))]; + tensor Add_10_cast_fp16 = conv(bias = const_61_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_30_to_fp16, x = model_1_model_add_1_add_cast_fp16)[name = tensor("Add_10_cast_fp16")]; + tensor model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16 = relu6(x = Add_10_cast_fp16)[name = tensor("model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(240)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_32_to_fp16 = const()[name = tensor("transpose_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126336)))]; + tensor const_62_to_fp16 = const()[name = tensor("const_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130752)))]; + tensor Add_11_cast_fp16 = conv(bias = const_62_to_fp16, 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_32_to_fp16, x = model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16)[name = tensor("Add_11_cast_fp16")]; + tensor model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16 = relu6(x = Add_11_cast_fp16)[name = tensor("model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_34_to_fp16 = const()[name = tensor("transpose_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131328)))]; + tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169792)))]; + tensor model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16 = conv(bias = const_63_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_34_to_fp16, x = model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_36_to_fp16 = const()[name = tensor("transpose_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170048)))]; + tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246912)))]; + tensor Add_12_cast_fp16 = conv(bias = const_64_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_36_to_fp16, x = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("Add_12_cast_fp16")]; + tensor model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16 = relu6(x = Add_12_cast_fp16)[name = tensor("model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(480)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_38_to_fp16 = const()[name = tensor("transpose_38_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247936)))]; + tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256640)))]; + tensor Add_13_cast_fp16 = conv(bias = const_65_to_fp16, 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_38_to_fp16, x = model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16)[name = tensor("Add_13_cast_fp16")]; + tensor model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16 = relu6(x = Add_13_cast_fp16)[name = tensor("model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_40_to_fp16 = const()[name = tensor("transpose_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257664)))]; + tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334528)))]; + tensor model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16 = conv(bias = const_66_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_40_to_fp16, x = model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16")]; + tensor model_1_model_add_2_add_cast_fp16 = add(x = model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_2_add_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_42_to_fp16 = const()[name = tensor("transpose_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334784)))]; + tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(411648)))]; + tensor Add_14_cast_fp16 = conv(bias = const_67_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_42_to_fp16, x = model_1_model_add_2_add_cast_fp16)[name = tensor("Add_14_cast_fp16")]; + tensor model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16 = relu6(x = Add_14_cast_fp16)[name = tensor("model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(480)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_44_to_fp16 = const()[name = tensor("transpose_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412672)))]; + tensor const_68_to_fp16 = const()[name = tensor("const_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421376)))]; + tensor Add_15_cast_fp16 = conv(bias = const_68_to_fp16, 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_44_to_fp16, x = model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16)[name = tensor("Add_15_cast_fp16")]; + tensor model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16 = relu6(x = Add_15_cast_fp16)[name = tensor("model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_46_to_fp16 = const()[name = tensor("transpose_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422400)))]; + tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(499264)))]; + tensor model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16 = conv(bias = const_69_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_46_to_fp16, x = model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16")]; + tensor model_1_model_add_3_add_cast_fp16 = add(x = model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16, y = model_1_model_add_2_add_cast_fp16)[name = tensor("model_1_model_add_3_add_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_48_to_fp16 = const()[name = tensor("transpose_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(499520)))]; + tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(576384)))]; + tensor Add_16_cast_fp16 = conv(bias = const_70_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_48_to_fp16, x = model_1_model_add_3_add_cast_fp16)[name = tensor("Add_16_cast_fp16")]; + tensor model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16 = relu6(x = Add_16_cast_fp16)[name = tensor("model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(480)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_50_to_fp16 = const()[name = tensor("transpose_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(577408)))]; + tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(601472)))]; + tensor Add_17_cast_fp16 = conv(bias = const_71_to_fp16, 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_50_to_fp16, x = model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16)[name = tensor("Add_17_cast_fp16")]; + tensor model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16 = relu6(x = Add_17_cast_fp16)[name = tensor("model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_52_to_fp16 = const()[name = tensor("transpose_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(602496)))]; + tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(710080)))]; + tensor model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16 = conv(bias = const_72_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_52_to_fp16, x = model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_54_to_fp16 = const()[name = tensor("transpose_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(710400)))]; + tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(860992)))]; + tensor Add_18_cast_fp16 = conv(bias = const_73_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_54_to_fp16, x = model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("Add_18_cast_fp16")]; + tensor model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16 = relu6(x = Add_18_cast_fp16)[name = tensor("model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(672)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_56_to_fp16 = const()[name = tensor("transpose_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(862400)))]; + tensor const_74_to_fp16 = const()[name = tensor("const_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(896064)))]; + tensor Add_19_cast_fp16 = conv(bias = const_74_to_fp16, 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_56_to_fp16, x = model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16)[name = tensor("Add_19_cast_fp16")]; + tensor model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16 = relu6(x = Add_19_cast_fp16)[name = tensor("model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_58_to_fp16 = const()[name = tensor("transpose_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(897472)))]; + tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1048064)))]; + tensor model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16 = conv(bias = const_75_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_58_to_fp16, x = model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16")]; + tensor model_1_model_add_4_add_cast_fp16 = add(x = model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_4_add_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_60_to_fp16 = const()[name = tensor("transpose_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1048384)))]; + tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1198976)))]; + tensor Add_20_cast_fp16 = conv(bias = const_76_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_60_to_fp16, x = model_1_model_add_4_add_cast_fp16)[name = tensor("Add_20_cast_fp16")]; + tensor model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16 = relu6(x = Add_20_cast_fp16)[name = tensor("model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(672)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_62_to_fp16 = const()[name = tensor("transpose_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1200384)))]; + tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1234048)))]; + tensor Add_21_cast_fp16 = conv(bias = const_77_to_fp16, 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_62_to_fp16, x = model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16)[name = tensor("Add_21_cast_fp16")]; + tensor model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_depthwise_conv2d_10_depthwise_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16 = relu6(x = Add_21_cast_fp16)[name = tensor("model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_depthwise_conv2d_10_depthwise_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_64_to_fp16 = const()[name = tensor("transpose_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1235456)))]; + tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1386048)))]; + tensor model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16 = conv(bias = const_78_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_64_to_fp16, x = model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_depthwise_conv2d_10_depthwise_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16")]; + tensor model_1_model_add_5_add_cast_fp16 = add(x = model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16, y = model_1_model_add_4_add_cast_fp16)[name = tensor("model_1_model_add_5_add_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_66_to_fp16 = const()[name = tensor("transpose_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1386368)))]; + tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1536960)))]; + tensor Add_22_cast_fp16 = conv(bias = const_79_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_66_to_fp16, x = model_1_model_add_5_add_cast_fp16)[name = tensor("Add_22_cast_fp16")]; + tensor model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16 = relu6(x = Add_22_cast_fp16)[name = tensor("model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(672)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_68_to_fp16 = const()[name = tensor("transpose_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1538368)))]; + tensor const_80_to_fp16 = const()[name = tensor("const_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1572032)))]; + tensor Add_23_cast_fp16 = conv(bias = const_80_to_fp16, 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_68_to_fp16, x = model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16)[name = tensor("Add_23_cast_fp16")]; + tensor model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16 = relu6(x = Add_23_cast_fp16)[name = tensor("model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16")]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_70_to_fp16 = const()[name = tensor("transpose_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1573440)))]; + tensor const_81_to_fp16 = const()[name = tensor("const_81_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1831552)))]; + tensor model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16 = conv(bias = const_81_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_70_to_fp16, x = model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_72_to_fp16 = const()[name = tensor("transpose_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1832000)))]; + tensor const_82_to_fp16 = const()[name = tensor("const_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2274432)))]; + tensor Add_24_cast_fp16 = conv(bias = const_82_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_72_to_fp16, x = model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16)[name = tensor("Add_24_cast_fp16")]; + tensor model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16 = relu6(x = Add_24_cast_fp16)[name = tensor("model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(1152)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_74_to_fp16 = const()[name = tensor("transpose_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2276800)))]; + tensor const_83_to_fp16 = const()[name = tensor("const_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2334464)))]; + tensor Add_25_cast_fp16 = conv(bias = const_83_to_fp16, 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_74_to_fp16, x = model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16)[name = tensor("Add_25_cast_fp16")]; + tensor model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_25_cast_fp16)[name = tensor("model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_76_to_fp16 = const()[name = tensor("transpose_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2336832)))]; + tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2779264)))]; + tensor model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16 = conv(bias = const_84_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_76_to_fp16, x = model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16")]; + tensor model_1_model_add_6_add_cast_fp16 = add(x = model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_6_add_cast_fp16")]; + tensor Conv2D_26x_pad_type_0 = const()[name = tensor("Conv2D_26x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_26x_strides_0 = const()[name = tensor("Conv2D_26x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_dilations_0 = const()[name = tensor("Conv2D_26x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_groups_0 = const()[name = tensor("Conv2D_26x_groups_0"), val = tensor(1)]; + tensor Conv2D_26x_pad_0 = const()[name = tensor("Conv2D_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_78_to_fp16 = const()[name = tensor("transpose_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2779712)))]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3222144)))]; + tensor Add_26_cast_fp16 = conv(bias = const_85_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_78_to_fp16, x = model_1_model_add_6_add_cast_fp16)[name = tensor("Add_26_cast_fp16")]; + tensor model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16 = relu6(x = Add_26_cast_fp16)[name = tensor("model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(1152)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_80_to_fp16 = const()[name = tensor("transpose_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3224512)))]; + tensor const_86_to_fp16 = const()[name = tensor("const_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3282176)))]; + tensor Add_27_cast_fp16 = conv(bias = const_86_to_fp16, 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_80_to_fp16, x = model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16)[name = tensor("Add_27_cast_fp16")]; + tensor model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_27_cast_fp16)[name = tensor("model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_27x_pad_type_0 = const()[name = tensor("Conv2D_27x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_27x_strides_0 = const()[name = tensor("Conv2D_27x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_dilations_0 = const()[name = tensor("Conv2D_27x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_groups_0 = const()[name = tensor("Conv2D_27x_groups_0"), val = tensor(1)]; + tensor Conv2D_27x_pad_0 = const()[name = tensor("Conv2D_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_82_to_fp16 = const()[name = tensor("transpose_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3284544)))]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3726976)))]; + tensor model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16 = conv(bias = const_87_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_82_to_fp16, x = model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16")]; + tensor model_1_model_add_7_add_cast_fp16 = add(x = model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16, y = model_1_model_add_6_add_cast_fp16)[name = tensor("model_1_model_add_7_add_cast_fp16")]; + tensor Conv2D_28x_pad_type_0 = const()[name = tensor("Conv2D_28x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_28x_strides_0 = const()[name = tensor("Conv2D_28x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_dilations_0 = const()[name = tensor("Conv2D_28x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_groups_0 = const()[name = tensor("Conv2D_28x_groups_0"), val = tensor(1)]; + tensor Conv2D_28x_pad_0 = const()[name = tensor("Conv2D_28x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_84_to_fp16 = const()[name = tensor("transpose_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3727424)))]; + tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4169856)))]; + tensor Add_28_cast_fp16 = conv(bias = const_88_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_84_to_fp16, x = model_1_model_add_7_add_cast_fp16)[name = tensor("Add_28_cast_fp16")]; + tensor model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16 = relu6(x = Add_28_cast_fp16)[name = tensor("model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(1152)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_86_to_fp16 = const()[name = tensor("transpose_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4172224)))]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4229888)))]; + tensor Add_29_cast_fp16 = conv(bias = const_89_to_fp16, 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_86_to_fp16, x = model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16)[name = tensor("Add_29_cast_fp16")]; + tensor model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_29_cast_fp16)[name = tensor("model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_29x_pad_type_0 = const()[name = tensor("Conv2D_29x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_29x_strides_0 = const()[name = tensor("Conv2D_29x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_dilations_0 = const()[name = tensor("Conv2D_29x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_groups_0 = const()[name = tensor("Conv2D_29x_groups_0"), val = tensor(1)]; + tensor Conv2D_29x_pad_0 = const()[name = tensor("Conv2D_29x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_88_to_fp16 = const()[name = tensor("transpose_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4232256)))]; + tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4674688)))]; + tensor model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16 = conv(bias = const_90_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_88_to_fp16, x = model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16")]; + tensor model_1_model_add_8_add_cast_fp16 = add(x = model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16, y = model_1_model_add_7_add_cast_fp16)[name = tensor("model_1_model_add_8_add_cast_fp16")]; + tensor Conv2D_30x_pad_type_0 = const()[name = tensor("Conv2D_30x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_30x_strides_0 = const()[name = tensor("Conv2D_30x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_dilations_0 = const()[name = tensor("Conv2D_30x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_groups_0 = const()[name = tensor("Conv2D_30x_groups_0"), val = tensor(1)]; + tensor Conv2D_30x_pad_0 = const()[name = tensor("Conv2D_30x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_90_to_fp16 = const()[name = tensor("transpose_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4675136)))]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5117568)))]; + tensor Add_30_cast_fp16 = conv(bias = const_91_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_90_to_fp16, x = model_1_model_add_8_add_cast_fp16)[name = tensor("Add_30_cast_fp16")]; + tensor model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16 = relu6(x = Add_30_cast_fp16)[name = tensor("model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(1152)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5119936)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5140736)))]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, 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 = conv_0_weight_0_to_fp16, x = model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor depthwise_15_perm_0 = const()[name = tensor("depthwise_15_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Add_31_cast_fp16 = transpose(perm = depthwise_15_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_98")]; + tensor model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_31_cast_fp16)[name = tensor("model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor model_1_model_global_average_pooling2d_Mean_axes_0 = const()[name = tensor("model_1_model_global_average_pooling2d_Mean_axes_0"), val = tensor([1, 2])]; + tensor model_1_model_global_average_pooling2d_Mean_keep_dims_0 = const()[name = tensor("model_1_model_global_average_pooling2d_Mean_keep_dims_0"), val = tensor(false)]; + tensor model_1_model_global_average_pooling2d_Mean_cast_fp16 = reduce_mean(axes = model_1_model_global_average_pooling2d_Mean_axes_0, keep_dims = model_1_model_global_average_pooling2d_Mean_keep_dims_0, x = model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_global_average_pooling2d_Mean_cast_fp16")]; + tensor transpose_94_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_94_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5143104)))]; + tensor Identity_bias_0_to_fp16 = const()[name = tensor("Identity_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5288320)))]; + tensor Identity_cast_fp16 = linear(bias = Identity_bias_0_to_fp16, weight = transpose_94_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("Identity_cast_fp16")]; + tensor Identity_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor transpose_95_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_95_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5288512)))]; + tensor model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16 = const()[name = tensor("model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16"), val = tensor([0x1.56p-3])]; + tensor model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16 = linear(bias = model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16, weight = transpose_95_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16")]; + tensor transpose_96_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_96_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5290880)))]; + tensor model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16 = const()[name = tensor("model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16"), val = tensor([-0x1.5a4p-8])]; + tensor model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16 = linear(bias = model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16, weight = transpose_96_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16")]; + tensor transpose_97_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_97_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5293248)))]; + tensor Identity_3_bias_0_to_fp16 = const()[name = tensor("Identity_3_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5438464)))]; + tensor Identity_3_cast_fp16 = linear(bias = Identity_3_bias_0_to_fp16, weight = transpose_97_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("Identity_3_cast_fp16")]; + tensor Identity_3_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_3_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1_cast_fp16 = sigmoid(x = model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16)[name = tensor("Identity_1_cast_fp16")]; + tensor Identity_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_1_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_2_cast_fp16 = sigmoid(x = model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16)[name = tensor("Identity_2_cast_fp16")]; + tensor Identity_2_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_2_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_2 = cast(dtype = Identity_2_cast_fp16_to_fp32_dtype_0, x = Identity_2_cast_fp16)[name = tensor("cast_0")]; + tensor Identity_1 = cast(dtype = Identity_1_cast_fp16_to_fp32_dtype_0, x = Identity_1_cast_fp16)[name = tensor("cast_1")]; + tensor Identity_3 = cast(dtype = Identity_3_cast_fp16_to_fp32_dtype_0, x = Identity_3_cast_fp16)[name = tensor("cast_2")]; + tensor Identity = cast(dtype = Identity_cast_fp16_to_fp32_dtype_0, x = Identity_cast_fp16)[name = tensor("cast_3")]; + } -> (Identity, Identity_1, Identity_2, Identity_3); +} \ No newline at end of file diff --git a/compiled/hand_landmark_full.mlmodelc/weights/weight.bin b/compiled/hand_landmark_full.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..fd84947b27f22ae8b9a298203277de1e312d3d6b --- /dev/null +++ b/compiled/hand_landmark_full.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:acc3ed6c4b578362d20343862c7c86e0a31c87847f447d556f3e41288cf3b81b +size 5438654 diff --git a/compiled/hand_landmark_lite.mlmodelc/analytics/coremldata.bin b/compiled/hand_landmark_lite.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..7203500030c519b24624dd6dc3768bed69afcf94 --- /dev/null +++ b/compiled/hand_landmark_lite.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8f2851f82dbd7e046c1d862dff52219a3bd6064bcda3e291685f8a9d8cc036f8 +size 243 diff --git a/compiled/hand_landmark_lite.mlmodelc/coremldata.bin b/compiled/hand_landmark_lite.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..8de75d40290ca1ef8f20915d2db6889b1f4c48c7 --- /dev/null +++ b/compiled/hand_landmark_lite.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fec7d8c93f25c5cf2f7d3752a294380bc297f45b120b69c68e3d831d8986b790 +size 339 diff --git a/compiled/hand_landmark_lite.mlmodelc/metadata.json b/compiled/hand_landmark_lite.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c728f40b3ba8e982158aea73706390e86e48c6f1 --- /dev/null +++ b/compiled/hand_landmark_lite.mlmodelc/metadata.json @@ -0,0 +1,97 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 63)", + "shortDescription" : "", + "shape" : "[1, 63]", + "name" : "Identity", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1)", + "shortDescription" : "", + "shape" : "[1, 1]", + "name" : "Identity_1", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 1)", + "shortDescription" : "", + "shape" : "[1, 1]", + "name" : "Identity_2", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 63)", + "shortDescription" : "", + "shape" : "[1, 63]", + "name" : "Identity_3", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Relu6" : 32, + "Linear" : 4, + "Cast" : 5, + "Conv" : 47, + "Sigmoid" : 2, + "Transpose" : 2, + "Add" : 10, + "ReduceMean" : 1, + "MaxPool" : 1 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 224 × 224 × 3)", + "shortDescription" : "", + "shape" : "[1, 224, 224, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "hand_landmark_lite", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/hand_landmark_lite.mlmodelc/model.mil b/compiled/hand_landmark_lite.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..fadff4a52d74e4d61e29fe213eaa6cc9f38d17a4 --- /dev/null +++ b/compiled/hand_landmark_lite.mlmodelc/model.mil @@ -0,0 +1,461 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1472)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_4")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_100")]; + tensor Add_cast_fp16 = conv(bias = const_46_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("Add_cast_fp16")]; + tensor model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16 = relu6(x = Add_cast_fp16)[name = tensor("model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(24)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1600)))]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2112)))]; + tensor Add_1_cast_fp16 = conv(bias = const_47_to_fp16, dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = model_1_model_re_lu_Relu6_model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_Conv2D_cast_fp16)[name = tensor("Add_1_cast_fp16")]; + tensor model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_cast_fp16 = relu6(x = Add_1_cast_fp16)[name = tensor("model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_cast_fp16")]; + tensor Conv2D_1x_pad_type_0 = const()[name = tensor("Conv2D_1x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_1x_strides_0 = const()[name = tensor("Conv2D_1x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_dilations_0 = const()[name = tensor("Conv2D_1x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_groups_0 = const()[name = tensor("Conv2D_1x_groups_0"), val = tensor(1)]; + tensor Conv2D_1x_pad_0 = const()[name = tensor("Conv2D_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2240)))]; + tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3072)))]; + tensor model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_1_Conv2D1_cast_fp16 = conv(bias = const_48_to_fp16, dilations = Conv2D_1x_dilations_0, groups = Conv2D_1x_groups_0, pad = Conv2D_1x_pad_0, pad_type = Conv2D_1x_pad_type_0, strides = Conv2D_1x_strides_0, weight = transpose_4_to_fp16, x = model_1_model_re_lu_1_Relu6_model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_depthwise_model_1_model_conv2d_9_Conv2D_cast_fp16)[name = tensor("model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_1_Conv2D1_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3200)))]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5312)))]; + tensor Add_2_cast_fp16 = conv(bias = const_49_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_6_to_fp16, x = model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_1_Conv2D1_cast_fp16)[name = tensor("Add_2_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("valid")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_1_Conv2D1_cast_fp16)[name = tensor("max_pool_0_cast_fp16")]; + tensor model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_2_Conv2D_cast_fp16 = relu6(x = Add_2_cast_fp16)[name = tensor("model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_2_Conv2D_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(64)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_9_to_fp16 = const()[name = tensor("transpose_9_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5504)))]; + tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6720)))]; + tensor Add_3_cast_fp16 = conv(bias = const_50_to_fp16, 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_9_to_fp16, x = model_1_model_re_lu_2_Relu6_model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_2_Conv2D_cast_fp16)[name = tensor("Add_3_cast_fp16")]; + tensor model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_cast_fp16 = relu6(x = Add_3_cast_fp16)[name = tensor("model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_11_to_fp16 = const()[name = tensor("transpose_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6912)))]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9024)))]; + tensor model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16 = conv(bias = const_51_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_11_to_fp16, x = model_1_model_re_lu_3_Relu6_model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_1_depthwise_model_1_model_conv2d_21_Conv2D_cast_fp16)[name = tensor("model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16")]; + tensor model_1_model_add_add_cast_fp16 = add(x = model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D_model_1_model_conv2d_3_Conv2D1_cast_fp16, y = max_pool_0_cast_fp16)[name = tensor("model_1_model_add_add_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_13_to_fp16 = const()[name = tensor("transpose_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9152)))]; + tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12288)))]; + tensor Add_4_cast_fp16 = conv(bias = const_52_to_fp16, dilations = Conv2D_4x_dilations_0, groups = Conv2D_4x_groups_0, pad = Conv2D_4x_pad_0, pad_type = Conv2D_4x_pad_type_0, strides = Conv2D_4x_strides_0, weight = transpose_13_to_fp16, x = model_1_model_add_add_cast_fp16)[name = tensor("Add_4_cast_fp16")]; + tensor model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16 = relu6(x = Add_4_cast_fp16)[name = tensor("model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(96)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_15_to_fp16 = const()[name = tensor("transpose_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12544)))]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14336)))]; + tensor Add_5_cast_fp16 = conv(bias = const_53_to_fp16, 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_15_to_fp16, x = model_1_model_re_lu_4_Relu6_model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_4_Conv2D_cast_fp16)[name = tensor("Add_5_cast_fp16")]; + tensor model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16 = relu6(x = Add_5_cast_fp16)[name = tensor("model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_17_to_fp16 = const()[name = tensor("transpose_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14592)))]; + tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17728)))]; + tensor model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16 = conv(bias = const_54_to_fp16, dilations = Conv2D_5x_dilations_0, groups = Conv2D_5x_groups_0, pad = Conv2D_5x_pad_0, pad_type = Conv2D_5x_pad_type_0, strides = Conv2D_5x_strides_0, weight = transpose_17_to_fp16, x = model_1_model_re_lu_5_Relu6_model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_depthwise_conv2d_2_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16")]; + tensor model_1_model_add_1_add_cast_fp16 = add(x = model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_5_Conv2D1_cast_fp16, y = model_1_model_add_add_cast_fp16)[name = tensor("model_1_model_add_1_add_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_19_to_fp16 = const()[name = tensor("transpose_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17856)))]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20992)))]; + tensor Add_6_cast_fp16 = conv(bias = const_55_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_19_to_fp16, x = model_1_model_add_1_add_cast_fp16)[name = tensor("Add_6_cast_fp16")]; + tensor model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16 = relu6(x = Add_6_cast_fp16)[name = tensor("model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(96)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_21_to_fp16 = const()[name = tensor("transpose_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21248)))]; + tensor const_56_to_fp16 = const()[name = tensor("const_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26112)))]; + tensor Add_7_cast_fp16 = conv(bias = const_56_to_fp16, 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_21_to_fp16, x = model_1_model_re_lu_6_Relu6_model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_6_Conv2D_cast_fp16)[name = tensor("Add_7_cast_fp16")]; + tensor model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16 = relu6(x = Add_7_cast_fp16)[name = tensor("model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_23_to_fp16 = const()[name = tensor("transpose_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26368)))]; + tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31040)))]; + tensor model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16 = conv(bias = const_57_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_23_to_fp16, x = model_1_model_re_lu_7_Relu6_model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_25_to_fp16 = const()[name = tensor("transpose_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31168)))]; + tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38144)))]; + tensor Add_8_cast_fp16 = conv(bias = const_58_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_25_to_fp16, x = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("Add_8_cast_fp16")]; + tensor model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16 = relu6(x = Add_8_cast_fp16)[name = tensor("model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(144)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_27_to_fp16 = const()[name = tensor("transpose_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38528)))]; + tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45824)))]; + tensor Add_9_cast_fp16 = conv(bias = const_59_to_fp16, 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_27_to_fp16, x = model_1_model_re_lu_8_Relu6_model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_8_Conv2D_cast_fp16)[name = tensor("Add_9_cast_fp16")]; + tensor model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16 = relu6(x = Add_9_cast_fp16)[name = tensor("model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_29_to_fp16 = const()[name = tensor("transpose_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46208)))]; + tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53184)))]; + tensor model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16 = conv(bias = const_60_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_29_to_fp16, x = model_1_model_re_lu_9_Relu6_model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_depthwise_conv2d_4_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16")]; + tensor model_1_model_add_2_add_cast_fp16 = add(x = model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_9_Conv2D_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_2_add_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_31_to_fp16 = const()[name = tensor("transpose_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53312)))]; + tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60288)))]; + tensor Add_10_cast_fp16 = conv(bias = const_61_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_31_to_fp16, x = model_1_model_add_2_add_cast_fp16)[name = tensor("Add_10_cast_fp16")]; + tensor model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16 = relu6(x = Add_10_cast_fp16)[name = tensor("model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(144)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_33_to_fp16 = const()[name = tensor("transpose_33_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60672)))]; + tensor const_62_to_fp16 = const()[name = tensor("const_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63360)))]; + tensor Add_11_cast_fp16 = conv(bias = const_62_to_fp16, 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_33_to_fp16, x = model_1_model_re_lu_10_Relu6_model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_model_1_model_conv2d_10_Conv2D_cast_fp16)[name = tensor("Add_11_cast_fp16")]; + tensor model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16 = relu6(x = Add_11_cast_fp16)[name = tensor("model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_35_to_fp16 = const()[name = tensor("transpose_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63744)))]; + tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77632)))]; + tensor model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16 = conv(bias = const_63_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_35_to_fp16, x = model_1_model_re_lu_11_Relu6_model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_depthwise_conv2d_5_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_37_to_fp16 = const()[name = tensor("transpose_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77824)))]; + tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105536)))]; + tensor Add_12_cast_fp16 = conv(bias = const_64_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_37_to_fp16, x = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("Add_12_cast_fp16")]; + tensor model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16 = relu6(x = Add_12_cast_fp16)[name = tensor("model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(288)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_39_to_fp16 = const()[name = tensor("transpose_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106176)))]; + tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111424)))]; + tensor Add_13_cast_fp16 = conv(bias = const_65_to_fp16, 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_39_to_fp16, x = model_1_model_re_lu_12_Relu6_model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_12_Conv2D_cast_fp16)[name = tensor("Add_13_cast_fp16")]; + tensor model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16 = relu6(x = Add_13_cast_fp16)[name = tensor("model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_41_to_fp16 = const()[name = tensor("transpose_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112064)))]; + tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139776)))]; + tensor model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16 = conv(bias = const_66_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_41_to_fp16, x = model_1_model_re_lu_13_Relu6_model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_6_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16")]; + tensor model_1_model_add_3_add_cast_fp16 = add(x = model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_3_add_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_43_to_fp16 = const()[name = tensor("transpose_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139968)))]; + tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167680)))]; + tensor Add_14_cast_fp16 = conv(bias = const_67_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_43_to_fp16, x = model_1_model_add_3_add_cast_fp16)[name = tensor("Add_14_cast_fp16")]; + tensor model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16 = relu6(x = Add_14_cast_fp16)[name = tensor("model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(288)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_45_to_fp16 = const()[name = tensor("transpose_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168320)))]; + tensor const_68_to_fp16 = const()[name = tensor("const_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173568)))]; + tensor Add_15_cast_fp16 = conv(bias = const_68_to_fp16, 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_45_to_fp16, x = model_1_model_re_lu_14_Relu6_model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_14_Conv2D_cast_fp16)[name = tensor("Add_15_cast_fp16")]; + tensor model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16 = relu6(x = Add_15_cast_fp16)[name = tensor("model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_47_to_fp16 = const()[name = tensor("transpose_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174208)))]; + tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201920)))]; + tensor model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16 = conv(bias = const_69_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_47_to_fp16, x = model_1_model_re_lu_15_Relu6_model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_depthwise_conv2d_7_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16")]; + tensor model_1_model_add_4_add_cast_fp16 = add(x = model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_15_Conv2D1_cast_fp16, y = model_1_model_add_3_add_cast_fp16)[name = tensor("model_1_model_add_4_add_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_49_to_fp16 = const()[name = tensor("transpose_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202112)))]; + tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229824)))]; + tensor Add_16_cast_fp16 = conv(bias = const_70_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_49_to_fp16, x = model_1_model_add_4_add_cast_fp16)[name = tensor("Add_16_cast_fp16")]; + tensor model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16 = relu6(x = Add_16_cast_fp16)[name = tensor("model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(288)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_51_to_fp16 = const()[name = tensor("transpose_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230464)))]; + tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244928)))]; + tensor Add_17_cast_fp16 = conv(bias = const_71_to_fp16, 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_51_to_fp16, x = model_1_model_re_lu_16_Relu6_model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_model_1_model_conv2d_16_Conv2D_cast_fp16)[name = tensor("Add_17_cast_fp16")]; + tensor model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16 = relu6(x = Add_17_cast_fp16)[name = tensor("model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_53_to_fp16 = const()[name = tensor("transpose_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245568)))]; + tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282496)))]; + tensor model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16 = conv(bias = const_72_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_53_to_fp16, x = model_1_model_re_lu_17_Relu6_model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_depthwise_conv2d_8_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_55_to_fp16 = const()[name = tensor("transpose_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282688)))]; + tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(331904)))]; + tensor Add_18_cast_fp16 = conv(bias = const_73_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_55_to_fp16, x = model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("Add_18_cast_fp16")]; + tensor model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16 = relu6(x = Add_18_cast_fp16)[name = tensor("model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(384)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_57_to_fp16 = const()[name = tensor("transpose_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(332736)))]; + tensor const_74_to_fp16 = const()[name = tensor("const_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352000)))]; + tensor Add_19_cast_fp16 = conv(bias = const_74_to_fp16, 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_57_to_fp16, x = model_1_model_re_lu_18_Relu6_model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_18_Conv2D_cast_fp16)[name = tensor("Add_19_cast_fp16")]; + tensor model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16 = relu6(x = Add_19_cast_fp16)[name = tensor("model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_59_to_fp16 = const()[name = tensor("transpose_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352832)))]; + tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402048)))]; + tensor model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16 = conv(bias = const_75_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_59_to_fp16, x = model_1_model_re_lu_19_Relu6_model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_9_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16")]; + tensor model_1_model_add_5_add_cast_fp16 = add(x = model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_5_add_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_61_to_fp16 = const()[name = tensor("transpose_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402240)))]; + tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451456)))]; + tensor Add_20_cast_fp16 = conv(bias = const_76_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_61_to_fp16, x = model_1_model_add_5_add_cast_fp16)[name = tensor("Add_20_cast_fp16")]; + tensor model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16 = relu6(x = Add_20_cast_fp16)[name = tensor("model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(384)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_63_to_fp16 = const()[name = tensor("transpose_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452288)))]; + tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471552)))]; + tensor Add_21_cast_fp16 = conv(bias = const_77_to_fp16, 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_63_to_fp16, x = model_1_model_re_lu_20_Relu6_model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_20_Conv2D_cast_fp16)[name = tensor("Add_21_cast_fp16")]; + tensor model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_10_depthwise_cast_fp16 = relu6(x = Add_21_cast_fp16)[name = tensor("model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_10_depthwise_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_65_to_fp16 = const()[name = tensor("transpose_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(472384)))]; + tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(521600)))]; + tensor model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16 = conv(bias = const_78_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_65_to_fp16, x = model_1_model_re_lu_21_Relu6_model_1_model_batch_normalization_31_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_depthwise_conv2d_10_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16")]; + tensor model_1_model_add_6_add_cast_fp16 = add(x = model_1_model_batch_normalization_32_FusedBatchNormV3_model_1_model_conv2d_21_Conv2D1_cast_fp16, y = model_1_model_add_5_add_cast_fp16)[name = tensor("model_1_model_add_6_add_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_67_to_fp16 = const()[name = tensor("transpose_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(521792)))]; + tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(571008)))]; + tensor Add_22_cast_fp16 = conv(bias = const_79_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_67_to_fp16, x = model_1_model_add_6_add_cast_fp16)[name = tensor("Add_22_cast_fp16")]; + tensor model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16 = relu6(x = Add_22_cast_fp16)[name = tensor("model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(384)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_69_to_fp16 = const()[name = tensor("transpose_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(571840)))]; + tensor const_80_to_fp16 = const()[name = tensor("const_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591104)))]; + tensor Add_23_cast_fp16 = conv(bias = const_80_to_fp16, 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_69_to_fp16, x = model_1_model_re_lu_22_Relu6_model_1_model_batch_normalization_33_FusedBatchNormV3_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_model_1_model_conv2d_22_Conv2D_cast_fp16)[name = tensor("Add_23_cast_fp16")]; + tensor model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16 = relu6(x = Add_23_cast_fp16)[name = tensor("model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16")]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_71_to_fp16 = const()[name = tensor("transpose_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591936)))]; + tensor const_81_to_fp16 = const()[name = tensor("const_81_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678016)))]; + tensor model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16 = conv(bias = const_81_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_71_to_fp16, x = model_1_model_re_lu_23_Relu6_model_1_model_batch_normalization_34_FusedBatchNormV3_model_1_model_depthwise_conv2d_11_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_73_to_fp16 = const()[name = tensor("transpose_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(678336)))]; + tensor const_82_to_fp16 = const()[name = tensor("const_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(828928)))]; + tensor Add_24_cast_fp16 = conv(bias = const_82_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_73_to_fp16, x = model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16)[name = tensor("Add_24_cast_fp16")]; + tensor model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16 = relu6(x = Add_24_cast_fp16)[name = tensor("model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(672)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_75_to_fp16 = const()[name = tensor("transpose_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(830336)))]; + tensor const_83_to_fp16 = const()[name = tensor("const_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(864000)))]; + tensor Add_25_cast_fp16 = conv(bias = const_83_to_fp16, 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_75_to_fp16, x = model_1_model_re_lu_24_Relu6_model_1_model_batch_normalization_36_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_24_Conv2D_cast_fp16)[name = tensor("Add_25_cast_fp16")]; + tensor model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_25_cast_fp16)[name = tensor("model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_77_to_fp16 = const()[name = tensor("transpose_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(865408)))]; + tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1016000)))]; + tensor model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16 = conv(bias = const_84_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_77_to_fp16, x = model_1_model_re_lu_25_Relu6_model_1_model_batch_normalization_37_FusedBatchNormV3_model_1_model_depthwise_conv2d_12_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16")]; + tensor model_1_model_add_7_add_cast_fp16 = add(x = model_1_model_batch_normalization_38_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_25_Conv2D1_cast_fp16, y = model_1_model_batch_normalization_35_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_7_add_cast_fp16")]; + tensor Conv2D_26x_pad_type_0 = const()[name = tensor("Conv2D_26x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_26x_strides_0 = const()[name = tensor("Conv2D_26x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_dilations_0 = const()[name = tensor("Conv2D_26x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_groups_0 = const()[name = tensor("Conv2D_26x_groups_0"), val = tensor(1)]; + tensor Conv2D_26x_pad_0 = const()[name = tensor("Conv2D_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_79_to_fp16 = const()[name = tensor("transpose_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1016320)))]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1166912)))]; + tensor Add_26_cast_fp16 = conv(bias = const_85_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_79_to_fp16, x = model_1_model_add_7_add_cast_fp16)[name = tensor("Add_26_cast_fp16")]; + tensor model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16 = relu6(x = Add_26_cast_fp16)[name = tensor("model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(672)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_81_to_fp16 = const()[name = tensor("transpose_81_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1168320)))]; + tensor const_86_to_fp16 = const()[name = tensor("const_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1201984)))]; + tensor Add_27_cast_fp16 = conv(bias = const_86_to_fp16, 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_81_to_fp16, x = model_1_model_re_lu_26_Relu6_model_1_model_batch_normalization_39_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_26_Conv2D_cast_fp16)[name = tensor("Add_27_cast_fp16")]; + tensor model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_27_cast_fp16)[name = tensor("model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_27x_pad_type_0 = const()[name = tensor("Conv2D_27x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_27x_strides_0 = const()[name = tensor("Conv2D_27x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_dilations_0 = const()[name = tensor("Conv2D_27x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_groups_0 = const()[name = tensor("Conv2D_27x_groups_0"), val = tensor(1)]; + tensor Conv2D_27x_pad_0 = const()[name = tensor("Conv2D_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_83_to_fp16 = const()[name = tensor("transpose_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1203392)))]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1353984)))]; + tensor model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16 = conv(bias = const_87_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_83_to_fp16, x = model_1_model_re_lu_27_Relu6_model_1_model_batch_normalization_40_FusedBatchNormV3_model_1_model_depthwise_conv2d_13_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16")]; + tensor model_1_model_add_8_add_cast_fp16 = add(x = model_1_model_batch_normalization_41_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D_model_1_model_conv2d_27_Conv2D1_cast_fp16, y = model_1_model_add_7_add_cast_fp16)[name = tensor("model_1_model_add_8_add_cast_fp16")]; + tensor Conv2D_28x_pad_type_0 = const()[name = tensor("Conv2D_28x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_28x_strides_0 = const()[name = tensor("Conv2D_28x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_dilations_0 = const()[name = tensor("Conv2D_28x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_groups_0 = const()[name = tensor("Conv2D_28x_groups_0"), val = tensor(1)]; + tensor Conv2D_28x_pad_0 = const()[name = tensor("Conv2D_28x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_85_to_fp16 = const()[name = tensor("transpose_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1354304)))]; + tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1504896)))]; + tensor Add_28_cast_fp16 = conv(bias = const_88_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_85_to_fp16, x = model_1_model_add_8_add_cast_fp16)[name = tensor("Add_28_cast_fp16")]; + tensor model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16 = relu6(x = Add_28_cast_fp16)[name = tensor("model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(672)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_87_to_fp16 = const()[name = tensor("transpose_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1506304)))]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1539968)))]; + tensor Add_29_cast_fp16 = conv(bias = const_89_to_fp16, 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_87_to_fp16, x = model_1_model_re_lu_28_Relu6_model_1_model_batch_normalization_42_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_28_Conv2D_cast_fp16)[name = tensor("Add_29_cast_fp16")]; + tensor model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_29_cast_fp16)[name = tensor("model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor Conv2D_29x_pad_type_0 = const()[name = tensor("Conv2D_29x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_29x_strides_0 = const()[name = tensor("Conv2D_29x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_dilations_0 = const()[name = tensor("Conv2D_29x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_groups_0 = const()[name = tensor("Conv2D_29x_groups_0"), val = tensor(1)]; + tensor Conv2D_29x_pad_0 = const()[name = tensor("Conv2D_29x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_89_to_fp16 = const()[name = tensor("transpose_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1541376)))]; + tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1691968)))]; + tensor model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16 = conv(bias = const_90_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_89_to_fp16, x = model_1_model_re_lu_29_Relu6_model_1_model_batch_normalization_43_FusedBatchNormV3_model_1_model_depthwise_conv2d_14_depthwise_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16")]; + tensor model_1_model_add_9_add_cast_fp16 = add(x = model_1_model_batch_normalization_44_FusedBatchNormV3_model_1_model_conv2d_29_Conv2D1_cast_fp16, y = model_1_model_add_8_add_cast_fp16)[name = tensor("model_1_model_add_9_add_cast_fp16")]; + tensor Conv2D_30x_pad_type_0 = const()[name = tensor("Conv2D_30x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_30x_strides_0 = const()[name = tensor("Conv2D_30x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_dilations_0 = const()[name = tensor("Conv2D_30x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_groups_0 = const()[name = tensor("Conv2D_30x_groups_0"), val = tensor(1)]; + tensor Conv2D_30x_pad_0 = const()[name = tensor("Conv2D_30x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_91_to_fp16 = const()[name = tensor("transpose_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1692288)))]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1842880)))]; + tensor Add_30_cast_fp16 = conv(bias = const_91_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_91_to_fp16, x = model_1_model_add_9_add_cast_fp16)[name = tensor("Add_30_cast_fp16")]; + tensor model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16 = relu6(x = Add_30_cast_fp16)[name = tensor("model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(672)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1844288)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1856448)))]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, 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 = conv_0_weight_0_to_fp16, x = model_1_model_re_lu_30_Relu6_model_1_model_batch_normalization_45_FusedBatchNormV3_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_model_1_model_conv2d_30_Conv2D_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor depthwise_15_perm_0 = const()[name = tensor("depthwise_15_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Add_31_cast_fp16 = transpose(perm = depthwise_15_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_99")]; + tensor model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16 = relu6(x = Add_31_cast_fp16)[name = tensor("model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16")]; + tensor model_1_model_global_average_pooling2d_Mean_axes_0 = const()[name = tensor("model_1_model_global_average_pooling2d_Mean_axes_0"), val = tensor([1, 2])]; + tensor model_1_model_global_average_pooling2d_Mean_keep_dims_0 = const()[name = tensor("model_1_model_global_average_pooling2d_Mean_keep_dims_0"), val = tensor(false)]; + tensor model_1_model_global_average_pooling2d_Mean_cast_fp16 = reduce_mean(axes = model_1_model_global_average_pooling2d_Mean_axes_0, keep_dims = model_1_model_global_average_pooling2d_Mean_keep_dims_0, x = model_1_model_re_lu_31_Relu6_model_1_model_batch_normalization_46_FusedBatchNormV3_model_1_model_depthwise_conv2d_15_depthwise_cast_fp16)[name = tensor("model_1_model_global_average_pooling2d_Mean_cast_fp16")]; + tensor transpose_95_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_95_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1857856)))]; + tensor Identity_bias_0_to_fp16 = const()[name = tensor("Identity_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1942592)))]; + tensor Identity_cast_fp16 = linear(bias = Identity_bias_0_to_fp16, weight = transpose_95_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("Identity_cast_fp16")]; + tensor Identity_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor transpose_96_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_96_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1942784)))]; + tensor model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16 = const()[name = tensor("model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16"), val = tensor([0x1.4c8p-2])]; + tensor model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16 = linear(bias = model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_bias_0_to_fp16, weight = transpose_96_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16")]; + tensor transpose_97_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_97_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1944192)))]; + tensor model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16 = const()[name = tensor("model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16"), val = tensor([-0x1.fd8p-5])]; + tensor model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16 = linear(bias = model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_bias_0_to_fp16, weight = transpose_97_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16")]; + tensor transpose_98_cast_fp16_to_fp32_to_fp16 = const()[name = tensor("transpose_98_cast_fp16_to_fp32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1945600)))]; + tensor Identity_3_bias_0_to_fp16 = const()[name = tensor("Identity_3_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2030336)))]; + tensor Identity_3_cast_fp16 = linear(bias = Identity_3_bias_0_to_fp16, weight = transpose_98_cast_fp16_to_fp32_to_fp16, x = model_1_model_global_average_pooling2d_Mean_cast_fp16)[name = tensor("Identity_3_cast_fp16")]; + tensor Identity_3_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_3_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1_cast_fp16 = sigmoid(x = model_1_model_conv_handflag_MatMul_model_1_model_conv_handflag_BiasAdd_dense_1_Add_cast_fp16)[name = tensor("Identity_1_cast_fp16")]; + tensor Identity_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_1_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_2_cast_fp16 = sigmoid(x = model_1_model_conv_handedness_MatMul_model_1_model_conv_handedness_BiasAdd_dense_1_Add_cast_fp16)[name = tensor("Identity_2_cast_fp16")]; + tensor Identity_2_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_2_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_2 = cast(dtype = Identity_2_cast_fp16_to_fp32_dtype_0, x = Identity_2_cast_fp16)[name = tensor("cast_0")]; + tensor Identity_1 = cast(dtype = Identity_1_cast_fp16_to_fp32_dtype_0, x = Identity_1_cast_fp16)[name = tensor("cast_1")]; + tensor Identity_3 = cast(dtype = Identity_3_cast_fp16_to_fp32_dtype_0, x = Identity_3_cast_fp16)[name = tensor("cast_2")]; + tensor Identity = cast(dtype = Identity_cast_fp16_to_fp32_dtype_0, x = Identity_cast_fp16)[name = tensor("cast_3")]; + } -> (Identity, Identity_1, Identity_2, Identity_3); +} \ No newline at end of file diff --git a/compiled/hand_landmark_lite.mlmodelc/weights/weight.bin b/compiled/hand_landmark_lite.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..9a8f9006b5c4ebd562b2654b96d69f55286095e7 --- /dev/null +++ b/compiled/hand_landmark_lite.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a501a09f7dbf9053985e9351253ec84f039ddf8443624cf32687bb68b5e17668 +size 2030526 diff --git a/compiled/iris_landmark.mlmodelc/analytics/coremldata.bin b/compiled/iris_landmark.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..6bc29094a5915e0cf071433a512f7ff1ba95a8a1 --- /dev/null +++ b/compiled/iris_landmark.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d88d56634a7aa460bdae91f93bcd6ff195e61225187839538e7e7ba1d52c7c87 +size 243 diff --git a/compiled/iris_landmark.mlmodelc/coremldata.bin b/compiled/iris_landmark.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..7113319301d0da682701e0fb2aac4b5c2eb01b06 --- /dev/null +++ b/compiled/iris_landmark.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2048b32d5c79987d8dce5efd57f0ff35223ebb001ce7dd1778ea184644a18d8d +size 309 diff --git a/compiled/iris_landmark.mlmodelc/metadata.json b/compiled/iris_landmark.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..074f871e4948dc6ae4865e4c0a006ab56522230a --- /dev/null +++ b/compiled/iris_landmark.mlmodelc/metadata.json @@ -0,0 +1,76 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 213)", + "shortDescription" : "", + "shape" : "[1, 213]", + "name" : "output_eyes_contours_and_brows", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 15)", + "shortDescription" : "", + "shape" : "[1, 15]", + "name" : "output_iris", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Cast" : 3, + "Conv" : 81, + "Prelu" : 53, + "Pad" : 1, + "Transpose" : 3, + "Add" : 26, + "Reshape" : 2, + "MaxPool" : 6 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 64 × 64 × 3)", + "shortDescription" : "", + "shape" : "[1, 64, 64, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "iris_landmark", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/iris_landmark.mlmodelc/model.mil b/compiled/iris_landmark.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..1f6c26d8fe461c351a4699e032c159ce4fccc507 --- /dev/null +++ b/compiled/iris_landmark.mlmodelc/model.mil @@ -0,0 +1,816 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor output_eyes_contours_and_brows_shape = const()[name = tensor("output_eyes_contours_and_brows_shape"), val = tensor([1, -1])]; + tensor output_iris_shape = const()[name = tensor("output_iris_shape"), val = tensor([1, -1])]; + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_161_to_fp16 = const()[name = tensor("const_161_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3584)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_3")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_170")]; + tensor 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("conv2d_1_cast_fp16")]; + tensor conv2d_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3776)))]; + tensor conv2d_prelu_1_add_cast_fp16 = prelu(alpha = conv2d_prelu_1_add_alpha_0_to_fp16, x = conv2d_1_cast_fp16)[name = tensor("conv2d_prelu_1_add_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3968)))]; + tensor const_162_to_fp16 = const()[name = tensor("const_162_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8128)))]; + tensor 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("conv2d_1_1_cast_fp16")]; + tensor conv2d_1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8256)))]; + tensor 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("conv2d_1_prelu_1_add_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(32)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8384)))]; + tensor 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("depthwisex_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9024)))]; + tensor const_163_to_fp16 = const()[name = tensor("const_163_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13184)))]; + tensor 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("conv2d_2_1_cast_fp16")]; + tensor add__xeno_compat__1_cast_fp16 = add(x = conv2d_prelu_1_add_cast_fp16, y = conv2d_2_1_cast_fp16)[name = tensor("add__xeno_compat__1_cast_fp16")]; + tensor add__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13376)))]; + tensor 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("add__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13568)))]; + tensor const_164_to_fp16 = const()[name = tensor("const_164_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17728)))]; + tensor 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("conv2d_3_1_cast_fp16")]; + tensor conv2d_3_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_3_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17856)))]; + tensor 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("conv2d_3_prelu_1_add_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(32)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_10_to_fp16 = const()[name = tensor("transpose_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17984)))]; + tensor 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("depthwise_1x_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_12_to_fp16 = const()[name = tensor("transpose_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18624)))]; + tensor const_165_to_fp16 = const()[name = tensor("const_165_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22784)))]; + tensor 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("conv2d_4_1_cast_fp16")]; + tensor 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("add_1__xeno_compat__1_cast_fp16")]; + tensor add_1__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_1__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22976)))]; + tensor 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("add_1__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_14_to_fp16 = const()[name = tensor("transpose_14_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23168)))]; + tensor const_166_to_fp16 = const()[name = tensor("const_166_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27328)))]; + tensor 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("conv2d_5_1_cast_fp16")]; + tensor conv2d_5_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_5_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27456)))]; + tensor 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("conv2d_5_prelu_1_add_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(32)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_16_to_fp16 = const()[name = tensor("transpose_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27584)))]; + tensor 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("depthwise_2x_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_18_to_fp16 = const()[name = tensor("transpose_18_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28224)))]; + tensor const_167_to_fp16 = const()[name = tensor("const_167_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32384)))]; + tensor 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("conv2d_6_1_cast_fp16")]; + tensor 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("add_2__xeno_compat__1_cast_fp16")]; + tensor add_2__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_2__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32576)))]; + tensor 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("add_2__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_20_to_fp16 = const()[name = tensor("transpose_20_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32768)))]; + tensor const_168_to_fp16 = const()[name = tensor("const_168_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36928)))]; + tensor 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("conv2d_7_1_cast_fp16")]; + tensor conv2d_7_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_7_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37056)))]; + tensor 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("conv2d_7_prelu_1_add_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(32)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_22_to_fp16 = const()[name = tensor("transpose_22_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37184)))]; + tensor 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("depthwise_3x_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_24_to_fp16 = const()[name = tensor("transpose_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37824)))]; + tensor const_169_to_fp16 = const()[name = tensor("const_169_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41984)))]; + tensor 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("conv2d_8_1_cast_fp16")]; + tensor 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("add_3__xeno_compat__1_cast_fp16")]; + tensor add_3__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_3__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42176)))]; + tensor 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("add_3__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("valid")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_0_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_27_to_fp16 = const()[name = tensor("transpose_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42368)))]; + tensor const_170_to_fp16 = const()[name = tensor("const_170_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75200)))]; + tensor 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("conv2d_9_1_cast_fp16")]; + tensor pad_0_mode_0 = const()[name = tensor("pad_0_mode_0"), val = tensor("constant")]; + tensor const_74 = const()[name = tensor("const_74"), val = tensor([0, 0, 0, 64, 0, 0, 0, 0])]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; + tensor 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("pad_0_cast_fp16")]; + tensor conv2d_9_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_9_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75392)))]; + tensor 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("conv2d_9_prelu_1_add_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(64)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_29_to_fp16 = const()[name = tensor("transpose_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75584)))]; + tensor 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("depthwise_4x_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_31_to_fp16 = const()[name = tensor("transpose_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76800)))]; + tensor const_171_to_fp16 = const()[name = tensor("const_171_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93248)))]; + tensor 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("conv2d_10_1_cast_fp16")]; + tensor add_4__xeno_compat__1_cast_fp16 = add(x = pad_0_cast_fp16, y = conv2d_10_1_cast_fp16)[name = tensor("add_4__xeno_compat__1_cast_fp16")]; + tensor add_4__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_4__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93568)))]; + tensor 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("add_4__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_33_to_fp16 = const()[name = tensor("transpose_33_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93888)))]; + tensor const_172_to_fp16 = const()[name = tensor("const_172_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110336)))]; + tensor 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("conv2d_11_1_cast_fp16")]; + tensor conv2d_11_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_11_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110528)))]; + tensor 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("conv2d_11_prelu_1_add_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(64)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_35_to_fp16 = const()[name = tensor("transpose_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110720)))]; + tensor 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("depthwise_5x_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_37_to_fp16 = const()[name = tensor("transpose_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111936)))]; + tensor const_173_to_fp16 = const()[name = tensor("const_173_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128384)))]; + tensor 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("conv2d_12_1_cast_fp16")]; + tensor 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("add_5__xeno_compat__1_cast_fp16")]; + tensor add_5__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_5__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128704)))]; + tensor 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("add_5__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_39_to_fp16 = const()[name = tensor("transpose_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129024)))]; + tensor const_174_to_fp16 = const()[name = tensor("const_174_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145472)))]; + tensor 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("conv2d_13_1_cast_fp16")]; + tensor conv2d_13_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_13_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145664)))]; + tensor 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("conv2d_13_prelu_1_add_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(64)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_41_to_fp16 = const()[name = tensor("transpose_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145856)))]; + tensor 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("depthwise_6x_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_43_to_fp16 = const()[name = tensor("transpose_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147072)))]; + tensor const_175_to_fp16 = const()[name = tensor("const_175_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163520)))]; + tensor 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("conv2d_14_1_cast_fp16")]; + tensor 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("add_6__xeno_compat__1_cast_fp16")]; + tensor add_6__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_6__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163840)))]; + tensor 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("add_6__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_45_to_fp16 = const()[name = tensor("transpose_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164160)))]; + tensor const_176_to_fp16 = const()[name = tensor("const_176_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180608)))]; + tensor 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("conv2d_15_1_cast_fp16")]; + tensor conv2d_15_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_15_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180800)))]; + tensor 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("conv2d_15_prelu_1_add_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(64)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_47_to_fp16 = const()[name = tensor("transpose_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180992)))]; + tensor 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("depthwise_7x_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_49_to_fp16 = const()[name = tensor("transpose_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182208)))]; + tensor const_177_to_fp16 = const()[name = tensor("const_177_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198656)))]; + tensor 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("conv2d_16_1_cast_fp16")]; + tensor 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("add_7__xeno_compat__1_cast_fp16")]; + tensor add_7__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_7__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198976)))]; + tensor 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("add_7__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_51_to_fp16 = const()[name = tensor("transpose_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199296)))]; + tensor const_178_to_fp16 = const()[name = tensor("const_178_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215744)))]; + tensor 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("conv2d_17_1_cast_fp16")]; + tensor conv2d_17_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_17_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215936)))]; + tensor 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("conv2d_17_prelu_1_add_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(64)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_53_to_fp16 = const()[name = tensor("transpose_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216128)))]; + tensor 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("depthwise_8x_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_55_to_fp16 = const()[name = tensor("transpose_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217344)))]; + tensor const_179_to_fp16 = const()[name = tensor("const_179_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233792)))]; + tensor 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("conv2d_18_1_cast_fp16")]; + tensor 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("add_8__xeno_compat__1_cast_fp16")]; + tensor add_8__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_8__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234112)))]; + tensor 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("add_8__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor max_pool_1_kernel_sizes_0 = const()[name = tensor("max_pool_1_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_1_strides_0 = const()[name = tensor("max_pool_1_strides_0"), val = tensor([2, 2])]; + tensor max_pool_1_pad_type_0 = const()[name = tensor("max_pool_1_pad_type_0"), val = tensor("valid")]; + tensor max_pool_1_pad_0 = const()[name = tensor("max_pool_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_1_ceil_mode_0 = const()[name = tensor("max_pool_1_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_1_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_58_to_fp16 = const()[name = tensor("transpose_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234432)))]; + tensor const_180_to_fp16 = const()[name = tensor("const_180_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300032)))]; + tensor 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("conv2d_19_1_cast_fp16")]; + tensor conv2d_19_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_19_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300224)))]; + tensor 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("conv2d_19_prelu_1_add_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(64)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_60_to_fp16 = const()[name = tensor("transpose_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300416)))]; + tensor 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("depthwise_9x_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_62_to_fp16 = const()[name = tensor("transpose_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301632)))]; + tensor const_181_to_fp16 = const()[name = tensor("const_181_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318080)))]; + tensor 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("conv2d_20_1_cast_fp16")]; + tensor add_9__xeno_compat__1_cast_fp16 = add(x = max_pool_1_cast_fp16, y = conv2d_20_1_cast_fp16)[name = tensor("add_9__xeno_compat__1_cast_fp16")]; + tensor add_9__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_9__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318400)))]; + tensor 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("add_9__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_64_to_fp16 = const()[name = tensor("transpose_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318720)))]; + tensor const_182_to_fp16 = const()[name = tensor("const_182_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(335168)))]; + tensor 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("conv2d_21_1_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_66_to_fp16 = const()[name = tensor("transpose_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(335360)))]; + tensor const_183_to_fp16 = const()[name = tensor("const_183_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351808)))]; + tensor 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("conv2d_37_cast_fp16")]; + tensor conv2d_37_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_37_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352000)))]; + tensor 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("conv2d_37_prelu_1_add_cast_fp16")]; + tensor p_re_lu_21_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_21_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352192)))]; + tensor 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("p_re_lu_21_prelu_1_add_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(64)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_68_to_fp16 = const()[name = tensor("transpose_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352384)))]; + tensor 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("depthwise_10x_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(64)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_70_to_fp16 = const()[name = tensor("transpose_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353600)))]; + tensor 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("depthwise_11x_cast_fp16")]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_72_to_fp16 = const()[name = tensor("transpose_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354816)))]; + tensor const_184_to_fp16 = const()[name = tensor("const_184_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(371264)))]; + tensor 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("conv2d_22_1_cast_fp16")]; + tensor Conv2D_26x_pad_type_0 = const()[name = tensor("Conv2D_26x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_26x_strides_0 = const()[name = tensor("Conv2D_26x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_dilations_0 = const()[name = tensor("Conv2D_26x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_groups_0 = const()[name = tensor("Conv2D_26x_groups_0"), val = tensor(1)]; + tensor Conv2D_26x_pad_0 = const()[name = tensor("Conv2D_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_74_to_fp16 = const()[name = tensor("transpose_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(371584)))]; + tensor const_185_to_fp16 = const()[name = tensor("const_185_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388032)))]; + tensor 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("conv2d_38_cast_fp16")]; + tensor 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("add_10__xeno_compat__1_cast_fp16")]; + tensor 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("add_18__xeno_compat__1_cast_fp16")]; + tensor add_18__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_18__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388352)))]; + tensor 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("add_18__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_22_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_22_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388672)))]; + tensor 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("p_re_lu_22_prelu_1_add_cast_fp16")]; + tensor Conv2D_27x_pad_type_0 = const()[name = tensor("Conv2D_27x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_27x_strides_0 = const()[name = tensor("Conv2D_27x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_dilations_0 = const()[name = tensor("Conv2D_27x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_groups_0 = const()[name = tensor("Conv2D_27x_groups_0"), val = tensor(1)]; + tensor Conv2D_27x_pad_0 = const()[name = tensor("Conv2D_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_76_to_fp16 = const()[name = tensor("transpose_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388992)))]; + tensor const_186_to_fp16 = const()[name = tensor("const_186_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(405440)))]; + tensor 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("conv2d_23_1_cast_fp16")]; + tensor Conv2D_28x_pad_type_0 = const()[name = tensor("Conv2D_28x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_28x_strides_0 = const()[name = tensor("Conv2D_28x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_dilations_0 = const()[name = tensor("Conv2D_28x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_groups_0 = const()[name = tensor("Conv2D_28x_groups_0"), val = tensor(1)]; + tensor Conv2D_28x_pad_0 = const()[name = tensor("Conv2D_28x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_78_to_fp16 = const()[name = tensor("transpose_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(405632)))]; + tensor const_187_to_fp16 = const()[name = tensor("const_187_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422080)))]; + tensor 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("conv2d_39_cast_fp16")]; + tensor conv2d_39_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_39_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422272)))]; + tensor 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("conv2d_39_prelu_1_add_cast_fp16")]; + tensor p_re_lu_23_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_23_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422464)))]; + tensor 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("p_re_lu_23_prelu_1_add_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(64)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_80_to_fp16 = const()[name = tensor("transpose_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422656)))]; + tensor 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("depthwise_12x_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(64)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_82_to_fp16 = const()[name = tensor("transpose_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423872)))]; + tensor 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("depthwise_13x_cast_fp16")]; + tensor Conv2D_29x_pad_type_0 = const()[name = tensor("Conv2D_29x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_29x_strides_0 = const()[name = tensor("Conv2D_29x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_dilations_0 = const()[name = tensor("Conv2D_29x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_groups_0 = const()[name = tensor("Conv2D_29x_groups_0"), val = tensor(1)]; + tensor Conv2D_29x_pad_0 = const()[name = tensor("Conv2D_29x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_84_to_fp16 = const()[name = tensor("transpose_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425088)))]; + tensor const_188_to_fp16 = const()[name = tensor("const_188_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441536)))]; + tensor 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("conv2d_24_1_cast_fp16")]; + tensor Conv2D_30x_pad_type_0 = const()[name = tensor("Conv2D_30x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_30x_strides_0 = const()[name = tensor("Conv2D_30x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_dilations_0 = const()[name = tensor("Conv2D_30x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_groups_0 = const()[name = tensor("Conv2D_30x_groups_0"), val = tensor(1)]; + tensor Conv2D_30x_pad_0 = const()[name = tensor("Conv2D_30x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_86_to_fp16 = const()[name = tensor("transpose_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441856)))]; + tensor const_189_to_fp16 = const()[name = tensor("const_189_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(458304)))]; + tensor 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("conv2d_40_cast_fp16")]; + tensor 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("add_11__xeno_compat__1_cast_fp16")]; + tensor 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("add_19__xeno_compat__1_cast_fp16")]; + tensor add_19__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_19__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(458624)))]; + tensor 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("add_19__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_24_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_24_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(458944)))]; + tensor 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("p_re_lu_24_prelu_1_add_cast_fp16")]; + tensor max_pool_2_kernel_sizes_0 = const()[name = tensor("max_pool_2_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_2_strides_0 = const()[name = tensor("max_pool_2_strides_0"), val = tensor([2, 2])]; + tensor max_pool_2_pad_type_0 = const()[name = tensor("max_pool_2_pad_type_0"), val = tensor("valid")]; + tensor max_pool_2_pad_0 = const()[name = tensor("max_pool_2_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_2_ceil_mode_0 = const()[name = tensor("max_pool_2_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_2_cast_fp16")]; + tensor Conv2D_31x_pad_type_0 = const()[name = tensor("Conv2D_31x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_31x_strides_0 = const()[name = tensor("Conv2D_31x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_31x_dilations_0 = const()[name = tensor("Conv2D_31x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_31x_groups_0 = const()[name = tensor("Conv2D_31x_groups_0"), val = tensor(1)]; + tensor Conv2D_31x_pad_0 = const()[name = tensor("Conv2D_31x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_89_to_fp16 = const()[name = tensor("transpose_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(459264)))]; + tensor const_190_to_fp16 = const()[name = tensor("const_190_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(524864)))]; + tensor 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("conv2d_25_1_cast_fp16")]; + tensor max_pool_3_kernel_sizes_0 = const()[name = tensor("max_pool_3_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_3_strides_0 = const()[name = tensor("max_pool_3_strides_0"), val = tensor([2, 2])]; + tensor max_pool_3_pad_type_0 = const()[name = tensor("max_pool_3_pad_type_0"), val = tensor("valid")]; + tensor max_pool_3_pad_0 = const()[name = tensor("max_pool_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_3_ceil_mode_0 = const()[name = tensor("max_pool_3_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_3_cast_fp16")]; + tensor Conv2D_32x_pad_type_0 = const()[name = tensor("Conv2D_32x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_32x_strides_0 = const()[name = tensor("Conv2D_32x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_32x_dilations_0 = const()[name = tensor("Conv2D_32x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_32x_groups_0 = const()[name = tensor("Conv2D_32x_groups_0"), val = tensor(1)]; + tensor Conv2D_32x_pad_0 = const()[name = tensor("Conv2D_32x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_92_to_fp16 = const()[name = tensor("transpose_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525056)))]; + tensor const_191_to_fp16 = const()[name = tensor("const_191_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(590656)))]; + tensor 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("conv2d_41_cast_fp16")]; + tensor conv2d_41_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_41_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(590848)))]; + tensor 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("conv2d_41_prelu_1_add_cast_fp16")]; + tensor p_re_lu_25_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_25_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591040)))]; + tensor 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("p_re_lu_25_prelu_1_add_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(64)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_94_to_fp16 = const()[name = tensor("transpose_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(591232)))]; + tensor 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("depthwise_14x_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(64)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_96_to_fp16 = const()[name = tensor("transpose_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(592448)))]; + tensor 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("depthwise_15x_cast_fp16")]; + tensor Conv2D_33x_pad_type_0 = const()[name = tensor("Conv2D_33x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_33x_strides_0 = const()[name = tensor("Conv2D_33x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_33x_dilations_0 = const()[name = tensor("Conv2D_33x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_33x_groups_0 = const()[name = tensor("Conv2D_33x_groups_0"), val = tensor(1)]; + tensor Conv2D_33x_pad_0 = const()[name = tensor("Conv2D_33x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_98_to_fp16 = const()[name = tensor("transpose_98_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(593664)))]; + tensor const_192_to_fp16 = const()[name = tensor("const_192_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(610112)))]; + tensor 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("conv2d_26_1_cast_fp16")]; + tensor Conv2D_34x_pad_type_0 = const()[name = tensor("Conv2D_34x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_34x_strides_0 = const()[name = tensor("Conv2D_34x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_34x_dilations_0 = const()[name = tensor("Conv2D_34x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_34x_groups_0 = const()[name = tensor("Conv2D_34x_groups_0"), val = tensor(1)]; + tensor Conv2D_34x_pad_0 = const()[name = tensor("Conv2D_34x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_100_to_fp16 = const()[name = tensor("transpose_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(610432)))]; + tensor const_193_to_fp16 = const()[name = tensor("const_193_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(626880)))]; + tensor 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("conv2d_42_cast_fp16")]; + tensor add_12__xeno_compat__1_cast_fp16 = add(x = max_pool_2_cast_fp16, y = conv2d_26_1_cast_fp16)[name = tensor("add_12__xeno_compat__1_cast_fp16")]; + tensor add_20__xeno_compat__1_cast_fp16 = add(x = max_pool_3_cast_fp16, y = conv2d_42_cast_fp16)[name = tensor("add_20__xeno_compat__1_cast_fp16")]; + tensor add_20__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_20__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627200)))]; + tensor 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("add_20__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_26_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_26_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627520)))]; + tensor 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("p_re_lu_26_prelu_1_add_cast_fp16")]; + tensor Conv2D_35x_pad_type_0 = const()[name = tensor("Conv2D_35x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_35x_strides_0 = const()[name = tensor("Conv2D_35x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_35x_dilations_0 = const()[name = tensor("Conv2D_35x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_35x_groups_0 = const()[name = tensor("Conv2D_35x_groups_0"), val = tensor(1)]; + tensor Conv2D_35x_pad_0 = const()[name = tensor("Conv2D_35x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_102_to_fp16 = const()[name = tensor("transpose_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(627840)))]; + tensor const_194_to_fp16 = const()[name = tensor("const_194_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644288)))]; + tensor 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("conv2d_27_1_cast_fp16")]; + tensor Conv2D_36x_pad_type_0 = const()[name = tensor("Conv2D_36x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_36x_strides_0 = const()[name = tensor("Conv2D_36x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_36x_dilations_0 = const()[name = tensor("Conv2D_36x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_36x_groups_0 = const()[name = tensor("Conv2D_36x_groups_0"), val = tensor(1)]; + tensor Conv2D_36x_pad_0 = const()[name = tensor("Conv2D_36x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_104_to_fp16 = const()[name = tensor("transpose_104_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(644480)))]; + tensor const_195_to_fp16 = const()[name = tensor("const_195_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(660928)))]; + tensor 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("conv2d_43_cast_fp16")]; + tensor conv2d_43_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_43_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661120)))]; + tensor 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("conv2d_43_prelu_1_add_cast_fp16")]; + tensor p_re_lu_27_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_27_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661312)))]; + tensor 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("p_re_lu_27_prelu_1_add_cast_fp16")]; + tensor depthwise_16x_pad_type_0 = const()[name = tensor("depthwise_16x_pad_type_0"), val = tensor("same")]; + tensor depthwise_16x_strides_0 = const()[name = tensor("depthwise_16x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_16x_dilations_0 = const()[name = tensor("depthwise_16x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_16x_groups_0 = const()[name = tensor("depthwise_16x_groups_0"), val = tensor(64)]; + tensor depthwise_16x_pad_0 = const()[name = tensor("depthwise_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_106_to_fp16 = const()[name = tensor("transpose_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(661504)))]; + tensor 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("depthwise_16x_cast_fp16")]; + tensor depthwise_17x_pad_type_0 = const()[name = tensor("depthwise_17x_pad_type_0"), val = tensor("same")]; + tensor depthwise_17x_strides_0 = const()[name = tensor("depthwise_17x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_17x_dilations_0 = const()[name = tensor("depthwise_17x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_17x_groups_0 = const()[name = tensor("depthwise_17x_groups_0"), val = tensor(64)]; + tensor depthwise_17x_pad_0 = const()[name = tensor("depthwise_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_108_to_fp16 = const()[name = tensor("transpose_108_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(662720)))]; + tensor 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("depthwise_17x_cast_fp16")]; + tensor Conv2D_44x_pad_type_0 = const()[name = tensor("Conv2D_44x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_44x_strides_0 = const()[name = tensor("Conv2D_44x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_44x_dilations_0 = const()[name = tensor("Conv2D_44x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_44x_groups_0 = const()[name = tensor("Conv2D_44x_groups_0"), val = tensor(1)]; + tensor Conv2D_44x_pad_0 = const()[name = tensor("Conv2D_44x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_110_to_fp16 = const()[name = tensor("transpose_110_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(663936)))]; + tensor const_196_to_fp16 = const()[name = tensor("const_196_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(680384)))]; + tensor 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("conv2d_28_1_cast_fp16")]; + tensor Conv2D_45x_pad_type_0 = const()[name = tensor("Conv2D_45x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_45x_strides_0 = const()[name = tensor("Conv2D_45x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_45x_dilations_0 = const()[name = tensor("Conv2D_45x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_45x_groups_0 = const()[name = tensor("Conv2D_45x_groups_0"), val = tensor(1)]; + tensor Conv2D_45x_pad_0 = const()[name = tensor("Conv2D_45x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_112_to_fp16 = const()[name = tensor("transpose_112_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(680704)))]; + tensor const_197_to_fp16 = const()[name = tensor("const_197_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(697152)))]; + tensor 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("conv2d_44_1_cast_fp16")]; + tensor 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("add_13__xeno_compat__1_cast_fp16")]; + tensor 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("add_21__xeno_compat__1_cast_fp16")]; + tensor add_21__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_21__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(697472)))]; + tensor 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("add_21__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_28_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_28_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(697792)))]; + tensor 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("p_re_lu_28_prelu_1_add_cast_fp16")]; + tensor Conv2D_46x_pad_type_0 = const()[name = tensor("Conv2D_46x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_46x_strides_0 = const()[name = tensor("Conv2D_46x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_46x_dilations_0 = const()[name = tensor("Conv2D_46x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_46x_groups_0 = const()[name = tensor("Conv2D_46x_groups_0"), val = tensor(1)]; + tensor Conv2D_46x_pad_0 = const()[name = tensor("Conv2D_46x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_114_to_fp16 = const()[name = tensor("transpose_114_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(698112)))]; + tensor const_198_to_fp16 = const()[name = tensor("const_198_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(714560)))]; + tensor 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("conv2d_29_1_cast_fp16")]; + tensor Conv2D_47x_pad_type_0 = const()[name = tensor("Conv2D_47x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_47x_strides_0 = const()[name = tensor("Conv2D_47x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_47x_dilations_0 = const()[name = tensor("Conv2D_47x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_47x_groups_0 = const()[name = tensor("Conv2D_47x_groups_0"), val = tensor(1)]; + tensor Conv2D_47x_pad_0 = const()[name = tensor("Conv2D_47x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_116_to_fp16 = const()[name = tensor("transpose_116_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(714752)))]; + tensor const_199_to_fp16 = const()[name = tensor("const_199_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(731200)))]; + tensor 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("conv2d_45_1_cast_fp16")]; + tensor conv2d_45_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_45_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(731392)))]; + tensor 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("conv2d_45_prelu_1_add_cast_fp16")]; + tensor p_re_lu_29_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_29_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(731584)))]; + tensor 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("p_re_lu_29_prelu_1_add_cast_fp16")]; + tensor depthwise_18x_pad_type_0 = const()[name = tensor("depthwise_18x_pad_type_0"), val = tensor("same")]; + tensor depthwise_18x_strides_0 = const()[name = tensor("depthwise_18x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_18x_dilations_0 = const()[name = tensor("depthwise_18x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_18x_groups_0 = const()[name = tensor("depthwise_18x_groups_0"), val = tensor(64)]; + tensor depthwise_18x_pad_0 = const()[name = tensor("depthwise_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_118_to_fp16 = const()[name = tensor("transpose_118_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(731776)))]; + tensor 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("depthwise_18x_cast_fp16")]; + tensor depthwise_19x_pad_type_0 = const()[name = tensor("depthwise_19x_pad_type_0"), val = tensor("same")]; + tensor depthwise_19x_strides_0 = const()[name = tensor("depthwise_19x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_19x_dilations_0 = const()[name = tensor("depthwise_19x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_19x_groups_0 = const()[name = tensor("depthwise_19x_groups_0"), val = tensor(64)]; + tensor depthwise_19x_pad_0 = const()[name = tensor("depthwise_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_120_to_fp16 = const()[name = tensor("transpose_120_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(732992)))]; + tensor 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("depthwise_19x_cast_fp16")]; + tensor Conv2D_48x_pad_type_0 = const()[name = tensor("Conv2D_48x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_48x_strides_0 = const()[name = tensor("Conv2D_48x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_48x_dilations_0 = const()[name = tensor("Conv2D_48x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_48x_groups_0 = const()[name = tensor("Conv2D_48x_groups_0"), val = tensor(1)]; + tensor Conv2D_48x_pad_0 = const()[name = tensor("Conv2D_48x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_122_to_fp16 = const()[name = tensor("transpose_122_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(734208)))]; + tensor const_200_to_fp16 = const()[name = tensor("const_200_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(750656)))]; + tensor 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("conv2d_30_1_cast_fp16")]; + tensor Conv2D_49x_pad_type_0 = const()[name = tensor("Conv2D_49x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_49x_strides_0 = const()[name = tensor("Conv2D_49x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_49x_dilations_0 = const()[name = tensor("Conv2D_49x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_49x_groups_0 = const()[name = tensor("Conv2D_49x_groups_0"), val = tensor(1)]; + tensor Conv2D_49x_pad_0 = const()[name = tensor("Conv2D_49x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_124_to_fp16 = const()[name = tensor("transpose_124_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(750976)))]; + tensor const_201_to_fp16 = const()[name = tensor("const_201_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(767424)))]; + tensor 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("conv2d_46_1_cast_fp16")]; + tensor 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("add_14__xeno_compat__1_cast_fp16")]; + tensor 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("add_22__xeno_compat__1_cast_fp16")]; + tensor add_22__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_22__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(767744)))]; + tensor 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("add_22__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_30_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_30_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(768064)))]; + tensor 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("p_re_lu_30_prelu_1_add_cast_fp16")]; + tensor max_pool_4_kernel_sizes_0 = const()[name = tensor("max_pool_4_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_4_strides_0 = const()[name = tensor("max_pool_4_strides_0"), val = tensor([2, 2])]; + tensor max_pool_4_pad_type_0 = const()[name = tensor("max_pool_4_pad_type_0"), val = tensor("valid")]; + tensor max_pool_4_pad_0 = const()[name = tensor("max_pool_4_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_4_ceil_mode_0 = const()[name = tensor("max_pool_4_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_4_cast_fp16")]; + tensor Conv2D_50x_pad_type_0 = const()[name = tensor("Conv2D_50x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_50x_strides_0 = const()[name = tensor("Conv2D_50x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_50x_dilations_0 = const()[name = tensor("Conv2D_50x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_50x_groups_0 = const()[name = tensor("Conv2D_50x_groups_0"), val = tensor(1)]; + tensor Conv2D_50x_pad_0 = const()[name = tensor("Conv2D_50x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_127_to_fp16 = const()[name = tensor("transpose_127_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(768384)))]; + tensor const_202_to_fp16 = const()[name = tensor("const_202_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(833984)))]; + tensor 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("conv2d_31_1_cast_fp16")]; + tensor max_pool_5_kernel_sizes_0 = const()[name = tensor("max_pool_5_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_5_strides_0 = const()[name = tensor("max_pool_5_strides_0"), val = tensor([2, 2])]; + tensor max_pool_5_pad_type_0 = const()[name = tensor("max_pool_5_pad_type_0"), val = tensor("valid")]; + tensor max_pool_5_pad_0 = const()[name = tensor("max_pool_5_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_5_ceil_mode_0 = const()[name = tensor("max_pool_5_ceil_mode_0"), val = tensor(false)]; + tensor 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("max_pool_5_cast_fp16")]; + tensor Conv2D_51x_pad_type_0 = const()[name = tensor("Conv2D_51x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_51x_strides_0 = const()[name = tensor("Conv2D_51x_strides_0"), val = tensor([2, 2])]; + tensor Conv2D_51x_dilations_0 = const()[name = tensor("Conv2D_51x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_51x_groups_0 = const()[name = tensor("Conv2D_51x_groups_0"), val = tensor(1)]; + tensor Conv2D_51x_pad_0 = const()[name = tensor("Conv2D_51x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_130_to_fp16 = const()[name = tensor("transpose_130_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(834176)))]; + tensor const_203_to_fp16 = const()[name = tensor("const_203_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(899776)))]; + tensor 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("conv2d_47_1_cast_fp16")]; + tensor conv2d_47_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_47_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(899968)))]; + tensor 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("conv2d_47_prelu_1_add_cast_fp16")]; + tensor p_re_lu_31_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_31_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(900160)))]; + tensor 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("p_re_lu_31_prelu_1_add_cast_fp16")]; + tensor depthwise_20x_pad_type_0 = const()[name = tensor("depthwise_20x_pad_type_0"), val = tensor("same")]; + tensor depthwise_20x_strides_0 = const()[name = tensor("depthwise_20x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_20x_dilations_0 = const()[name = tensor("depthwise_20x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_20x_groups_0 = const()[name = tensor("depthwise_20x_groups_0"), val = tensor(64)]; + tensor depthwise_20x_pad_0 = const()[name = tensor("depthwise_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_132_to_fp16 = const()[name = tensor("transpose_132_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(900352)))]; + tensor 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("depthwise_20x_cast_fp16")]; + tensor depthwise_21x_pad_type_0 = const()[name = tensor("depthwise_21x_pad_type_0"), val = tensor("same")]; + tensor depthwise_21x_strides_0 = const()[name = tensor("depthwise_21x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_21x_dilations_0 = const()[name = tensor("depthwise_21x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_21x_groups_0 = const()[name = tensor("depthwise_21x_groups_0"), val = tensor(64)]; + tensor depthwise_21x_pad_0 = const()[name = tensor("depthwise_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_134_to_fp16 = const()[name = tensor("transpose_134_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(901568)))]; + tensor 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("depthwise_21x_cast_fp16")]; + tensor Conv2D_52x_pad_type_0 = const()[name = tensor("Conv2D_52x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_52x_strides_0 = const()[name = tensor("Conv2D_52x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_52x_dilations_0 = const()[name = tensor("Conv2D_52x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_52x_groups_0 = const()[name = tensor("Conv2D_52x_groups_0"), val = tensor(1)]; + tensor Conv2D_52x_pad_0 = const()[name = tensor("Conv2D_52x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_136_to_fp16 = const()[name = tensor("transpose_136_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(902784)))]; + tensor const_204_to_fp16 = const()[name = tensor("const_204_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(919232)))]; + tensor 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("conv2d_32_1_cast_fp16")]; + tensor Conv2D_53x_pad_type_0 = const()[name = tensor("Conv2D_53x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_53x_strides_0 = const()[name = tensor("Conv2D_53x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_53x_dilations_0 = const()[name = tensor("Conv2D_53x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_53x_groups_0 = const()[name = tensor("Conv2D_53x_groups_0"), val = tensor(1)]; + tensor Conv2D_53x_pad_0 = const()[name = tensor("Conv2D_53x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_138_to_fp16 = const()[name = tensor("transpose_138_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(919552)))]; + tensor const_205_to_fp16 = const()[name = tensor("const_205_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(936000)))]; + tensor 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("conv2d_48_1_cast_fp16")]; + tensor add_15__xeno_compat__1_cast_fp16 = add(x = max_pool_4_cast_fp16, y = conv2d_32_1_cast_fp16)[name = tensor("add_15__xeno_compat__1_cast_fp16")]; + tensor add_23__xeno_compat__1_cast_fp16 = add(x = max_pool_5_cast_fp16, y = conv2d_48_1_cast_fp16)[name = tensor("add_23__xeno_compat__1_cast_fp16")]; + tensor add_23__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_23__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(936320)))]; + tensor 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("add_23__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_32_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_32_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(936640)))]; + tensor 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("p_re_lu_32_prelu_1_add_cast_fp16")]; + tensor Conv2D_54x_pad_type_0 = const()[name = tensor("Conv2D_54x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_54x_strides_0 = const()[name = tensor("Conv2D_54x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_54x_dilations_0 = const()[name = tensor("Conv2D_54x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_54x_groups_0 = const()[name = tensor("Conv2D_54x_groups_0"), val = tensor(1)]; + tensor Conv2D_54x_pad_0 = const()[name = tensor("Conv2D_54x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_140_to_fp16 = const()[name = tensor("transpose_140_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(936960)))]; + tensor const_206_to_fp16 = const()[name = tensor("const_206_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(953408)))]; + tensor 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("conv2d_33_1_cast_fp16")]; + tensor Conv2D_55x_pad_type_0 = const()[name = tensor("Conv2D_55x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_55x_strides_0 = const()[name = tensor("Conv2D_55x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_55x_dilations_0 = const()[name = tensor("Conv2D_55x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_55x_groups_0 = const()[name = tensor("Conv2D_55x_groups_0"), val = tensor(1)]; + tensor Conv2D_55x_pad_0 = const()[name = tensor("Conv2D_55x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_142_to_fp16 = const()[name = tensor("transpose_142_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(953600)))]; + tensor const_207_to_fp16 = const()[name = tensor("const_207_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(970048)))]; + tensor 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("conv2d_49_1_cast_fp16")]; + tensor conv2d_49_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_49_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(970240)))]; + tensor 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("conv2d_49_prelu_1_add_cast_fp16")]; + tensor p_re_lu_33_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_33_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(970432)))]; + tensor 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("p_re_lu_33_prelu_1_add_cast_fp16")]; + tensor depthwise_22x_pad_type_0 = const()[name = tensor("depthwise_22x_pad_type_0"), val = tensor("same")]; + tensor depthwise_22x_strides_0 = const()[name = tensor("depthwise_22x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_22x_dilations_0 = const()[name = tensor("depthwise_22x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_22x_groups_0 = const()[name = tensor("depthwise_22x_groups_0"), val = tensor(64)]; + tensor depthwise_22x_pad_0 = const()[name = tensor("depthwise_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_144_to_fp16 = const()[name = tensor("transpose_144_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(970624)))]; + tensor 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("depthwise_22x_cast_fp16")]; + tensor depthwise_23x_pad_type_0 = const()[name = tensor("depthwise_23x_pad_type_0"), val = tensor("same")]; + tensor depthwise_23x_strides_0 = const()[name = tensor("depthwise_23x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_23x_dilations_0 = const()[name = tensor("depthwise_23x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_23x_groups_0 = const()[name = tensor("depthwise_23x_groups_0"), val = tensor(64)]; + tensor depthwise_23x_pad_0 = const()[name = tensor("depthwise_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_146_to_fp16 = const()[name = tensor("transpose_146_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(971840)))]; + tensor 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("depthwise_23x_cast_fp16")]; + tensor Conv2D_56x_pad_type_0 = const()[name = tensor("Conv2D_56x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_56x_strides_0 = const()[name = tensor("Conv2D_56x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_56x_dilations_0 = const()[name = tensor("Conv2D_56x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_56x_groups_0 = const()[name = tensor("Conv2D_56x_groups_0"), val = tensor(1)]; + tensor Conv2D_56x_pad_0 = const()[name = tensor("Conv2D_56x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_148_to_fp16 = const()[name = tensor("transpose_148_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(973056)))]; + tensor const_208_to_fp16 = const()[name = tensor("const_208_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(989504)))]; + tensor 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("conv2d_34_1_cast_fp16")]; + tensor Conv2D_57x_pad_type_0 = const()[name = tensor("Conv2D_57x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_57x_strides_0 = const()[name = tensor("Conv2D_57x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_57x_dilations_0 = const()[name = tensor("Conv2D_57x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_57x_groups_0 = const()[name = tensor("Conv2D_57x_groups_0"), val = tensor(1)]; + tensor Conv2D_57x_pad_0 = const()[name = tensor("Conv2D_57x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_150_to_fp16 = const()[name = tensor("transpose_150_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(989824)))]; + tensor const_209_to_fp16 = const()[name = tensor("const_209_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1006272)))]; + tensor 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("conv2d_50_1_cast_fp16")]; + tensor 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("add_16__xeno_compat__1_cast_fp16")]; + tensor 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("add_24__xeno_compat__1_cast_fp16")]; + tensor add_24__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_24__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1006592)))]; + tensor 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("add_24__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_34_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_34_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1006912)))]; + tensor 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("p_re_lu_34_prelu_1_add_cast_fp16")]; + tensor Conv2D_58x_pad_type_0 = const()[name = tensor("Conv2D_58x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_58x_strides_0 = const()[name = tensor("Conv2D_58x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_58x_dilations_0 = const()[name = tensor("Conv2D_58x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_58x_groups_0 = const()[name = tensor("Conv2D_58x_groups_0"), val = tensor(1)]; + tensor Conv2D_58x_pad_0 = const()[name = tensor("Conv2D_58x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_152_to_fp16 = const()[name = tensor("transpose_152_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1007232)))]; + tensor const_210_to_fp16 = const()[name = tensor("const_210_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1023680)))]; + tensor 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("conv2d_35_1_cast_fp16")]; + tensor Conv2D_59x_pad_type_0 = const()[name = tensor("Conv2D_59x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_59x_strides_0 = const()[name = tensor("Conv2D_59x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_59x_dilations_0 = const()[name = tensor("Conv2D_59x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_59x_groups_0 = const()[name = tensor("Conv2D_59x_groups_0"), val = tensor(1)]; + tensor Conv2D_59x_pad_0 = const()[name = tensor("Conv2D_59x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_154_to_fp16 = const()[name = tensor("transpose_154_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1023872)))]; + tensor const_211_to_fp16 = const()[name = tensor("const_211_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040320)))]; + tensor 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("conv2d_51_1_cast_fp16")]; + tensor conv2d_51_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("conv2d_51_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040512)))]; + tensor 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("conv2d_51_prelu_1_add_cast_fp16")]; + tensor p_re_lu_35_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_35_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040704)))]; + tensor 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("p_re_lu_35_prelu_1_add_cast_fp16")]; + tensor depthwise_24x_pad_type_0 = const()[name = tensor("depthwise_24x_pad_type_0"), val = tensor("same")]; + tensor depthwise_24x_strides_0 = const()[name = tensor("depthwise_24x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_24x_dilations_0 = const()[name = tensor("depthwise_24x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_24x_groups_0 = const()[name = tensor("depthwise_24x_groups_0"), val = tensor(64)]; + tensor depthwise_24x_pad_0 = const()[name = tensor("depthwise_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_156_to_fp16 = const()[name = tensor("transpose_156_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040896)))]; + tensor 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("depthwise_24x_cast_fp16")]; + tensor depthwise_25x_pad_type_0 = const()[name = tensor("depthwise_25x_pad_type_0"), val = tensor("same")]; + tensor depthwise_25x_strides_0 = const()[name = tensor("depthwise_25x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_25x_dilations_0 = const()[name = tensor("depthwise_25x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_25x_groups_0 = const()[name = tensor("depthwise_25x_groups_0"), val = tensor(64)]; + tensor depthwise_25x_pad_0 = const()[name = tensor("depthwise_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_158_to_fp16 = const()[name = tensor("transpose_158_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1042112)))]; + tensor 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("depthwise_25x_cast_fp16")]; + tensor Conv2D_60x_pad_type_0 = const()[name = tensor("Conv2D_60x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_60x_strides_0 = const()[name = tensor("Conv2D_60x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_60x_dilations_0 = const()[name = tensor("Conv2D_60x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_60x_groups_0 = const()[name = tensor("Conv2D_60x_groups_0"), val = tensor(1)]; + tensor Conv2D_60x_pad_0 = const()[name = tensor("Conv2D_60x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_160_to_fp16 = const()[name = tensor("transpose_160_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1043328)))]; + tensor const_212_to_fp16 = const()[name = tensor("const_212_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1059776)))]; + tensor 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("conv2d_36_1_cast_fp16")]; + tensor Conv2D_61x_pad_type_0 = const()[name = tensor("Conv2D_61x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_61x_strides_0 = const()[name = tensor("Conv2D_61x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_61x_dilations_0 = const()[name = tensor("Conv2D_61x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_61x_groups_0 = const()[name = tensor("Conv2D_61x_groups_0"), val = tensor(1)]; + tensor Conv2D_61x_pad_0 = const()[name = tensor("Conv2D_61x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_162_to_fp16 = const()[name = tensor("transpose_162_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1060096)))]; + tensor const_213_to_fp16 = const()[name = tensor("const_213_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1076544)))]; + tensor 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("conv2d_52_1_cast_fp16")]; + tensor 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("add_17__xeno_compat__1_cast_fp16")]; + tensor 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("add_25__xeno_compat__1_cast_fp16")]; + tensor add_25__xeno_compat__1_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("add_25__xeno_compat__1_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1076864)))]; + tensor 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("add_25__xeno_compat__1_prelu_1_add_cast_fp16")]; + tensor p_re_lu_36_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("p_re_lu_36_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1077184)))]; + tensor 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("p_re_lu_36_prelu_1_add_cast_fp16")]; + tensor Conv2D_62x_pad_type_0 = const()[name = tensor("Conv2D_62x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_62x_strides_0 = const()[name = tensor("Conv2D_62x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_62x_dilations_0 = const()[name = tensor("Conv2D_62x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_62x_groups_0 = const()[name = tensor("Conv2D_62x_groups_0"), val = tensor(1)]; + tensor Conv2D_62x_pad_0 = const()[name = tensor("Conv2D_62x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1077504)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1295680)))]; + tensor 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("conv_0_cast_fp16")]; + tensor Conv2D_62_perm_0 = const()[name = tensor("Conv2D_62_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_63x_pad_type_0 = const()[name = tensor("Conv2D_63x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_63x_strides_0 = const()[name = tensor("Conv2D_63x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_63x_dilations_0 = const()[name = tensor("Conv2D_63x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_63x_groups_0 = const()[name = tensor("Conv2D_63x_groups_0"), val = tensor(1)]; + tensor Conv2D_63x_pad_0 = const()[name = tensor("Conv2D_63x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_1_weight_0_to_fp16 = const()[name = tensor("conv_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1296192)))]; + tensor conv_1_bias_0_to_fp16 = const()[name = tensor("conv_1_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1311616)))]; + tensor 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("conv_1_cast_fp16")]; + tensor Conv2D_63_perm_0 = const()[name = tensor("Conv2D_63_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor conv_eyes_contours_and_brows_cast_fp16 = transpose(perm = Conv2D_62_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_169")]; + tensor 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("output_eyes_contours_and_brows_cast_fp16")]; + tensor output_eyes_contours_and_brows_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("output_eyes_contours_and_brows_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor conv_iris_cast_fp16 = transpose(perm = Conv2D_63_perm_0, x = conv_1_cast_fp16)[name = tensor("transpose_168")]; + tensor output_iris_cast_fp16 = reshape(shape = output_iris_shape, x = conv_iris_cast_fp16)[name = tensor("output_iris_cast_fp16")]; + tensor output_iris_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("output_iris_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor output_iris = cast(dtype = output_iris_cast_fp16_to_fp32_dtype_0, x = output_iris_cast_fp16)[name = tensor("cast_1")]; + tensor 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("cast_2")]; + } -> (output_eyes_contours_and_brows, output_iris); +} \ No newline at end of file diff --git a/compiled/iris_landmark.mlmodelc/weights/weight.bin b/compiled/iris_landmark.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..4ab15d29d0782c8d45d16765b1b978aeb810c625 --- /dev/null +++ b/compiled/iris_landmark.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8503c3a6396c2616f4879916f08ff3702cc9fe7d9f1a62618396fc3b5747859b +size 1311710 diff --git a/compiled/palm_detection_full.mlmodelc/analytics/coremldata.bin b/compiled/palm_detection_full.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..03773224144fc9904c944a61102ad5f374762209 --- /dev/null +++ b/compiled/palm_detection_full.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8a6c7067a46c3679e26acbca031c7897bb818cfd2bea1942e1dcbae22490f9c6 +size 243 diff --git a/compiled/palm_detection_full.mlmodelc/coremldata.bin b/compiled/palm_detection_full.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..98a746c3734a76685046064df53af2d327367aee --- /dev/null +++ b/compiled/palm_detection_full.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:39f41608128171770bc43020714a87c7dad9f782d51ca3ba42ba49fd44ff7fdb +size 291 diff --git a/compiled/palm_detection_full.mlmodelc/metadata.json b/compiled/palm_detection_full.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..12f451430dea5f0c05f507d8d85ff7c98f04d4f7 --- /dev/null +++ b/compiled/palm_detection_full.mlmodelc/metadata.json @@ -0,0 +1,78 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 2016 × 18)", + "shortDescription" : "", + "shape" : "[1, 2016, 18]", + "name" : "Identity", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 2016 × 1)", + "shortDescription" : "", + "shape" : "[1, 2016, 1]", + "name" : "Identity_1", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Concat" : 2, + "Cast" : 3, + "Conv" : 63, + "Prelu" : 31, + "Pad" : 3, + "Transpose" : 5, + "Add" : 30, + "ResizeBilinear" : 2, + "Reshape" : 4, + "MaxPool" : 4 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 192 × 192 × 3)", + "shortDescription" : "", + "shape" : "[1, 192, 192, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "palm_detection_full", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/palm_detection_full.mlmodelc/model.mil b/compiled/palm_detection_full.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..b25b9519db75a52431812c9c9ed5aebd6ba35286 --- /dev/null +++ b/compiled/palm_detection_full.mlmodelc/model.mil @@ -0,0 +1,648 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor model_1_model_reshaped_regressor_palm_8_Reshape_shape = const()[name = tensor("model_1_model_reshaped_regressor_palm_8_Reshape_shape"), val = tensor([1, -1, 18])]; + tensor model_1_model_reshaped_regressor_palm_16_Reshape_shape = const()[name = tensor("model_1_model_reshaped_regressor_palm_16_Reshape_shape"), val = tensor([1, -1, 18])]; + tensor Identity_axis = const()[name = tensor("Identity_axis"), val = tensor(1)]; + tensor model_1_model_reshaped_classifier_palm_8_Reshape_shape = const()[name = tensor("model_1_model_reshaped_classifier_palm_8_Reshape_shape"), val = tensor([1, -1, 1])]; + tensor model_1_model_reshaped_classifier_palm_16_Reshape_shape = const()[name = tensor("model_1_model_reshaped_classifier_palm_16_Reshape_shape"), val = tensor([1, -1, 1])]; + tensor Identity_1_axis = const()[name = tensor("Identity_1_axis"), val = tensor(1)]; + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_99_to_fp16 = const()[name = tensor("const_99_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4928)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_5")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_136")]; + tensor model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16 = conv(bias = const_99_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("model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16")]; + tensor model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5056)))]; + tensor model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16)[name = tensor("model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(32)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5184)))]; + tensor depthwisex_cast_fp16 = conv(dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwisex_cast_fp16")]; + tensor Conv2D_1x_pad_type_0 = const()[name = tensor("Conv2D_1x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_1x_strides_0 = const()[name = tensor("Conv2D_1x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_dilations_0 = const()[name = tensor("Conv2D_1x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_groups_0 = const()[name = tensor("Conv2D_1x_groups_0"), val = tensor(1)]; + tensor Conv2D_1x_pad_0 = const()[name = tensor("Conv2D_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6848)))]; + tensor const_100_to_fp16 = const()[name = tensor("const_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8960)))]; + tensor model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16 = conv(bias = const_100_to_fp16, dilations = Conv2D_1x_dilations_0, groups = Conv2D_1x_groups_0, pad = Conv2D_1x_pad_0, pad_type = Conv2D_1x_pad_type_0, strides = Conv2D_1x_strides_0, weight = transpose_4_to_fp16, x = depthwisex_cast_fp16)[name = tensor("model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16")]; + tensor model_1_model_add_add_cast_fp16 = add(x = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_add_cast_fp16")]; + tensor model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9088)))]; + tensor model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(32)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9216)))]; + tensor depthwise_1x_cast_fp16 = conv(dilations = depthwise_1x_dilations_0, groups = depthwise_1x_groups_0, pad = depthwise_1x_pad_0, pad_type = depthwise_1x_pad_type_0, strides = depthwise_1x_strides_0, weight = transpose_6_to_fp16, x = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_1x_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10880)))]; + tensor const_101_to_fp16 = const()[name = tensor("const_101_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12992)))]; + tensor model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16 = conv(bias = const_101_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_8_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor("model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16")]; + tensor model_1_model_add_1_add_cast_fp16 = add(x = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_1_add_cast_fp16")]; + tensor model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13120)))]; + tensor model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_1_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(32)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_10_to_fp16 = const()[name = tensor("transpose_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13248)))]; + tensor 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_10_to_fp16, x = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_2x_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_12_to_fp16 = const()[name = tensor("transpose_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14912)))]; + tensor const_102_to_fp16 = const()[name = tensor("const_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17024)))]; + tensor model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16 = conv(bias = const_102_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_12_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor("model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16")]; + tensor model_1_model_add_2_add_cast_fp16 = add(x = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_2_add_cast_fp16")]; + tensor model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17152)))]; + tensor model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_2_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(32)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_14_to_fp16 = const()[name = tensor("transpose_14_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17280)))]; + tensor 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_14_to_fp16, x = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_3x_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_16_to_fp16 = const()[name = tensor("transpose_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18944)))]; + tensor const_103_to_fp16 = const()[name = tensor("const_103_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21056)))]; + tensor model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16 = conv(bias = const_103_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_16_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor("model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16")]; + tensor model_1_model_add_3_add_cast_fp16 = add(x = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_4_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_3_add_cast_fp16")]; + tensor model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21184)))]; + tensor model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_3_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("same")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_0_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(32)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_19_to_fp16 = const()[name = tensor("transpose_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21312)))]; + tensor depthwise_4x_cast_fp16 = conv(dilations = depthwise_4x_dilations_0, groups = depthwise_4x_groups_0, pad = depthwise_4x_pad_0, pad_type = depthwise_4x_pad_type_0, strides = depthwise_4x_strides_0, weight = transpose_19_to_fp16, x = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_4x_cast_fp16")]; + tensor pad_0_mode_0 = const()[name = tensor("pad_0_mode_0"), val = tensor("constant")]; + tensor const_44 = const()[name = tensor("const_44"), val = tensor([0, 0, 0, 32, 0, 0, 0, 0])]; + tensor const_5_to_fp16 = const()[name = tensor("const_5_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_0_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = pad_0_mode_0, pad = const_44, x = max_pool_0_cast_fp16)[name = tensor("pad_0_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_21_to_fp16 = const()[name = tensor("transpose_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22976)))]; + tensor const_104_to_fp16 = const()[name = tensor("const_104_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27136)))]; + tensor model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16 = conv(bias = const_104_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_21_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor("model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16")]; + tensor model_1_model_add_4_add_cast_fp16 = add(x = pad_0_cast_fp16, y = model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_4_add_cast_fp16")]; + tensor model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27328)))]; + tensor model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_4_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(64)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_23_to_fp16 = const()[name = tensor("transpose_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27520)))]; + tensor 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_23_to_fp16, x = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_5x_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_25_to_fp16 = const()[name = tensor("transpose_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30784)))]; + tensor const_105_to_fp16 = const()[name = tensor("const_105_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39040)))]; + tensor model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16 = conv(bias = const_105_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_25_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor("model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16")]; + tensor model_1_model_add_5_add_cast_fp16 = add(x = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_5_add_cast_fp16")]; + tensor model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39232)))]; + tensor model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_5_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(64)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_27_to_fp16 = const()[name = tensor("transpose_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39424)))]; + tensor 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_27_to_fp16, x = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_6x_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_29_to_fp16 = const()[name = tensor("transpose_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42688)))]; + tensor const_106_to_fp16 = const()[name = tensor("const_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50944)))]; + tensor model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16 = conv(bias = const_106_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_29_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor("model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16")]; + tensor model_1_model_add_6_add_cast_fp16 = add(x = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_6_add_cast_fp16")]; + tensor model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51136)))]; + tensor model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_6_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(64)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_31_to_fp16 = const()[name = tensor("transpose_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51328)))]; + tensor 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_31_to_fp16, x = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_7x_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_33_to_fp16 = const()[name = tensor("transpose_33_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54592)))]; + tensor const_107_to_fp16 = const()[name = tensor("const_107_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62848)))]; + tensor model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_8_Conv2D1_cast_fp16 = conv(bias = const_107_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_33_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor("model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_8_Conv2D1_cast_fp16")]; + tensor model_1_model_add_7_add_cast_fp16 = add(x = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_8_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_7_add_cast_fp16")]; + tensor model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63040)))]; + tensor model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_7_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(64)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_35_to_fp16 = const()[name = tensor("transpose_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63232)))]; + tensor 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_35_to_fp16, x = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_8x_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_37_to_fp16 = const()[name = tensor("transpose_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66496)))]; + tensor const_108_to_fp16 = const()[name = tensor("const_108_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74752)))]; + tensor model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_9_Conv2D1_cast_fp16 = conv(bias = const_108_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_37_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor("model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_9_Conv2D1_cast_fp16")]; + tensor model_1_model_add_8_add_cast_fp16 = add(x = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_depthwise_conv2d_9_depthwise_model_1_model_conv2d_9_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_8_add_cast_fp16")]; + tensor model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74944)))]; + tensor model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_8_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_1_kernel_sizes_0 = const()[name = tensor("max_pool_1_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_1_strides_0 = const()[name = tensor("max_pool_1_strides_0"), val = tensor([2, 2])]; + tensor max_pool_1_pad_type_0 = const()[name = tensor("max_pool_1_pad_type_0"), val = tensor("same")]; + tensor max_pool_1_pad_0 = const()[name = tensor("max_pool_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_1_ceil_mode_0 = const()[name = tensor("max_pool_1_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_1_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(64)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_40_to_fp16 = const()[name = tensor("transpose_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75136)))]; + tensor 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_40_to_fp16, x = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_9x_cast_fp16")]; + tensor pad_1_mode_0 = const()[name = tensor("pad_1_mode_0"), val = tensor("constant")]; + tensor const_55 = const()[name = tensor("const_55"), val = tensor([0, 0, 0, 64, 0, 0, 0, 0])]; + tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_1_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = pad_1_mode_0, pad = const_55, x = max_pool_1_cast_fp16)[name = tensor("pad_1_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_42_to_fp16 = const()[name = tensor("transpose_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78400)))]; + tensor const_109_to_fp16 = const()[name = tensor("const_109_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94848)))]; + tensor model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16 = conv(bias = const_109_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_42_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor("model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16")]; + tensor model_1_model_add_9_add_cast_fp16 = add(x = pad_1_cast_fp16, y = model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_9_add_cast_fp16")]; + tensor model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95168)))]; + tensor model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_9_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(128)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_44_to_fp16 = const()[name = tensor("transpose_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95488)))]; + tensor 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_44_to_fp16, x = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_10x_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_46_to_fp16 = const()[name = tensor("transpose_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101952)))]; + tensor const_110_to_fp16 = const()[name = tensor("const_110_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134784)))]; + tensor model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16 = conv(bias = const_110_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_46_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor("model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16")]; + tensor model_1_model_add_10_add_cast_fp16 = add(x = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_10_add_cast_fp16")]; + tensor model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135104)))]; + tensor model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_10_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(128)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_48_to_fp16 = const()[name = tensor("transpose_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135424)))]; + tensor 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_48_to_fp16, x = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_11x_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_50_to_fp16 = const()[name = tensor("transpose_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141888)))]; + tensor const_111_to_fp16 = const()[name = tensor("const_111_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174720)))]; + tensor model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16 = conv(bias = const_111_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_50_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor("model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16")]; + tensor model_1_model_add_11_add_cast_fp16 = add(x = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_11_add_cast_fp16")]; + tensor model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175040)))]; + tensor model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_11_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(128)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_52_to_fp16 = const()[name = tensor("transpose_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175360)))]; + tensor 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_52_to_fp16, x = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_12x_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_54_to_fp16 = const()[name = tensor("transpose_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181824)))]; + tensor const_112_to_fp16 = const()[name = tensor("const_112_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214656)))]; + tensor model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16 = conv(bias = const_112_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_54_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor("model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16")]; + tensor model_1_model_add_12_add_cast_fp16 = add(x = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_12_add_cast_fp16")]; + tensor model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214976)))]; + tensor model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_12_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(128)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_56_to_fp16 = const()[name = tensor("transpose_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215296)))]; + tensor 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_56_to_fp16, x = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_13x_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_58_to_fp16 = const()[name = tensor("transpose_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221760)))]; + tensor const_113_to_fp16 = const()[name = tensor("const_113_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254592)))]; + tensor model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16 = conv(bias = const_113_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_58_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor("model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16")]; + tensor model_1_model_add_13_add_cast_fp16 = add(x = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_13_add_cast_fp16")]; + tensor model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254912)))]; + tensor model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_13_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_2_kernel_sizes_0 = const()[name = tensor("max_pool_2_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_2_strides_0 = const()[name = tensor("max_pool_2_strides_0"), val = tensor([2, 2])]; + tensor max_pool_2_pad_type_0 = const()[name = tensor("max_pool_2_pad_type_0"), val = tensor("same")]; + tensor max_pool_2_pad_0 = const()[name = tensor("max_pool_2_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_2_ceil_mode_0 = const()[name = tensor("max_pool_2_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_2_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(128)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_61_to_fp16 = const()[name = tensor("transpose_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255232)))]; + tensor 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_61_to_fp16, x = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_14x_cast_fp16")]; + tensor pad_2_mode_0 = const()[name = tensor("pad_2_mode_0"), val = tensor("constant")]; + tensor const_76 = const()[name = tensor("const_76"), val = tensor([0, 0, 0, 128, 0, 0, 0, 0])]; + tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_2_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = pad_2_mode_0, pad = const_76, x = max_pool_2_cast_fp16)[name = tensor("pad_2_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_63_to_fp16 = const()[name = tensor("transpose_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261696)))]; + tensor const_114_to_fp16 = const()[name = tensor("const_114_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(327296)))]; + tensor model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16 = conv(bias = const_114_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_63_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor("model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16")]; + tensor model_1_model_add_14_add_cast_fp16 = add(x = pad_2_cast_fp16, y = model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_14_add_cast_fp16")]; + tensor model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(327872)))]; + tensor model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_14_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(256)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_65_to_fp16 = const()[name = tensor("transpose_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328448)))]; + tensor 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_65_to_fp16, x = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_15x_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_67_to_fp16 = const()[name = tensor("transpose_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341312)))]; + tensor const_115_to_fp16 = const()[name = tensor("const_115_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(472448)))]; + tensor model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16 = conv(bias = const_115_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_67_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor("model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16")]; + tensor model_1_model_add_15_add_cast_fp16 = add(x = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_15_add_cast_fp16")]; + tensor model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473024)))]; + tensor model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_15_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_16x_pad_type_0 = const()[name = tensor("depthwise_16x_pad_type_0"), val = tensor("same")]; + tensor depthwise_16x_strides_0 = const()[name = tensor("depthwise_16x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_16x_dilations_0 = const()[name = tensor("depthwise_16x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_16x_groups_0 = const()[name = tensor("depthwise_16x_groups_0"), val = tensor(256)]; + tensor depthwise_16x_pad_0 = const()[name = tensor("depthwise_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_69_to_fp16 = const()[name = tensor("transpose_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473600)))]; + tensor 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_69_to_fp16, x = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_16x_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_71_to_fp16 = const()[name = tensor("transpose_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486464)))]; + tensor const_116_to_fp16 = const()[name = tensor("const_116_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(617600)))]; + tensor model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16 = conv(bias = const_116_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_71_to_fp16, x = depthwise_16x_cast_fp16)[name = tensor("model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16")]; + tensor model_1_model_add_16_add_cast_fp16 = add(x = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_16_add_cast_fp16")]; + tensor model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(618176)))]; + tensor model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_16_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_17x_pad_type_0 = const()[name = tensor("depthwise_17x_pad_type_0"), val = tensor("same")]; + tensor depthwise_17x_strides_0 = const()[name = tensor("depthwise_17x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_17x_dilations_0 = const()[name = tensor("depthwise_17x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_17x_groups_0 = const()[name = tensor("depthwise_17x_groups_0"), val = tensor(256)]; + tensor depthwise_17x_pad_0 = const()[name = tensor("depthwise_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_73_to_fp16 = const()[name = tensor("transpose_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(618752)))]; + tensor 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_73_to_fp16, x = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_17x_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_75_to_fp16 = const()[name = tensor("transpose_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(631616)))]; + tensor const_117_to_fp16 = const()[name = tensor("const_117_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(762752)))]; + tensor model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16 = conv(bias = const_117_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_75_to_fp16, x = depthwise_17x_cast_fp16)[name = tensor("model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16")]; + tensor model_1_model_add_17_add_cast_fp16 = add(x = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_17_add_cast_fp16")]; + tensor model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(763328)))]; + tensor model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_17_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_18x_pad_type_0 = const()[name = tensor("depthwise_18x_pad_type_0"), val = tensor("same")]; + tensor depthwise_18x_strides_0 = const()[name = tensor("depthwise_18x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_18x_dilations_0 = const()[name = tensor("depthwise_18x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_18x_groups_0 = const()[name = tensor("depthwise_18x_groups_0"), val = tensor(256)]; + tensor depthwise_18x_pad_0 = const()[name = tensor("depthwise_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_77_to_fp16 = const()[name = tensor("transpose_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(763904)))]; + tensor 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_77_to_fp16, x = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_18x_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_79_to_fp16 = const()[name = tensor("transpose_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(776768)))]; + tensor const_118_to_fp16 = const()[name = tensor("const_118_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(907904)))]; + tensor model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16 = conv(bias = const_118_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_79_to_fp16, x = depthwise_18x_cast_fp16)[name = tensor("model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16")]; + tensor model_1_model_add_18_add_cast_fp16 = add(x = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_18_add_cast_fp16")]; + tensor model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(908480)))]; + tensor model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_18_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_3_kernel_sizes_0 = const()[name = tensor("max_pool_3_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_3_strides_0 = const()[name = tensor("max_pool_3_strides_0"), val = tensor([2, 2])]; + tensor max_pool_3_pad_type_0 = const()[name = tensor("max_pool_3_pad_type_0"), val = tensor("same")]; + tensor max_pool_3_pad_0 = const()[name = tensor("max_pool_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_3_ceil_mode_0 = const()[name = tensor("max_pool_3_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_3_cast_fp16")]; + tensor depthwise_19x_pad_type_0 = const()[name = tensor("depthwise_19x_pad_type_0"), val = tensor("same")]; + tensor depthwise_19x_strides_0 = const()[name = tensor("depthwise_19x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_19x_dilations_0 = const()[name = tensor("depthwise_19x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_19x_groups_0 = const()[name = tensor("depthwise_19x_groups_0"), val = tensor(256)]; + tensor depthwise_19x_pad_0 = const()[name = tensor("depthwise_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_82_to_fp16 = const()[name = tensor("transpose_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(909056)))]; + tensor 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_82_to_fp16, x = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_19x_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_84_to_fp16 = const()[name = tensor("transpose_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(921920)))]; + tensor const_119_to_fp16 = const()[name = tensor("const_119_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1053056)))]; + tensor model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_20_Conv2D1_cast_fp16 = conv(bias = const_119_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_84_to_fp16, x = depthwise_19x_cast_fp16)[name = tensor("model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_20_Conv2D1_cast_fp16")]; + tensor model_1_model_add_19_add_cast_fp16 = add(x = max_pool_3_cast_fp16, y = model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_20_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_19_add_cast_fp16")]; + tensor model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1053632)))]; + tensor model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_19_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_20x_pad_type_0 = const()[name = tensor("depthwise_20x_pad_type_0"), val = tensor("same")]; + tensor depthwise_20x_strides_0 = const()[name = tensor("depthwise_20x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_20x_dilations_0 = const()[name = tensor("depthwise_20x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_20x_groups_0 = const()[name = tensor("depthwise_20x_groups_0"), val = tensor(256)]; + tensor depthwise_20x_pad_0 = const()[name = tensor("depthwise_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_86_to_fp16 = const()[name = tensor("transpose_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1054208)))]; + tensor 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_86_to_fp16, x = model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_20x_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_88_to_fp16 = const()[name = tensor("transpose_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1067072)))]; + tensor const_120_to_fp16 = const()[name = tensor("const_120_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1198208)))]; + tensor model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16 = conv(bias = const_120_to_fp16, dilations = Conv2D_21x_dilations_0, groups = Conv2D_21x_groups_0, pad = Conv2D_21x_pad_0, pad_type = Conv2D_21x_pad_type_0, strides = Conv2D_21x_strides_0, weight = transpose_88_to_fp16, x = depthwise_20x_cast_fp16)[name = tensor("model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16")]; + tensor model_1_model_add_20_add_cast_fp16 = add(x = model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_20_add_cast_fp16")]; + tensor model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1198784)))]; + tensor model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_20_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_21x_pad_type_0 = const()[name = tensor("depthwise_21x_pad_type_0"), val = tensor("same")]; + tensor depthwise_21x_strides_0 = const()[name = tensor("depthwise_21x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_21x_dilations_0 = const()[name = tensor("depthwise_21x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_21x_groups_0 = const()[name = tensor("depthwise_21x_groups_0"), val = tensor(256)]; + tensor depthwise_21x_pad_0 = const()[name = tensor("depthwise_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_90_to_fp16 = const()[name = tensor("transpose_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1199360)))]; + tensor 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_90_to_fp16, x = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_21x_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_92_to_fp16 = const()[name = tensor("transpose_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1212224)))]; + tensor const_121_to_fp16 = const()[name = tensor("const_121_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1343360)))]; + tensor model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_22_Conv2D1_cast_fp16 = conv(bias = const_121_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_92_to_fp16, x = depthwise_21x_cast_fp16)[name = tensor("model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_22_Conv2D1_cast_fp16")]; + tensor model_1_model_add_21_add_cast_fp16 = add(x = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_22_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_21_add_cast_fp16")]; + tensor model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1343936)))]; + tensor model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_21_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_22x_pad_type_0 = const()[name = tensor("depthwise_22x_pad_type_0"), val = tensor("same")]; + tensor depthwise_22x_strides_0 = const()[name = tensor("depthwise_22x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_22x_dilations_0 = const()[name = tensor("depthwise_22x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_22x_groups_0 = const()[name = tensor("depthwise_22x_groups_0"), val = tensor(256)]; + tensor depthwise_22x_pad_0 = const()[name = tensor("depthwise_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_94_to_fp16 = const()[name = tensor("transpose_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1344512)))]; + tensor 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_94_to_fp16, x = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_22x_cast_fp16")]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_96_to_fp16 = const()[name = tensor("transpose_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1357376)))]; + tensor const_122_to_fp16 = const()[name = tensor("const_122_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1488512)))]; + tensor model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16 = conv(bias = const_122_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_96_to_fp16, x = depthwise_22x_cast_fp16)[name = tensor("model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16")]; + tensor model_1_model_add_22_add_cast_fp16 = add(x = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_23_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_22_add_cast_fp16")]; + tensor model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1489088)))]; + tensor model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_22_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_23x_pad_type_0 = const()[name = tensor("depthwise_23x_pad_type_0"), val = tensor("same")]; + tensor depthwise_23x_strides_0 = const()[name = tensor("depthwise_23x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_23x_dilations_0 = const()[name = tensor("depthwise_23x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_23x_groups_0 = const()[name = tensor("depthwise_23x_groups_0"), val = tensor(256)]; + tensor depthwise_23x_pad_0 = const()[name = tensor("depthwise_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_98_to_fp16 = const()[name = tensor("transpose_98_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1489664)))]; + tensor 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_98_to_fp16, x = model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_23x_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_100_to_fp16 = const()[name = tensor("transpose_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1502528)))]; + tensor const_123_to_fp16 = const()[name = tensor("const_123_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1633664)))]; + tensor model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16 = conv(bias = const_123_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_100_to_fp16, x = depthwise_23x_cast_fp16)[name = tensor("model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16")]; + tensor model_1_model_add_23_add_cast_fp16 = add(x = model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_23_add_cast_fp16")]; + tensor model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1634240)))]; + tensor model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_23_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0"), val = tensor(12)]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0"), val = tensor(12)]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0"), val = tensor("STRICT_ALIGN_CORNERS")]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16 = resize_bilinear(sampling_mode = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0, target_size_height = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0, target_size_width = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0, x = model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16")]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_103_to_fp16 = const()[name = tensor("transpose_103_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1634816)))]; + tensor const_124_to_fp16 = const()[name = tensor("const_124_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1765952)))]; + tensor model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_25_BiasAdd_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_25_Conv2D_cast_fp16 = conv(bias = const_124_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_103_to_fp16, x = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16)[name = tensor("model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_25_BiasAdd_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_25_Conv2D_cast_fp16")]; + tensor model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1766528)))]; + tensor model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_25_BiasAdd_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_25_Conv2D_cast_fp16)[name = tensor("model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_add_24_add_cast_fp16 = add(x = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_add_24_add_cast_fp16")]; + tensor depthwise_24x_pad_type_0 = const()[name = tensor("depthwise_24x_pad_type_0"), val = tensor("same")]; + tensor depthwise_24x_strides_0 = const()[name = tensor("depthwise_24x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_24x_dilations_0 = const()[name = tensor("depthwise_24x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_24x_groups_0 = const()[name = tensor("depthwise_24x_groups_0"), val = tensor(256)]; + tensor depthwise_24x_pad_0 = const()[name = tensor("depthwise_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_105_to_fp16 = const()[name = tensor("transpose_105_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1767104)))]; + tensor 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_105_to_fp16, x = model_1_model_add_24_add_cast_fp16)[name = tensor("depthwise_24x_cast_fp16")]; + tensor Conv2D_26x_pad_type_0 = const()[name = tensor("Conv2D_26x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_26x_strides_0 = const()[name = tensor("Conv2D_26x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_dilations_0 = const()[name = tensor("Conv2D_26x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_groups_0 = const()[name = tensor("Conv2D_26x_groups_0"), val = tensor(1)]; + tensor Conv2D_26x_pad_0 = const()[name = tensor("Conv2D_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_107_to_fp16 = const()[name = tensor("transpose_107_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1779968)))]; + tensor const_125_to_fp16 = const()[name = tensor("const_125_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1911104)))]; + tensor model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_26_Conv2D1_cast_fp16 = conv(bias = const_125_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_107_to_fp16, x = depthwise_24x_cast_fp16)[name = tensor("model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_26_Conv2D1_cast_fp16")]; + tensor model_1_model_add_25_add_cast_fp16 = add(x = model_1_model_add_24_add_cast_fp16, y = model_1_model_batch_normalization_26_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D_model_1_model_conv2d_26_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_25_add_cast_fp16")]; + tensor model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1911680)))]; + tensor model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_25_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_25x_pad_type_0 = const()[name = tensor("depthwise_25x_pad_type_0"), val = tensor("same")]; + tensor depthwise_25x_strides_0 = const()[name = tensor("depthwise_25x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_25x_dilations_0 = const()[name = tensor("depthwise_25x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_25x_groups_0 = const()[name = tensor("depthwise_25x_groups_0"), val = tensor(256)]; + tensor depthwise_25x_pad_0 = const()[name = tensor("depthwise_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_109_to_fp16 = const()[name = tensor("transpose_109_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1912256)))]; + tensor 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_109_to_fp16, x = model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_25x_cast_fp16")]; + tensor Conv2D_27x_pad_type_0 = const()[name = tensor("Conv2D_27x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_27x_strides_0 = const()[name = tensor("Conv2D_27x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_dilations_0 = const()[name = tensor("Conv2D_27x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_groups_0 = const()[name = tensor("Conv2D_27x_groups_0"), val = tensor(1)]; + tensor Conv2D_27x_pad_0 = const()[name = tensor("Conv2D_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_111_to_fp16 = const()[name = tensor("transpose_111_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1925120)))]; + tensor const_126_to_fp16 = const()[name = tensor("const_126_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2056256)))]; + tensor model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D1_cast_fp16 = conv(bias = const_126_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_111_to_fp16, x = depthwise_25x_cast_fp16)[name = tensor("model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D1_cast_fp16")]; + tensor model_1_model_add_26_add_cast_fp16 = add(x = model_1_model_p_re_lu_26_add_model_1_model_p_re_lu_26_Relu_model_1_model_p_re_lu_26_Neg_1_model_1_model_p_re_lu_26_Relu_1_model_1_model_p_re_lu_26_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_27_FusedBatchNormV3_model_1_model_conv2d_27_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_26_add_cast_fp16")]; + tensor model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2056832)))]; + tensor model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_26_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0"), val = tensor(24)]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0"), val = tensor(24)]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0"), val = tensor("STRICT_ALIGN_CORNERS")]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16 = resize_bilinear(sampling_mode = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0, target_size_height = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0, target_size_width = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0, x = model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16")]; + tensor Conv2D_29x_pad_type_0 = const()[name = tensor("Conv2D_29x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_29x_strides_0 = const()[name = tensor("Conv2D_29x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_dilations_0 = const()[name = tensor("Conv2D_29x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_groups_0 = const()[name = tensor("Conv2D_29x_groups_0"), val = tensor(1)]; + tensor Conv2D_29x_pad_0 = const()[name = tensor("Conv2D_29x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2057408)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2112768)))]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_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 = conv_0_weight_0_to_fp16, x = model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor Conv2D_29_perm_0 = const()[name = tensor("Conv2D_29_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_28x_pad_type_0 = const()[name = tensor("Conv2D_28x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_28x_strides_0 = const()[name = tensor("Conv2D_28x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_dilations_0 = const()[name = tensor("Conv2D_28x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_groups_0 = const()[name = tensor("Conv2D_28x_groups_0"), val = tensor(1)]; + tensor Conv2D_28x_pad_0 = const()[name = tensor("Conv2D_28x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_1_weight_0_to_fp16 = const()[name = tensor("conv_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2113088)))]; + tensor conv_1_bias_0_to_fp16 = const()[name = tensor("conv_1_bias_0_to_fp16"), val = tensor([0x1.8fp-5, 0x1.77p-4, -0x1.188p-3, -0x1.da4p-3, -0x1.a9p-2, -0x1.004p-1])]; + tensor conv_1_cast_fp16 = conv(bias = conv_1_bias_0_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 = conv_1_weight_0_to_fp16, x = model_1_model_p_re_lu_27_add_model_1_model_p_re_lu_27_Relu_model_1_model_p_re_lu_27_Neg_1_model_1_model_p_re_lu_27_Relu_1_model_1_model_p_re_lu_27_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor Conv2D_28_perm_0 = const()[name = tensor("Conv2D_28_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_30x_pad_type_0 = const()[name = tensor("Conv2D_30x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_30x_strides_0 = const()[name = tensor("Conv2D_30x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_dilations_0 = const()[name = tensor("Conv2D_30x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_30x_groups_0 = const()[name = tensor("Conv2D_30x_groups_0"), val = tensor(1)]; + tensor Conv2D_30x_pad_0 = const()[name = tensor("Conv2D_30x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_118_to_fp16 = const()[name = tensor("transpose_118_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2116224)))]; + tensor const_127_to_fp16 = const()[name = tensor("const_127_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2181824)))]; + tensor model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_conv2d_28_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_28_BiasAdd_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_28_Conv2D_cast_fp16 = conv(bias = const_127_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_118_to_fp16, x = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16)[name = tensor("model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_conv2d_28_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_28_BiasAdd_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_28_Conv2D_cast_fp16")]; + tensor model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_16_NO_PRUNING_Conv2D_model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_29_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_135")]; + tensor model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_regressor_palm_16_Reshape_shape, x = model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_16_NO_PRUNING_Conv2D_model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16")]; + tensor model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_16_NO_PRUNING_Conv2D_model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_28_perm_0, x = conv_1_cast_fp16)[name = tensor("transpose_134")]; + tensor model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_classifier_palm_16_Reshape_shape, x = model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_16_NO_PRUNING_Conv2D_model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16")]; + tensor model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2182144)))]; + tensor model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_28_FusedBatchNormV3_model_1_model_conv2d_28_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_28_BiasAdd_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_28_Conv2D_cast_fp16)[name = tensor("model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_add_27_add_cast_fp16 = add(x = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_p_re_lu_28_add_model_1_model_p_re_lu_28_Relu_model_1_model_p_re_lu_28_Neg_1_model_1_model_p_re_lu_28_Relu_1_model_1_model_p_re_lu_28_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_add_27_add_cast_fp16")]; + tensor depthwise_26x_pad_type_0 = const()[name = tensor("depthwise_26x_pad_type_0"), val = tensor("same")]; + tensor depthwise_26x_strides_0 = const()[name = tensor("depthwise_26x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_26x_dilations_0 = const()[name = tensor("depthwise_26x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_26x_groups_0 = const()[name = tensor("depthwise_26x_groups_0"), val = tensor(128)]; + tensor depthwise_26x_pad_0 = const()[name = tensor("depthwise_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_120_to_fp16 = const()[name = tensor("transpose_120_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2182464)))]; + tensor depthwise_26x_cast_fp16 = conv(dilations = depthwise_26x_dilations_0, groups = depthwise_26x_groups_0, pad = depthwise_26x_pad_0, pad_type = depthwise_26x_pad_type_0, strides = depthwise_26x_strides_0, weight = transpose_120_to_fp16, x = model_1_model_add_27_add_cast_fp16)[name = tensor("depthwise_26x_cast_fp16")]; + tensor Conv2D_31x_pad_type_0 = const()[name = tensor("Conv2D_31x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_31x_strides_0 = const()[name = tensor("Conv2D_31x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_31x_dilations_0 = const()[name = tensor("Conv2D_31x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_31x_groups_0 = const()[name = tensor("Conv2D_31x_groups_0"), val = tensor(1)]; + tensor Conv2D_31x_pad_0 = const()[name = tensor("Conv2D_31x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_122_to_fp16 = const()[name = tensor("transpose_122_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2188928)))]; + tensor const_128_to_fp16 = const()[name = tensor("const_128_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2221760)))]; + tensor model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_29_Conv2D1_cast_fp16 = conv(bias = const_128_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_122_to_fp16, x = depthwise_26x_cast_fp16)[name = tensor("model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_29_Conv2D1_cast_fp16")]; + tensor model_1_model_add_28_add_cast_fp16 = add(x = model_1_model_add_27_add_cast_fp16, y = model_1_model_batch_normalization_29_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D_model_1_model_conv2d_29_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_28_add_cast_fp16")]; + tensor model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2222080)))]; + tensor model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_28_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_27x_pad_type_0 = const()[name = tensor("depthwise_27x_pad_type_0"), val = tensor("same")]; + tensor depthwise_27x_strides_0 = const()[name = tensor("depthwise_27x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_27x_dilations_0 = const()[name = tensor("depthwise_27x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_27x_groups_0 = const()[name = tensor("depthwise_27x_groups_0"), val = tensor(128)]; + tensor depthwise_27x_pad_0 = const()[name = tensor("depthwise_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_124_to_fp16 = const()[name = tensor("transpose_124_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2222400)))]; + tensor depthwise_27x_cast_fp16 = conv(dilations = depthwise_27x_dilations_0, groups = depthwise_27x_groups_0, pad = depthwise_27x_pad_0, pad_type = depthwise_27x_pad_type_0, strides = depthwise_27x_strides_0, weight = transpose_124_to_fp16, x = model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_27x_cast_fp16")]; + tensor Conv2D_32x_pad_type_0 = const()[name = tensor("Conv2D_32x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_32x_strides_0 = const()[name = tensor("Conv2D_32x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_32x_dilations_0 = const()[name = tensor("Conv2D_32x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_32x_groups_0 = const()[name = tensor("Conv2D_32x_groups_0"), val = tensor(1)]; + tensor Conv2D_32x_pad_0 = const()[name = tensor("Conv2D_32x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_126_to_fp16 = const()[name = tensor("transpose_126_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2228864)))]; + tensor const_129_to_fp16 = const()[name = tensor("const_129_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2261696)))]; + tensor model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D1_cast_fp16 = conv(bias = const_129_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_126_to_fp16, x = depthwise_27x_cast_fp16)[name = tensor("model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D1_cast_fp16")]; + tensor model_1_model_add_29_add_cast_fp16 = add(x = model_1_model_p_re_lu_29_add_model_1_model_p_re_lu_29_Relu_model_1_model_p_re_lu_29_Neg_1_model_1_model_p_re_lu_29_Relu_1_model_1_model_p_re_lu_29_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_30_FusedBatchNormV3_model_1_model_conv2d_30_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_29_add_cast_fp16")]; + tensor model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2262016)))]; + tensor model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_29_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_34x_pad_type_0 = const()[name = tensor("Conv2D_34x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_34x_strides_0 = const()[name = tensor("Conv2D_34x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_34x_dilations_0 = const()[name = tensor("Conv2D_34x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_34x_groups_0 = const()[name = tensor("Conv2D_34x_groups_0"), val = tensor(1)]; + tensor Conv2D_34x_pad_0 = const()[name = tensor("Conv2D_34x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_2_weight_0_to_fp16 = const()[name = tensor("conv_2_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2262336)))]; + tensor conv_2_bias_0_to_fp16 = const()[name = tensor("conv_2_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2271616)))]; + tensor conv_2_cast_fp16 = conv(bias = conv_2_bias_0_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 = conv_2_weight_0_to_fp16, x = model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_2_cast_fp16")]; + tensor Conv2D_34_perm_0 = const()[name = tensor("Conv2D_34_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_33x_pad_type_0 = const()[name = tensor("Conv2D_33x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_33x_strides_0 = const()[name = tensor("Conv2D_33x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_33x_dilations_0 = const()[name = tensor("Conv2D_33x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_33x_groups_0 = const()[name = tensor("Conv2D_33x_groups_0"), val = tensor(1)]; + tensor Conv2D_33x_pad_0 = const()[name = tensor("Conv2D_33x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_3_weight_0_to_fp16 = const()[name = tensor("conv_3_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2271808)))]; + tensor conv_3_bias_0_to_fp16 = const()[name = tensor("conv_3_bias_0_to_fp16"), val = tensor([0x1.068p-2, -0x1.2ecp-1])]; + tensor conv_3_cast_fp16 = conv(bias = conv_3_bias_0_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 = conv_3_weight_0_to_fp16, x = model_1_model_p_re_lu_30_add_model_1_model_p_re_lu_30_Relu_model_1_model_p_re_lu_30_Neg_1_model_1_model_p_re_lu_30_Relu_1_model_1_model_p_re_lu_30_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_3_cast_fp16")]; + tensor Conv2D_33_perm_0 = const()[name = tensor("Conv2D_33_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_8_NO_PRUNING_Conv2D_model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_34_perm_0, x = conv_2_cast_fp16)[name = tensor("transpose_133")]; + tensor model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_regressor_palm_8_Reshape_shape, x = model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_8_NO_PRUNING_Conv2D_model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16")]; + tensor model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_8_NO_PRUNING_Conv2D_model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_33_perm_0, x = conv_3_cast_fp16)[name = tensor("transpose_132")]; + tensor model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_classifier_palm_8_Reshape_shape, x = model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_8_NO_PRUNING_Conv2D_model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16")]; + tensor Identity_interleave_0 = const()[name = tensor("Identity_interleave_0"), val = tensor(false)]; + tensor Identity_cast_fp16 = concat(axis = Identity_axis, interleave = Identity_interleave_0, values = (model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16, model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16))[name = tensor("Identity_cast_fp16")]; + tensor Identity_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1_interleave_0 = const()[name = tensor("Identity_1_interleave_0"), val = tensor(false)]; + tensor Identity_1_cast_fp16 = concat(axis = Identity_1_axis, interleave = Identity_1_interleave_0, values = (model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16, model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16))[name = tensor("Identity_1_cast_fp16")]; + tensor Identity_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_1_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1 = cast(dtype = Identity_1_cast_fp16_to_fp32_dtype_0, x = Identity_1_cast_fp16)[name = tensor("cast_3")]; + tensor Identity = cast(dtype = Identity_cast_fp16_to_fp32_dtype_0, x = Identity_cast_fp16)[name = tensor("cast_4")]; + } -> (Identity, Identity_1); +} \ No newline at end of file diff --git a/compiled/palm_detection_full.mlmodelc/weights/weight.bin b/compiled/palm_detection_full.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..d7b0983ce159c64d8da879c34676a0385e73e26b --- /dev/null +++ b/compiled/palm_detection_full.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1305c52bab2d07badb9e18671b925475d9cc9b9c48d3f916185f7f7c93ddd3f1 +size 2272384 diff --git a/compiled/palm_detection_lite.mlmodelc/analytics/coremldata.bin b/compiled/palm_detection_lite.mlmodelc/analytics/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..544d4456326f0cf089c939c25e994ee773f24d07 --- /dev/null +++ b/compiled/palm_detection_lite.mlmodelc/analytics/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:00c4451c4b779c6e864eb3a22023e4b1385498252bff0723566c7683e48e053f +size 243 diff --git a/compiled/palm_detection_lite.mlmodelc/coremldata.bin b/compiled/palm_detection_lite.mlmodelc/coremldata.bin new file mode 100644 index 0000000000000000000000000000000000000000..98a746c3734a76685046064df53af2d327367aee --- /dev/null +++ b/compiled/palm_detection_lite.mlmodelc/coremldata.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:39f41608128171770bc43020714a87c7dad9f782d51ca3ba42ba49fd44ff7fdb +size 291 diff --git a/compiled/palm_detection_lite.mlmodelc/metadata.json b/compiled/palm_detection_lite.mlmodelc/metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..ab0ba807ee3b04d267630bababd7628cea5e37b8 --- /dev/null +++ b/compiled/palm_detection_lite.mlmodelc/metadata.json @@ -0,0 +1,78 @@ +[ + { + "metadataOutputVersion" : "3.0", + "storagePrecision" : "Float16", + "outputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 2016 × 18)", + "shortDescription" : "", + "shape" : "[1, 2016, 18]", + "name" : "Identity", + "type" : "MultiArray" + }, + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 2016 × 1)", + "shortDescription" : "", + "shape" : "[1, 2016, 1]", + "name" : "Identity_1", + "type" : "MultiArray" + } + ], + "modelParameters" : [ + + ], + "specificationVersion" : 6, + "mlProgramOperationTypeHistogram" : { + "Concat" : 2, + "Cast" : 3, + "Conv" : 53, + "Prelu" : 26, + "Pad" : 3, + "Transpose" : 5, + "Add" : 25, + "ResizeBilinear" : 2, + "Reshape" : 4, + "MaxPool" : 4 + }, + "computePrecision" : "Mixed (Float16, Float32, Int32)", + "isUpdatable" : "0", + "stateSchema" : [ + + ], + "availability" : { + "macOS" : "12.0", + "tvOS" : "15.0", + "visionOS" : "1.0", + "watchOS" : "8.0", + "iOS" : "15.0", + "macCatalyst" : "15.0" + }, + "modelType" : { + "name" : "MLModelType_mlProgram" + }, + "userDefinedMetadata" : { + "com.github.apple.coremltools.version" : "8.3.0", + "com.github.apple.coremltools.source" : "tensorflow==2.16.2" + }, + "inputSchema" : [ + { + "hasShapeFlexibility" : "0", + "isOptional" : "0", + "dataType" : "Float32", + "formattedType" : "MultiArray (Float32 1 × 192 × 192 × 3)", + "shortDescription" : "", + "shape" : "[1, 192, 192, 3]", + "name" : "input_1", + "type" : "MultiArray" + } + ], + "generatedClassName" : "palm_detection_lite", + "method" : "predict" + } +] \ No newline at end of file diff --git a/compiled/palm_detection_lite.mlmodelc/model.mil b/compiled/palm_detection_lite.mlmodelc/model.mil new file mode 100644 index 0000000000000000000000000000000000000000..a971a99d49190f320dbc120a07b4d3e580fd681a --- /dev/null +++ b/compiled/palm_detection_lite.mlmodelc/model.mil @@ -0,0 +1,558 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.16.2"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor input_1) { + tensor model_1_model_reshaped_regressor_palm_8_Reshape_shape = const()[name = tensor("model_1_model_reshaped_regressor_palm_8_Reshape_shape"), val = tensor([1, -1, 18])]; + tensor model_1_model_reshaped_regressor_palm_16_Reshape_shape = const()[name = tensor("model_1_model_reshaped_regressor_palm_16_Reshape_shape"), val = tensor([1, -1, 18])]; + tensor Identity_axis = const()[name = tensor("Identity_axis"), val = tensor(1)]; + tensor model_1_model_reshaped_classifier_palm_8_Reshape_shape = const()[name = tensor("model_1_model_reshaped_classifier_palm_8_Reshape_shape"), val = tensor([1, -1, 1])]; + tensor model_1_model_reshaped_classifier_palm_16_Reshape_shape = const()[name = tensor("model_1_model_reshaped_classifier_palm_16_Reshape_shape"), val = tensor([1, -1, 1])]; + tensor Identity_1_axis = const()[name = tensor("Identity_1_axis"), val = tensor(1)]; + tensor transpose_1_perm_0 = const()[name = tensor("transpose_1_perm_0"), val = tensor([0, 3, 1, 2])]; + tensor input_1_to_fp16_dtype_0 = const()[name = tensor("input_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor Conv2Dx_pad_type_0 = const()[name = tensor("Conv2Dx_pad_type_0"), val = tensor("same")]; + tensor Conv2Dx_strides_0 = const()[name = tensor("Conv2Dx_strides_0"), val = tensor([2, 2])]; + tensor Conv2Dx_dilations_0 = const()[name = tensor("Conv2Dx_dilations_0"), val = tensor([1, 1])]; + tensor Conv2Dx_groups_0 = const()[name = tensor("Conv2Dx_groups_0"), val = tensor(1)]; + tensor Conv2Dx_pad_0 = const()[name = tensor("Conv2Dx_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4928)))]; + tensor input_1_to_fp16 = cast(dtype = input_1_to_fp16_dtype_0, x = input_1)[name = tensor("cast_5")]; + tensor transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_1_to_fp16)[name = tensor("transpose_116")]; + tensor model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16 = conv(bias = const_84_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("model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16")]; + tensor model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5056)))]; + tensor model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_Conv2D1_cast_fp16)[name = tensor("model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwisex_pad_type_0 = const()[name = tensor("depthwisex_pad_type_0"), val = tensor("same")]; + tensor depthwisex_strides_0 = const()[name = tensor("depthwisex_strides_0"), val = tensor([1, 1])]; + tensor depthwisex_dilations_0 = const()[name = tensor("depthwisex_dilations_0"), val = tensor([1, 1])]; + tensor depthwisex_groups_0 = const()[name = tensor("depthwisex_groups_0"), val = tensor(32)]; + tensor depthwisex_pad_0 = const()[name = tensor("depthwisex_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5184)))]; + tensor depthwisex_cast_fp16 = conv(dilations = depthwisex_dilations_0, groups = depthwisex_groups_0, pad = depthwisex_pad_0, pad_type = depthwisex_pad_type_0, strides = depthwisex_strides_0, weight = transpose_2_to_fp16, x = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwisex_cast_fp16")]; + tensor Conv2D_1x_pad_type_0 = const()[name = tensor("Conv2D_1x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_1x_strides_0 = const()[name = tensor("Conv2D_1x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_dilations_0 = const()[name = tensor("Conv2D_1x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_1x_groups_0 = const()[name = tensor("Conv2D_1x_groups_0"), val = tensor(1)]; + tensor Conv2D_1x_pad_0 = const()[name = tensor("Conv2D_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_4_to_fp16 = const()[name = tensor("transpose_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6848)))]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8960)))]; + tensor model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16 = conv(bias = const_85_to_fp16, dilations = Conv2D_1x_dilations_0, groups = Conv2D_1x_groups_0, pad = Conv2D_1x_pad_0, pad_type = Conv2D_1x_pad_type_0, strides = Conv2D_1x_strides_0, weight = transpose_4_to_fp16, x = depthwisex_cast_fp16)[name = tensor("model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16")]; + tensor model_1_model_add_add_cast_fp16 = add(x = model_1_model_p_re_lu_add_model_1_model_p_re_lu_Relu_model_1_model_p_re_lu_Neg_1_model_1_model_p_re_lu_Relu_1_model_1_model_p_re_lu_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_1_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_1_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_add_cast_fp16")]; + tensor model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9088)))]; + tensor model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_1x_pad_type_0 = const()[name = tensor("depthwise_1x_pad_type_0"), val = tensor("same")]; + tensor depthwise_1x_strides_0 = const()[name = tensor("depthwise_1x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_1x_dilations_0 = const()[name = tensor("depthwise_1x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_1x_groups_0 = const()[name = tensor("depthwise_1x_groups_0"), val = tensor(32)]; + tensor depthwise_1x_pad_0 = const()[name = tensor("depthwise_1x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_6_to_fp16 = const()[name = tensor("transpose_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9216)))]; + tensor depthwise_1x_cast_fp16 = conv(dilations = depthwise_1x_dilations_0, groups = depthwise_1x_groups_0, pad = depthwise_1x_pad_0, pad_type = depthwise_1x_pad_type_0, strides = depthwise_1x_strides_0, weight = transpose_6_to_fp16, x = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_1x_cast_fp16")]; + tensor Conv2D_2x_pad_type_0 = const()[name = tensor("Conv2D_2x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_2x_strides_0 = const()[name = tensor("Conv2D_2x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_dilations_0 = const()[name = tensor("Conv2D_2x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_2x_groups_0 = const()[name = tensor("Conv2D_2x_groups_0"), val = tensor(1)]; + tensor Conv2D_2x_pad_0 = const()[name = tensor("Conv2D_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_8_to_fp16 = const()[name = tensor("transpose_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10880)))]; + tensor const_86_to_fp16 = const()[name = tensor("const_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12992)))]; + tensor model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16 = conv(bias = const_86_to_fp16, dilations = Conv2D_2x_dilations_0, groups = Conv2D_2x_groups_0, pad = Conv2D_2x_pad_0, pad_type = Conv2D_2x_pad_type_0, strides = Conv2D_2x_strides_0, weight = transpose_8_to_fp16, x = depthwise_1x_cast_fp16)[name = tensor("model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16")]; + tensor model_1_model_add_1_add_cast_fp16 = add(x = model_1_model_p_re_lu_1_add_model_1_model_p_re_lu_1_Relu_model_1_model_p_re_lu_1_Neg_1_model_1_model_p_re_lu_1_Relu_1_model_1_model_p_re_lu_1_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_2_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_2_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_1_add_cast_fp16")]; + tensor model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13120)))]; + tensor model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_1_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_2x_pad_type_0 = const()[name = tensor("depthwise_2x_pad_type_0"), val = tensor("same")]; + tensor depthwise_2x_strides_0 = const()[name = tensor("depthwise_2x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_2x_dilations_0 = const()[name = tensor("depthwise_2x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_2x_groups_0 = const()[name = tensor("depthwise_2x_groups_0"), val = tensor(32)]; + tensor depthwise_2x_pad_0 = const()[name = tensor("depthwise_2x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_10_to_fp16 = const()[name = tensor("transpose_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13248)))]; + tensor 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_10_to_fp16, x = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_2x_cast_fp16")]; + tensor Conv2D_3x_pad_type_0 = const()[name = tensor("Conv2D_3x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_3x_strides_0 = const()[name = tensor("Conv2D_3x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_dilations_0 = const()[name = tensor("Conv2D_3x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_3x_groups_0 = const()[name = tensor("Conv2D_3x_groups_0"), val = tensor(1)]; + tensor Conv2D_3x_pad_0 = const()[name = tensor("Conv2D_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_12_to_fp16 = const()[name = tensor("transpose_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14912)))]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17024)))]; + tensor model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16 = conv(bias = const_87_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_12_to_fp16, x = depthwise_2x_cast_fp16)[name = tensor("model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16")]; + tensor model_1_model_add_2_add_cast_fp16 = add(x = model_1_model_p_re_lu_2_add_model_1_model_p_re_lu_2_Relu_model_1_model_p_re_lu_2_Neg_1_model_1_model_p_re_lu_2_Relu_1_model_1_model_p_re_lu_2_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_3_FusedBatchNormV3_model_1_model_depthwise_conv2d_3_depthwise_model_1_model_conv2d_3_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_2_add_cast_fp16")]; + tensor model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17152)))]; + tensor model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_2_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_0_kernel_sizes_0 = const()[name = tensor("max_pool_0_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_0_strides_0 = const()[name = tensor("max_pool_0_strides_0"), val = tensor([2, 2])]; + tensor max_pool_0_pad_type_0 = const()[name = tensor("max_pool_0_pad_type_0"), val = tensor("same")]; + tensor max_pool_0_pad_0 = const()[name = tensor("max_pool_0_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_0_ceil_mode_0 = const()[name = tensor("max_pool_0_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_0_cast_fp16")]; + tensor depthwise_3x_pad_type_0 = const()[name = tensor("depthwise_3x_pad_type_0"), val = tensor("same")]; + tensor depthwise_3x_strides_0 = const()[name = tensor("depthwise_3x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_3x_dilations_0 = const()[name = tensor("depthwise_3x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_3x_groups_0 = const()[name = tensor("depthwise_3x_groups_0"), val = tensor(32)]; + tensor depthwise_3x_pad_0 = const()[name = tensor("depthwise_3x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_15_to_fp16 = const()[name = tensor("transpose_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17280)))]; + tensor depthwise_3x_cast_fp16 = conv(dilations = depthwise_3x_dilations_0, groups = depthwise_3x_groups_0, pad = depthwise_3x_pad_0, pad_type = depthwise_3x_pad_type_0, strides = depthwise_3x_strides_0, weight = transpose_15_to_fp16, x = model_1_model_p_re_lu_3_add_model_1_model_p_re_lu_3_Relu_model_1_model_p_re_lu_3_Neg_1_model_1_model_p_re_lu_3_Relu_1_model_1_model_p_re_lu_3_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_3x_cast_fp16")]; + tensor pad_0_mode_0 = const()[name = tensor("pad_0_mode_0"), val = tensor("constant")]; + tensor const_42 = const()[name = tensor("const_42"), val = tensor([0, 0, 0, 32, 0, 0, 0, 0])]; + tensor const_4_to_fp16 = const()[name = tensor("const_4_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_0_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = pad_0_mode_0, pad = const_42, x = max_pool_0_cast_fp16)[name = tensor("pad_0_cast_fp16")]; + tensor Conv2D_4x_pad_type_0 = const()[name = tensor("Conv2D_4x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_4x_strides_0 = const()[name = tensor("Conv2D_4x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_dilations_0 = const()[name = tensor("Conv2D_4x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_4x_groups_0 = const()[name = tensor("Conv2D_4x_groups_0"), val = tensor(1)]; + tensor Conv2D_4x_pad_0 = const()[name = tensor("Conv2D_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_17_to_fp16 = const()[name = tensor("transpose_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18944)))]; + tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23104)))]; + tensor model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16 = conv(bias = const_88_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_17_to_fp16, x = depthwise_3x_cast_fp16)[name = tensor("model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16")]; + tensor model_1_model_add_3_add_cast_fp16 = add(x = pad_0_cast_fp16, y = model_1_model_batch_normalization_4_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_4_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_3_add_cast_fp16")]; + tensor model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23296)))]; + tensor model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_3_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_4x_pad_type_0 = const()[name = tensor("depthwise_4x_pad_type_0"), val = tensor("same")]; + tensor depthwise_4x_strides_0 = const()[name = tensor("depthwise_4x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_4x_dilations_0 = const()[name = tensor("depthwise_4x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_4x_groups_0 = const()[name = tensor("depthwise_4x_groups_0"), val = tensor(64)]; + tensor depthwise_4x_pad_0 = const()[name = tensor("depthwise_4x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_19_to_fp16 = const()[name = tensor("transpose_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23488)))]; + tensor depthwise_4x_cast_fp16 = conv(dilations = depthwise_4x_dilations_0, groups = depthwise_4x_groups_0, pad = depthwise_4x_pad_0, pad_type = depthwise_4x_pad_type_0, strides = depthwise_4x_strides_0, weight = transpose_19_to_fp16, x = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_4x_cast_fp16")]; + tensor Conv2D_5x_pad_type_0 = const()[name = tensor("Conv2D_5x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_5x_strides_0 = const()[name = tensor("Conv2D_5x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_dilations_0 = const()[name = tensor("Conv2D_5x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_5x_groups_0 = const()[name = tensor("Conv2D_5x_groups_0"), val = tensor(1)]; + tensor Conv2D_5x_pad_0 = const()[name = tensor("Conv2D_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_21_to_fp16 = const()[name = tensor("transpose_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26752)))]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35008)))]; + tensor model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16 = conv(bias = const_89_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_21_to_fp16, x = depthwise_4x_cast_fp16)[name = tensor("model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16")]; + tensor model_1_model_add_4_add_cast_fp16 = add(x = model_1_model_p_re_lu_4_add_model_1_model_p_re_lu_4_Relu_model_1_model_p_re_lu_4_Neg_1_model_1_model_p_re_lu_4_Relu_1_model_1_model_p_re_lu_4_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_5_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_5_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_4_add_cast_fp16")]; + tensor model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35200)))]; + tensor model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_4_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_5x_pad_type_0 = const()[name = tensor("depthwise_5x_pad_type_0"), val = tensor("same")]; + tensor depthwise_5x_strides_0 = const()[name = tensor("depthwise_5x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_5x_dilations_0 = const()[name = tensor("depthwise_5x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_5x_groups_0 = const()[name = tensor("depthwise_5x_groups_0"), val = tensor(64)]; + tensor depthwise_5x_pad_0 = const()[name = tensor("depthwise_5x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_23_to_fp16 = const()[name = tensor("transpose_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35392)))]; + tensor 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_23_to_fp16, x = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_5x_cast_fp16")]; + tensor Conv2D_6x_pad_type_0 = const()[name = tensor("Conv2D_6x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_6x_strides_0 = const()[name = tensor("Conv2D_6x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_dilations_0 = const()[name = tensor("Conv2D_6x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_6x_groups_0 = const()[name = tensor("Conv2D_6x_groups_0"), val = tensor(1)]; + tensor Conv2D_6x_pad_0 = const()[name = tensor("Conv2D_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_25_to_fp16 = const()[name = tensor("transpose_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38656)))]; + tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46912)))]; + tensor model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16 = conv(bias = const_90_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_25_to_fp16, x = depthwise_5x_cast_fp16)[name = tensor("model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16")]; + tensor model_1_model_add_5_add_cast_fp16 = add(x = model_1_model_p_re_lu_5_add_model_1_model_p_re_lu_5_Relu_model_1_model_p_re_lu_5_Neg_1_model_1_model_p_re_lu_5_Relu_1_model_1_model_p_re_lu_5_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_6_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_6_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_5_add_cast_fp16")]; + tensor model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47104)))]; + tensor model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_5_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_6x_pad_type_0 = const()[name = tensor("depthwise_6x_pad_type_0"), val = tensor("same")]; + tensor depthwise_6x_strides_0 = const()[name = tensor("depthwise_6x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_6x_dilations_0 = const()[name = tensor("depthwise_6x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_6x_groups_0 = const()[name = tensor("depthwise_6x_groups_0"), val = tensor(64)]; + tensor depthwise_6x_pad_0 = const()[name = tensor("depthwise_6x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_27_to_fp16 = const()[name = tensor("transpose_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47296)))]; + tensor 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_27_to_fp16, x = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_6x_cast_fp16")]; + tensor Conv2D_7x_pad_type_0 = const()[name = tensor("Conv2D_7x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_7x_strides_0 = const()[name = tensor("Conv2D_7x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_dilations_0 = const()[name = tensor("Conv2D_7x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_7x_groups_0 = const()[name = tensor("Conv2D_7x_groups_0"), val = tensor(1)]; + tensor Conv2D_7x_pad_0 = const()[name = tensor("Conv2D_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_29_to_fp16 = const()[name = tensor("transpose_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50560)))]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58816)))]; + tensor model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16 = conv(bias = const_91_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_29_to_fp16, x = depthwise_6x_cast_fp16)[name = tensor("model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16")]; + tensor model_1_model_add_6_add_cast_fp16 = add(x = model_1_model_p_re_lu_6_add_model_1_model_p_re_lu_6_Relu_model_1_model_p_re_lu_6_Neg_1_model_1_model_p_re_lu_6_Relu_1_model_1_model_p_re_lu_6_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_7_FusedBatchNormV3_model_1_model_depthwise_conv2d_7_depthwise_model_1_model_conv2d_7_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_6_add_cast_fp16")]; + tensor model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59008)))]; + tensor model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_6_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_1_kernel_sizes_0 = const()[name = tensor("max_pool_1_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_1_strides_0 = const()[name = tensor("max_pool_1_strides_0"), val = tensor([2, 2])]; + tensor max_pool_1_pad_type_0 = const()[name = tensor("max_pool_1_pad_type_0"), val = tensor("same")]; + tensor max_pool_1_pad_0 = const()[name = tensor("max_pool_1_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_1_ceil_mode_0 = const()[name = tensor("max_pool_1_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_1_cast_fp16")]; + tensor depthwise_7x_pad_type_0 = const()[name = tensor("depthwise_7x_pad_type_0"), val = tensor("same")]; + tensor depthwise_7x_strides_0 = const()[name = tensor("depthwise_7x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_7x_dilations_0 = const()[name = tensor("depthwise_7x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_7x_groups_0 = const()[name = tensor("depthwise_7x_groups_0"), val = tensor(64)]; + tensor depthwise_7x_pad_0 = const()[name = tensor("depthwise_7x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_32_to_fp16 = const()[name = tensor("transpose_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59200)))]; + tensor depthwise_7x_cast_fp16 = conv(dilations = depthwise_7x_dilations_0, groups = depthwise_7x_groups_0, pad = depthwise_7x_pad_0, pad_type = depthwise_7x_pad_type_0, strides = depthwise_7x_strides_0, weight = transpose_32_to_fp16, x = model_1_model_p_re_lu_7_add_model_1_model_p_re_lu_7_Relu_model_1_model_p_re_lu_7_Neg_1_model_1_model_p_re_lu_7_Relu_1_model_1_model_p_re_lu_7_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_7x_cast_fp16")]; + tensor pad_1_mode_0 = const()[name = tensor("pad_1_mode_0"), val = tensor("constant")]; + tensor const_46 = const()[name = tensor("const_46"), val = tensor([0, 0, 0, 64, 0, 0, 0, 0])]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_1_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = pad_1_mode_0, pad = const_46, x = max_pool_1_cast_fp16)[name = tensor("pad_1_cast_fp16")]; + tensor Conv2D_8x_pad_type_0 = const()[name = tensor("Conv2D_8x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_8x_strides_0 = const()[name = tensor("Conv2D_8x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_dilations_0 = const()[name = tensor("Conv2D_8x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_8x_groups_0 = const()[name = tensor("Conv2D_8x_groups_0"), val = tensor(1)]; + tensor Conv2D_8x_pad_0 = const()[name = tensor("Conv2D_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_34_to_fp16 = const()[name = tensor("transpose_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62464)))]; + tensor const_92_to_fp16 = const()[name = tensor("const_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78912)))]; + tensor model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_8_Conv2D1_cast_fp16 = conv(bias = const_92_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_34_to_fp16, x = depthwise_7x_cast_fp16)[name = tensor("model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_8_Conv2D1_cast_fp16")]; + tensor model_1_model_add_7_add_cast_fp16 = add(x = pad_1_cast_fp16, y = model_1_model_batch_normalization_8_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_8_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_7_add_cast_fp16")]; + tensor model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79232)))]; + tensor model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_7_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_8x_pad_type_0 = const()[name = tensor("depthwise_8x_pad_type_0"), val = tensor("same")]; + tensor depthwise_8x_strides_0 = const()[name = tensor("depthwise_8x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_8x_dilations_0 = const()[name = tensor("depthwise_8x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_8x_groups_0 = const()[name = tensor("depthwise_8x_groups_0"), val = tensor(128)]; + tensor depthwise_8x_pad_0 = const()[name = tensor("depthwise_8x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_36_to_fp16 = const()[name = tensor("transpose_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79552)))]; + tensor 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_36_to_fp16, x = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_8x_cast_fp16")]; + tensor Conv2D_9x_pad_type_0 = const()[name = tensor("Conv2D_9x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_9x_strides_0 = const()[name = tensor("Conv2D_9x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_dilations_0 = const()[name = tensor("Conv2D_9x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_9x_groups_0 = const()[name = tensor("Conv2D_9x_groups_0"), val = tensor(1)]; + tensor Conv2D_9x_pad_0 = const()[name = tensor("Conv2D_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_38_to_fp16 = const()[name = tensor("transpose_38_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86016)))]; + tensor const_93_to_fp16 = const()[name = tensor("const_93_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118848)))]; + tensor model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_9_Conv2D1_cast_fp16 = conv(bias = const_93_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_38_to_fp16, x = depthwise_8x_cast_fp16)[name = tensor("model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_9_Conv2D1_cast_fp16")]; + tensor model_1_model_add_8_add_cast_fp16 = add(x = model_1_model_p_re_lu_8_add_model_1_model_p_re_lu_8_Relu_model_1_model_p_re_lu_8_Neg_1_model_1_model_p_re_lu_8_Relu_1_model_1_model_p_re_lu_8_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_9_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_9_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_8_add_cast_fp16")]; + tensor model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119168)))]; + tensor model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_8_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_9x_pad_type_0 = const()[name = tensor("depthwise_9x_pad_type_0"), val = tensor("same")]; + tensor depthwise_9x_strides_0 = const()[name = tensor("depthwise_9x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_9x_dilations_0 = const()[name = tensor("depthwise_9x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_9x_groups_0 = const()[name = tensor("depthwise_9x_groups_0"), val = tensor(128)]; + tensor depthwise_9x_pad_0 = const()[name = tensor("depthwise_9x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_40_to_fp16 = const()[name = tensor("transpose_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119488)))]; + tensor 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_40_to_fp16, x = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_9x_cast_fp16")]; + tensor Conv2D_10x_pad_type_0 = const()[name = tensor("Conv2D_10x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_10x_strides_0 = const()[name = tensor("Conv2D_10x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_dilations_0 = const()[name = tensor("Conv2D_10x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_10x_groups_0 = const()[name = tensor("Conv2D_10x_groups_0"), val = tensor(1)]; + tensor Conv2D_10x_pad_0 = const()[name = tensor("Conv2D_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_42_to_fp16 = const()[name = tensor("transpose_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125952)))]; + tensor const_94_to_fp16 = const()[name = tensor("const_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158784)))]; + tensor model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16 = conv(bias = const_94_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_42_to_fp16, x = depthwise_9x_cast_fp16)[name = tensor("model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16")]; + tensor model_1_model_add_9_add_cast_fp16 = add(x = model_1_model_p_re_lu_9_add_model_1_model_p_re_lu_9_Relu_model_1_model_p_re_lu_9_Neg_1_model_1_model_p_re_lu_9_Relu_1_model_1_model_p_re_lu_9_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_10_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_10_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_9_add_cast_fp16")]; + tensor model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159104)))]; + tensor model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_9_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_10x_pad_type_0 = const()[name = tensor("depthwise_10x_pad_type_0"), val = tensor("same")]; + tensor depthwise_10x_strides_0 = const()[name = tensor("depthwise_10x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_10x_dilations_0 = const()[name = tensor("depthwise_10x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_10x_groups_0 = const()[name = tensor("depthwise_10x_groups_0"), val = tensor(128)]; + tensor depthwise_10x_pad_0 = const()[name = tensor("depthwise_10x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_44_to_fp16 = const()[name = tensor("transpose_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159424)))]; + tensor 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_44_to_fp16, x = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_10x_cast_fp16")]; + tensor Conv2D_11x_pad_type_0 = const()[name = tensor("Conv2D_11x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_11x_strides_0 = const()[name = tensor("Conv2D_11x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_dilations_0 = const()[name = tensor("Conv2D_11x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_11x_groups_0 = const()[name = tensor("Conv2D_11x_groups_0"), val = tensor(1)]; + tensor Conv2D_11x_pad_0 = const()[name = tensor("Conv2D_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_46_to_fp16 = const()[name = tensor("transpose_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165888)))]; + tensor const_95_to_fp16 = const()[name = tensor("const_95_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198720)))]; + tensor model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16 = conv(bias = const_95_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_46_to_fp16, x = depthwise_10x_cast_fp16)[name = tensor("model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16")]; + tensor model_1_model_add_10_add_cast_fp16 = add(x = model_1_model_p_re_lu_10_add_model_1_model_p_re_lu_10_Relu_model_1_model_p_re_lu_10_Neg_1_model_1_model_p_re_lu_10_Relu_1_model_1_model_p_re_lu_10_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_11_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_11_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_10_add_cast_fp16")]; + tensor model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199040)))]; + tensor model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_10_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_2_kernel_sizes_0 = const()[name = tensor("max_pool_2_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_2_strides_0 = const()[name = tensor("max_pool_2_strides_0"), val = tensor([2, 2])]; + tensor max_pool_2_pad_type_0 = const()[name = tensor("max_pool_2_pad_type_0"), val = tensor("same")]; + tensor max_pool_2_pad_0 = const()[name = tensor("max_pool_2_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_2_ceil_mode_0 = const()[name = tensor("max_pool_2_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_2_cast_fp16")]; + tensor depthwise_11x_pad_type_0 = const()[name = tensor("depthwise_11x_pad_type_0"), val = tensor("same")]; + tensor depthwise_11x_strides_0 = const()[name = tensor("depthwise_11x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_11x_dilations_0 = const()[name = tensor("depthwise_11x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_11x_groups_0 = const()[name = tensor("depthwise_11x_groups_0"), val = tensor(128)]; + tensor depthwise_11x_pad_0 = const()[name = tensor("depthwise_11x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_49_to_fp16 = const()[name = tensor("transpose_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199360)))]; + tensor 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_49_to_fp16, x = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_11x_cast_fp16")]; + tensor pad_2_mode_0 = const()[name = tensor("pad_2_mode_0"), val = tensor("constant")]; + tensor const_64 = const()[name = tensor("const_64"), val = tensor([0, 0, 0, 128, 0, 0, 0, 0])]; + tensor const_14_to_fp16 = const()[name = tensor("const_14_to_fp16"), val = tensor(0x0p+0)]; + tensor pad_2_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = pad_2_mode_0, pad = const_64, x = max_pool_2_cast_fp16)[name = tensor("pad_2_cast_fp16")]; + tensor Conv2D_12x_pad_type_0 = const()[name = tensor("Conv2D_12x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_12x_strides_0 = const()[name = tensor("Conv2D_12x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_dilations_0 = const()[name = tensor("Conv2D_12x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_12x_groups_0 = const()[name = tensor("Conv2D_12x_groups_0"), val = tensor(1)]; + tensor Conv2D_12x_pad_0 = const()[name = tensor("Conv2D_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_51_to_fp16 = const()[name = tensor("transpose_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205824)))]; + tensor const_96_to_fp16 = const()[name = tensor("const_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271424)))]; + tensor model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16 = conv(bias = const_96_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_51_to_fp16, x = depthwise_11x_cast_fp16)[name = tensor("model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16")]; + tensor model_1_model_add_11_add_cast_fp16 = add(x = pad_2_cast_fp16, y = model_1_model_batch_normalization_12_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_12_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_11_add_cast_fp16")]; + tensor model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272000)))]; + tensor model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_11_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_12x_pad_type_0 = const()[name = tensor("depthwise_12x_pad_type_0"), val = tensor("same")]; + tensor depthwise_12x_strides_0 = const()[name = tensor("depthwise_12x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_12x_dilations_0 = const()[name = tensor("depthwise_12x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_12x_groups_0 = const()[name = tensor("depthwise_12x_groups_0"), val = tensor(256)]; + tensor depthwise_12x_pad_0 = const()[name = tensor("depthwise_12x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_53_to_fp16 = const()[name = tensor("transpose_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272576)))]; + tensor 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_53_to_fp16, x = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_12x_cast_fp16")]; + tensor Conv2D_13x_pad_type_0 = const()[name = tensor("Conv2D_13x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_13x_strides_0 = const()[name = tensor("Conv2D_13x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_dilations_0 = const()[name = tensor("Conv2D_13x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_13x_groups_0 = const()[name = tensor("Conv2D_13x_groups_0"), val = tensor(1)]; + tensor Conv2D_13x_pad_0 = const()[name = tensor("Conv2D_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_55_to_fp16 = const()[name = tensor("transpose_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(285440)))]; + tensor const_97_to_fp16 = const()[name = tensor("const_97_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(416576)))]; + tensor model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16 = conv(bias = const_97_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_55_to_fp16, x = depthwise_12x_cast_fp16)[name = tensor("model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16")]; + tensor model_1_model_add_12_add_cast_fp16 = add(x = model_1_model_p_re_lu_12_add_model_1_model_p_re_lu_12_Relu_model_1_model_p_re_lu_12_Neg_1_model_1_model_p_re_lu_12_Relu_1_model_1_model_p_re_lu_12_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_13_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_13_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_12_add_cast_fp16")]; + tensor model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417152)))]; + tensor model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_12_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_13x_pad_type_0 = const()[name = tensor("depthwise_13x_pad_type_0"), val = tensor("same")]; + tensor depthwise_13x_strides_0 = const()[name = tensor("depthwise_13x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_13x_dilations_0 = const()[name = tensor("depthwise_13x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_13x_groups_0 = const()[name = tensor("depthwise_13x_groups_0"), val = tensor(256)]; + tensor depthwise_13x_pad_0 = const()[name = tensor("depthwise_13x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_57_to_fp16 = const()[name = tensor("transpose_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417728)))]; + tensor 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_57_to_fp16, x = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_13x_cast_fp16")]; + tensor Conv2D_14x_pad_type_0 = const()[name = tensor("Conv2D_14x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_14x_strides_0 = const()[name = tensor("Conv2D_14x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_dilations_0 = const()[name = tensor("Conv2D_14x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_14x_groups_0 = const()[name = tensor("Conv2D_14x_groups_0"), val = tensor(1)]; + tensor Conv2D_14x_pad_0 = const()[name = tensor("Conv2D_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_59_to_fp16 = const()[name = tensor("transpose_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(430592)))]; + tensor const_98_to_fp16 = const()[name = tensor("const_98_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(561728)))]; + tensor model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16 = conv(bias = const_98_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_59_to_fp16, x = depthwise_13x_cast_fp16)[name = tensor("model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16")]; + tensor model_1_model_add_13_add_cast_fp16 = add(x = model_1_model_p_re_lu_13_add_model_1_model_p_re_lu_13_Relu_model_1_model_p_re_lu_13_Neg_1_model_1_model_p_re_lu_13_Relu_1_model_1_model_p_re_lu_13_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_14_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_14_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_13_add_cast_fp16")]; + tensor model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(562304)))]; + tensor model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_13_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_14x_pad_type_0 = const()[name = tensor("depthwise_14x_pad_type_0"), val = tensor("same")]; + tensor depthwise_14x_strides_0 = const()[name = tensor("depthwise_14x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_14x_dilations_0 = const()[name = tensor("depthwise_14x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_14x_groups_0 = const()[name = tensor("depthwise_14x_groups_0"), val = tensor(256)]; + tensor depthwise_14x_pad_0 = const()[name = tensor("depthwise_14x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_61_to_fp16 = const()[name = tensor("transpose_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(562880)))]; + tensor 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_61_to_fp16, x = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_14x_cast_fp16")]; + tensor Conv2D_15x_pad_type_0 = const()[name = tensor("Conv2D_15x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_15x_strides_0 = const()[name = tensor("Conv2D_15x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_dilations_0 = const()[name = tensor("Conv2D_15x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_15x_groups_0 = const()[name = tensor("Conv2D_15x_groups_0"), val = tensor(1)]; + tensor Conv2D_15x_pad_0 = const()[name = tensor("Conv2D_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_63_to_fp16 = const()[name = tensor("transpose_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(575744)))]; + tensor const_99_to_fp16 = const()[name = tensor("const_99_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(706880)))]; + tensor model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16 = conv(bias = const_99_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_63_to_fp16, x = depthwise_14x_cast_fp16)[name = tensor("model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16")]; + tensor model_1_model_add_14_add_cast_fp16 = add(x = model_1_model_p_re_lu_14_add_model_1_model_p_re_lu_14_Relu_model_1_model_p_re_lu_14_Neg_1_model_1_model_p_re_lu_14_Relu_1_model_1_model_p_re_lu_14_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_15_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_15_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_14_add_cast_fp16")]; + tensor model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(707456)))]; + tensor model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_14_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor max_pool_3_kernel_sizes_0 = const()[name = tensor("max_pool_3_kernel_sizes_0"), val = tensor([2, 2])]; + tensor max_pool_3_strides_0 = const()[name = tensor("max_pool_3_strides_0"), val = tensor([2, 2])]; + tensor max_pool_3_pad_type_0 = const()[name = tensor("max_pool_3_pad_type_0"), val = tensor("same")]; + tensor max_pool_3_pad_0 = const()[name = tensor("max_pool_3_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor max_pool_3_ceil_mode_0 = const()[name = tensor("max_pool_3_ceil_mode_0"), val = tensor(false)]; + tensor 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 = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("max_pool_3_cast_fp16")]; + tensor depthwise_15x_pad_type_0 = const()[name = tensor("depthwise_15x_pad_type_0"), val = tensor("same")]; + tensor depthwise_15x_strides_0 = const()[name = tensor("depthwise_15x_strides_0"), val = tensor([2, 2])]; + tensor depthwise_15x_dilations_0 = const()[name = tensor("depthwise_15x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_15x_groups_0 = const()[name = tensor("depthwise_15x_groups_0"), val = tensor(256)]; + tensor depthwise_15x_pad_0 = const()[name = tensor("depthwise_15x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_66_to_fp16 = const()[name = tensor("transpose_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(708032)))]; + tensor 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_66_to_fp16, x = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_15x_cast_fp16")]; + tensor Conv2D_16x_pad_type_0 = const()[name = tensor("Conv2D_16x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_16x_strides_0 = const()[name = tensor("Conv2D_16x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_dilations_0 = const()[name = tensor("Conv2D_16x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_16x_groups_0 = const()[name = tensor("Conv2D_16x_groups_0"), val = tensor(1)]; + tensor Conv2D_16x_pad_0 = const()[name = tensor("Conv2D_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_68_to_fp16 = const()[name = tensor("transpose_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(720896)))]; + tensor const_100_to_fp16 = const()[name = tensor("const_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(852032)))]; + tensor model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16 = conv(bias = const_100_to_fp16, dilations = Conv2D_16x_dilations_0, groups = Conv2D_16x_groups_0, pad = Conv2D_16x_pad_0, pad_type = Conv2D_16x_pad_type_0, strides = Conv2D_16x_strides_0, weight = transpose_68_to_fp16, x = depthwise_15x_cast_fp16)[name = tensor("model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16")]; + tensor model_1_model_add_15_add_cast_fp16 = add(x = max_pool_3_cast_fp16, y = model_1_model_batch_normalization_16_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_16_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_15_add_cast_fp16")]; + tensor model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(852608)))]; + tensor model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_15_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_16x_pad_type_0 = const()[name = tensor("depthwise_16x_pad_type_0"), val = tensor("same")]; + tensor depthwise_16x_strides_0 = const()[name = tensor("depthwise_16x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_16x_dilations_0 = const()[name = tensor("depthwise_16x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_16x_groups_0 = const()[name = tensor("depthwise_16x_groups_0"), val = tensor(256)]; + tensor depthwise_16x_pad_0 = const()[name = tensor("depthwise_16x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_70_to_fp16 = const()[name = tensor("transpose_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(853184)))]; + tensor 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_70_to_fp16, x = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_16x_cast_fp16")]; + tensor Conv2D_17x_pad_type_0 = const()[name = tensor("Conv2D_17x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_17x_strides_0 = const()[name = tensor("Conv2D_17x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_dilations_0 = const()[name = tensor("Conv2D_17x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_17x_groups_0 = const()[name = tensor("Conv2D_17x_groups_0"), val = tensor(1)]; + tensor Conv2D_17x_pad_0 = const()[name = tensor("Conv2D_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_72_to_fp16 = const()[name = tensor("transpose_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(866048)))]; + tensor const_101_to_fp16 = const()[name = tensor("const_101_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(997184)))]; + tensor model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16 = conv(bias = const_101_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_72_to_fp16, x = depthwise_16x_cast_fp16)[name = tensor("model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16")]; + tensor model_1_model_add_16_add_cast_fp16 = add(x = model_1_model_p_re_lu_16_add_model_1_model_p_re_lu_16_Relu_model_1_model_p_re_lu_16_Neg_1_model_1_model_p_re_lu_16_Relu_1_model_1_model_p_re_lu_16_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_17_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_17_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_16_add_cast_fp16")]; + tensor model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(997760)))]; + tensor model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_16_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_17x_pad_type_0 = const()[name = tensor("depthwise_17x_pad_type_0"), val = tensor("same")]; + tensor depthwise_17x_strides_0 = const()[name = tensor("depthwise_17x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_17x_dilations_0 = const()[name = tensor("depthwise_17x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_17x_groups_0 = const()[name = tensor("depthwise_17x_groups_0"), val = tensor(256)]; + tensor depthwise_17x_pad_0 = const()[name = tensor("depthwise_17x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_74_to_fp16 = const()[name = tensor("transpose_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(998336)))]; + tensor 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_74_to_fp16, x = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_17x_cast_fp16")]; + tensor Conv2D_18x_pad_type_0 = const()[name = tensor("Conv2D_18x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_18x_strides_0 = const()[name = tensor("Conv2D_18x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_dilations_0 = const()[name = tensor("Conv2D_18x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_18x_groups_0 = const()[name = tensor("Conv2D_18x_groups_0"), val = tensor(1)]; + tensor Conv2D_18x_pad_0 = const()[name = tensor("Conv2D_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_76_to_fp16 = const()[name = tensor("transpose_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1011200)))]; + tensor const_102_to_fp16 = const()[name = tensor("const_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1142336)))]; + tensor model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16 = conv(bias = const_102_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_76_to_fp16, x = depthwise_17x_cast_fp16)[name = tensor("model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16")]; + tensor model_1_model_add_17_add_cast_fp16 = add(x = model_1_model_p_re_lu_17_add_model_1_model_p_re_lu_17_Relu_model_1_model_p_re_lu_17_Neg_1_model_1_model_p_re_lu_17_Relu_1_model_1_model_p_re_lu_17_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_18_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_18_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_17_add_cast_fp16")]; + tensor model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1142912)))]; + tensor model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_17_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_18x_pad_type_0 = const()[name = tensor("depthwise_18x_pad_type_0"), val = tensor("same")]; + tensor depthwise_18x_strides_0 = const()[name = tensor("depthwise_18x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_18x_dilations_0 = const()[name = tensor("depthwise_18x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_18x_groups_0 = const()[name = tensor("depthwise_18x_groups_0"), val = tensor(256)]; + tensor depthwise_18x_pad_0 = const()[name = tensor("depthwise_18x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_78_to_fp16 = const()[name = tensor("transpose_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1143488)))]; + tensor depthwise_18x_cast_fp16 = conv(dilations = depthwise_18x_dilations_0, groups = depthwise_18x_groups_0, pad = depthwise_18x_pad_0, pad_type = depthwise_18x_pad_type_0, strides = depthwise_18x_strides_0, weight = transpose_78_to_fp16, x = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_18x_cast_fp16")]; + tensor Conv2D_19x_pad_type_0 = const()[name = tensor("Conv2D_19x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_19x_strides_0 = const()[name = tensor("Conv2D_19x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_dilations_0 = const()[name = tensor("Conv2D_19x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_19x_groups_0 = const()[name = tensor("Conv2D_19x_groups_0"), val = tensor(1)]; + tensor Conv2D_19x_pad_0 = const()[name = tensor("Conv2D_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_80_to_fp16 = const()[name = tensor("transpose_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1156352)))]; + tensor const_103_to_fp16 = const()[name = tensor("const_103_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1287488)))]; + tensor model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16 = conv(bias = const_103_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_80_to_fp16, x = depthwise_18x_cast_fp16)[name = tensor("model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16")]; + tensor model_1_model_add_18_add_cast_fp16 = add(x = model_1_model_p_re_lu_18_add_model_1_model_p_re_lu_18_Relu_model_1_model_p_re_lu_18_Neg_1_model_1_model_p_re_lu_18_Relu_1_model_1_model_p_re_lu_18_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_19_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_19_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_18_add_cast_fp16")]; + tensor model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1288064)))]; + tensor model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_18_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0"), val = tensor(12)]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0"), val = tensor(12)]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0 = const()[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0"), val = tensor("STRICT_ALIGN_CORNERS")]; + tensor model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16 = resize_bilinear(sampling_mode = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0, target_size_height = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0, target_size_width = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0, x = model_1_model_p_re_lu_19_add_model_1_model_p_re_lu_19_Relu_model_1_model_p_re_lu_19_Neg_1_model_1_model_p_re_lu_19_Relu_1_model_1_model_p_re_lu_19_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16")]; + tensor Conv2D_20x_pad_type_0 = const()[name = tensor("Conv2D_20x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_20x_strides_0 = const()[name = tensor("Conv2D_20x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_dilations_0 = const()[name = tensor("Conv2D_20x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_20x_groups_0 = const()[name = tensor("Conv2D_20x_groups_0"), val = tensor(1)]; + tensor Conv2D_20x_pad_0 = const()[name = tensor("Conv2D_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_83_to_fp16 = const()[name = tensor("transpose_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1288640)))]; + tensor const_104_to_fp16 = const()[name = tensor("const_104_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1419776)))]; + tensor model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_20_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_20_BiasAdd_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_20_Conv2D_cast_fp16 = conv(bias = const_104_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_83_to_fp16, x = model_1_model_up_sampling2d_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16)[name = tensor("model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_20_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_20_BiasAdd_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_20_Conv2D_cast_fp16")]; + tensor model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1420352)))]; + tensor model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_20_FusedBatchNormV3_model_1_model_conv2d_20_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_20_BiasAdd_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_20_Conv2D_cast_fp16)[name = tensor("model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_add_19_add_cast_fp16 = add(x = model_1_model_p_re_lu_15_add_model_1_model_p_re_lu_15_Relu_model_1_model_p_re_lu_15_Neg_1_model_1_model_p_re_lu_15_Relu_1_model_1_model_p_re_lu_15_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_p_re_lu_20_add_model_1_model_p_re_lu_20_Relu_model_1_model_p_re_lu_20_Neg_1_model_1_model_p_re_lu_20_Relu_1_model_1_model_p_re_lu_20_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_add_19_add_cast_fp16")]; + tensor depthwise_19x_pad_type_0 = const()[name = tensor("depthwise_19x_pad_type_0"), val = tensor("same")]; + tensor depthwise_19x_strides_0 = const()[name = tensor("depthwise_19x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_19x_dilations_0 = const()[name = tensor("depthwise_19x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_19x_groups_0 = const()[name = tensor("depthwise_19x_groups_0"), val = tensor(256)]; + tensor depthwise_19x_pad_0 = const()[name = tensor("depthwise_19x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_85_to_fp16 = const()[name = tensor("transpose_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1420928)))]; + tensor 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_85_to_fp16, x = model_1_model_add_19_add_cast_fp16)[name = tensor("depthwise_19x_cast_fp16")]; + tensor Conv2D_21x_pad_type_0 = const()[name = tensor("Conv2D_21x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_21x_strides_0 = const()[name = tensor("Conv2D_21x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_dilations_0 = const()[name = tensor("Conv2D_21x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_21x_groups_0 = const()[name = tensor("Conv2D_21x_groups_0"), val = tensor(1)]; + tensor Conv2D_21x_pad_0 = const()[name = tensor("Conv2D_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_87_to_fp16 = const()[name = tensor("transpose_87_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1433792)))]; + tensor const_105_to_fp16 = const()[name = tensor("const_105_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1564928)))]; + tensor model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16 = conv(bias = const_105_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_87_to_fp16, x = depthwise_19x_cast_fp16)[name = tensor("model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16")]; + tensor model_1_model_add_20_add_cast_fp16 = add(x = model_1_model_add_19_add_cast_fp16, y = model_1_model_batch_normalization_21_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D_model_1_model_conv2d_21_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_20_add_cast_fp16")]; + tensor model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1565504)))]; + tensor model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_20_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_20x_pad_type_0 = const()[name = tensor("depthwise_20x_pad_type_0"), val = tensor("same")]; + tensor depthwise_20x_strides_0 = const()[name = tensor("depthwise_20x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_20x_dilations_0 = const()[name = tensor("depthwise_20x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_20x_groups_0 = const()[name = tensor("depthwise_20x_groups_0"), val = tensor(256)]; + tensor depthwise_20x_pad_0 = const()[name = tensor("depthwise_20x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_89_to_fp16 = const()[name = tensor("transpose_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1566080)))]; + tensor 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_89_to_fp16, x = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_20x_cast_fp16")]; + tensor Conv2D_22x_pad_type_0 = const()[name = tensor("Conv2D_22x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_22x_strides_0 = const()[name = tensor("Conv2D_22x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_dilations_0 = const()[name = tensor("Conv2D_22x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_22x_groups_0 = const()[name = tensor("Conv2D_22x_groups_0"), val = tensor(1)]; + tensor Conv2D_22x_pad_0 = const()[name = tensor("Conv2D_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_91_to_fp16 = const()[name = tensor("transpose_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1578944)))]; + tensor const_106_to_fp16 = const()[name = tensor("const_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1710080)))]; + tensor model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D1_cast_fp16 = conv(bias = const_106_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_91_to_fp16, x = depthwise_20x_cast_fp16)[name = tensor("model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D1_cast_fp16")]; + tensor model_1_model_add_21_add_cast_fp16 = add(x = model_1_model_p_re_lu_21_add_model_1_model_p_re_lu_21_Relu_model_1_model_p_re_lu_21_Neg_1_model_1_model_p_re_lu_21_Relu_1_model_1_model_p_re_lu_21_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_22_FusedBatchNormV3_model_1_model_conv2d_22_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_21_add_cast_fp16")]; + tensor model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1710656)))]; + tensor model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_21_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0"), val = tensor(24)]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0"), val = tensor(24)]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0 = const()[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0"), val = tensor("STRICT_ALIGN_CORNERS")]; + tensor model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16 = resize_bilinear(sampling_mode = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_sampling_mode_0, target_size_height = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_height_0, target_size_width = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_target_size_width_0, x = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16")]; + tensor Conv2D_24x_pad_type_0 = const()[name = tensor("Conv2D_24x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_24x_strides_0 = const()[name = tensor("Conv2D_24x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_dilations_0 = const()[name = tensor("Conv2D_24x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_24x_groups_0 = const()[name = tensor("Conv2D_24x_groups_0"), val = tensor(1)]; + tensor Conv2D_24x_pad_0 = const()[name = tensor("Conv2D_24x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_0_weight_0_to_fp16 = const()[name = tensor("conv_0_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1711232)))]; + tensor conv_0_bias_0_to_fp16 = const()[name = tensor("conv_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1766592)))]; + tensor conv_0_cast_fp16 = conv(bias = conv_0_bias_0_to_fp16, dilations = Conv2D_24x_dilations_0, groups = Conv2D_24x_groups_0, pad = Conv2D_24x_pad_0, pad_type = Conv2D_24x_pad_type_0, strides = Conv2D_24x_strides_0, weight = conv_0_weight_0_to_fp16, x = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_0_cast_fp16")]; + tensor Conv2D_24_perm_0 = const()[name = tensor("Conv2D_24_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_23x_pad_type_0 = const()[name = tensor("Conv2D_23x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_23x_strides_0 = const()[name = tensor("Conv2D_23x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_dilations_0 = const()[name = tensor("Conv2D_23x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_23x_groups_0 = const()[name = tensor("Conv2D_23x_groups_0"), val = tensor(1)]; + tensor Conv2D_23x_pad_0 = const()[name = tensor("Conv2D_23x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_1_weight_0_to_fp16 = const()[name = tensor("conv_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1766912)))]; + tensor conv_1_bias_0_to_fp16 = const()[name = tensor("conv_1_bias_0_to_fp16"), val = tensor([0x1.098p-3, -0x1.d44p-7, -0x1.5f4p-4, -0x1.6d8p-3, -0x1.984p-2, -0x1.3bp-1])]; + tensor conv_1_cast_fp16 = conv(bias = conv_1_bias_0_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 = conv_1_weight_0_to_fp16, x = model_1_model_p_re_lu_22_add_model_1_model_p_re_lu_22_Relu_model_1_model_p_re_lu_22_Neg_1_model_1_model_p_re_lu_22_Relu_1_model_1_model_p_re_lu_22_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_1_cast_fp16")]; + tensor Conv2D_23_perm_0 = const()[name = tensor("Conv2D_23_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_25x_pad_type_0 = const()[name = tensor("Conv2D_25x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_25x_strides_0 = const()[name = tensor("Conv2D_25x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_dilations_0 = const()[name = tensor("Conv2D_25x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_25x_groups_0 = const()[name = tensor("Conv2D_25x_groups_0"), val = tensor(1)]; + tensor Conv2D_25x_pad_0 = const()[name = tensor("Conv2D_25x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_98_to_fp16 = const()[name = tensor("transpose_98_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1770048)))]; + tensor const_107_to_fp16 = const()[name = tensor("const_107_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1835648)))]; + tensor model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_23_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_23_BiasAdd_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_23_Conv2D_cast_fp16 = conv(bias = const_107_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_98_to_fp16, x = model_1_model_up_sampling2d_1_resize_ResizeBilinear_lambda_1_ResizeBilinear_channel_first_resize_bilinear_cast_fp16)[name = tensor("model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_23_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_23_BiasAdd_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_23_Conv2D_cast_fp16")]; + tensor model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_16_NO_PRUNING_Conv2D_model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_24_perm_0, x = conv_0_cast_fp16)[name = tensor("transpose_115")]; + tensor model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_regressor_palm_16_Reshape_shape, x = model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_16_NO_PRUNING_Conv2D_model_1_model_regressor_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16")]; + tensor model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_16_NO_PRUNING_Conv2D_model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_23_perm_0, x = conv_1_cast_fp16)[name = tensor("transpose_114")]; + tensor model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_classifier_palm_16_Reshape_shape, x = model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_16_NO_PRUNING_Conv2D_model_1_model_classifier_palm_16_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16")]; + tensor model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1835968)))]; + tensor model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_batch_normalization_23_FusedBatchNormV3_model_1_model_conv2d_23_BiasAdd_ReadVariableOp_resource_model_1_model_conv2d_23_BiasAdd_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_23_Conv2D_cast_fp16)[name = tensor("model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor model_1_model_add_22_add_cast_fp16 = add(x = model_1_model_p_re_lu_11_add_model_1_model_p_re_lu_11_Relu_model_1_model_p_re_lu_11_Neg_1_model_1_model_p_re_lu_11_Relu_1_model_1_model_p_re_lu_11_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_p_re_lu_23_add_model_1_model_p_re_lu_23_Relu_model_1_model_p_re_lu_23_Neg_1_model_1_model_p_re_lu_23_Relu_1_model_1_model_p_re_lu_23_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("model_1_model_add_22_add_cast_fp16")]; + tensor depthwise_21x_pad_type_0 = const()[name = tensor("depthwise_21x_pad_type_0"), val = tensor("same")]; + tensor depthwise_21x_strides_0 = const()[name = tensor("depthwise_21x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_21x_dilations_0 = const()[name = tensor("depthwise_21x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_21x_groups_0 = const()[name = tensor("depthwise_21x_groups_0"), val = tensor(128)]; + tensor depthwise_21x_pad_0 = const()[name = tensor("depthwise_21x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_100_to_fp16 = const()[name = tensor("transpose_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1836288)))]; + tensor 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_100_to_fp16, x = model_1_model_add_22_add_cast_fp16)[name = tensor("depthwise_21x_cast_fp16")]; + tensor Conv2D_26x_pad_type_0 = const()[name = tensor("Conv2D_26x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_26x_strides_0 = const()[name = tensor("Conv2D_26x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_dilations_0 = const()[name = tensor("Conv2D_26x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_26x_groups_0 = const()[name = tensor("Conv2D_26x_groups_0"), val = tensor(1)]; + tensor Conv2D_26x_pad_0 = const()[name = tensor("Conv2D_26x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_102_to_fp16 = const()[name = tensor("transpose_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1842752)))]; + tensor const_108_to_fp16 = const()[name = tensor("const_108_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1875584)))]; + tensor model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16 = conv(bias = const_108_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_102_to_fp16, x = depthwise_21x_cast_fp16)[name = tensor("model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16")]; + tensor model_1_model_add_23_add_cast_fp16 = add(x = model_1_model_add_22_add_cast_fp16, y = model_1_model_batch_normalization_24_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D_model_1_model_conv2d_24_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_23_add_cast_fp16")]; + tensor model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1875904)))]; + tensor model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_23_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor depthwise_22x_pad_type_0 = const()[name = tensor("depthwise_22x_pad_type_0"), val = tensor("same")]; + tensor depthwise_22x_strides_0 = const()[name = tensor("depthwise_22x_strides_0"), val = tensor([1, 1])]; + tensor depthwise_22x_dilations_0 = const()[name = tensor("depthwise_22x_dilations_0"), val = tensor([1, 1])]; + tensor depthwise_22x_groups_0 = const()[name = tensor("depthwise_22x_groups_0"), val = tensor(128)]; + tensor depthwise_22x_pad_0 = const()[name = tensor("depthwise_22x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_104_to_fp16 = const()[name = tensor("transpose_104_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1876224)))]; + tensor 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_104_to_fp16, x = model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("depthwise_22x_cast_fp16")]; + tensor Conv2D_27x_pad_type_0 = const()[name = tensor("Conv2D_27x_pad_type_0"), val = tensor("valid")]; + tensor Conv2D_27x_strides_0 = const()[name = tensor("Conv2D_27x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_dilations_0 = const()[name = tensor("Conv2D_27x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_27x_groups_0 = const()[name = tensor("Conv2D_27x_groups_0"), val = tensor(1)]; + tensor Conv2D_27x_pad_0 = const()[name = tensor("Conv2D_27x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor transpose_106_to_fp16 = const()[name = tensor("transpose_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1882688)))]; + tensor const_109_to_fp16 = const()[name = tensor("const_109_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1915520)))]; + tensor model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D1_cast_fp16 = conv(bias = const_109_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_106_to_fp16, x = depthwise_22x_cast_fp16)[name = tensor("model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D1_cast_fp16")]; + tensor model_1_model_add_24_add_cast_fp16 = add(x = model_1_model_p_re_lu_24_add_model_1_model_p_re_lu_24_Relu_model_1_model_p_re_lu_24_Neg_1_model_1_model_p_re_lu_24_Relu_1_model_1_model_p_re_lu_24_mul_dequantize_prelu_1_add_cast_fp16, y = model_1_model_batch_normalization_25_FusedBatchNormV3_model_1_model_conv2d_25_Conv2D1_cast_fp16)[name = tensor("model_1_model_add_24_add_cast_fp16")]; + tensor model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16 = const()[name = tensor("model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1915840)))]; + tensor model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16 = prelu(alpha = model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_alpha_0_to_fp16, x = model_1_model_add_24_add_cast_fp16)[name = tensor("model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16")]; + tensor Conv2D_29x_pad_type_0 = const()[name = tensor("Conv2D_29x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_29x_strides_0 = const()[name = tensor("Conv2D_29x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_dilations_0 = const()[name = tensor("Conv2D_29x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_29x_groups_0 = const()[name = tensor("Conv2D_29x_groups_0"), val = tensor(1)]; + tensor Conv2D_29x_pad_0 = const()[name = tensor("Conv2D_29x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_2_weight_0_to_fp16 = const()[name = tensor("conv_2_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1916160)))]; + tensor conv_2_bias_0_to_fp16 = const()[name = tensor("conv_2_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1925440)))]; + tensor conv_2_cast_fp16 = conv(bias = conv_2_bias_0_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 = conv_2_weight_0_to_fp16, x = model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_2_cast_fp16")]; + tensor Conv2D_29_perm_0 = const()[name = tensor("Conv2D_29_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor Conv2D_28x_pad_type_0 = const()[name = tensor("Conv2D_28x_pad_type_0"), val = tensor("same")]; + tensor Conv2D_28x_strides_0 = const()[name = tensor("Conv2D_28x_strides_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_dilations_0 = const()[name = tensor("Conv2D_28x_dilations_0"), val = tensor([1, 1])]; + tensor Conv2D_28x_groups_0 = const()[name = tensor("Conv2D_28x_groups_0"), val = tensor(1)]; + tensor Conv2D_28x_pad_0 = const()[name = tensor("Conv2D_28x_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor conv_3_weight_0_to_fp16 = const()[name = tensor("conv_3_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1925632)))]; + tensor conv_3_bias_0_to_fp16 = const()[name = tensor("conv_3_bias_0_to_fp16"), val = tensor([0x1.f54p-4, -0x1.18cp-1])]; + tensor conv_3_cast_fp16 = conv(bias = conv_3_bias_0_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 = conv_3_weight_0_to_fp16, x = model_1_model_p_re_lu_25_add_model_1_model_p_re_lu_25_Relu_model_1_model_p_re_lu_25_Neg_1_model_1_model_p_re_lu_25_Relu_1_model_1_model_p_re_lu_25_mul_dequantize_prelu_1_add_cast_fp16)[name = tensor("conv_3_cast_fp16")]; + tensor Conv2D_28_perm_0 = const()[name = tensor("Conv2D_28_perm_0"), val = tensor([0, 2, 3, 1])]; + tensor model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_8_NO_PRUNING_Conv2D_model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_29_perm_0, x = conv_2_cast_fp16)[name = tensor("transpose_113")]; + tensor model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_regressor_palm_8_Reshape_shape, x = model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_model_1_model_regressor_palm_8_NO_PRUNING_Conv2D_model_1_model_regressor_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16")]; + tensor model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_8_NO_PRUNING_Conv2D_model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16 = transpose(perm = Conv2D_28_perm_0, x = conv_3_cast_fp16)[name = tensor("transpose_112")]; + tensor model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16 = reshape(shape = model_1_model_reshaped_classifier_palm_8_Reshape_shape, x = model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_model_1_model_classifier_palm_8_NO_PRUNING_Conv2D_model_1_model_classifier_palm_8_NO_PRUNING_BiasAdd_ReadVariableOp_resource1_cast_fp16)[name = tensor("model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16")]; + tensor Identity_interleave_0 = const()[name = tensor("Identity_interleave_0"), val = tensor(false)]; + tensor Identity_cast_fp16 = concat(axis = Identity_axis, interleave = Identity_interleave_0, values = (model_1_model_reshaped_regressor_palm_8_Reshape_cast_fp16, model_1_model_reshaped_regressor_palm_16_Reshape_cast_fp16))[name = tensor("Identity_cast_fp16")]; + tensor Identity_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1_interleave_0 = const()[name = tensor("Identity_1_interleave_0"), val = tensor(false)]; + tensor Identity_1_cast_fp16 = concat(axis = Identity_1_axis, interleave = Identity_1_interleave_0, values = (model_1_model_reshaped_classifier_palm_8_Reshape_cast_fp16, model_1_model_reshaped_classifier_palm_16_Reshape_cast_fp16))[name = tensor("Identity_1_cast_fp16")]; + tensor Identity_1_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("Identity_1_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor Identity_1 = cast(dtype = Identity_1_cast_fp16_to_fp32_dtype_0, x = Identity_1_cast_fp16)[name = tensor("cast_3")]; + tensor Identity = cast(dtype = Identity_cast_fp16_to_fp32_dtype_0, x = Identity_cast_fp16)[name = tensor("cast_4")]; + } -> (Identity, Identity_1); +} \ No newline at end of file diff --git a/compiled/palm_detection_lite.mlmodelc/weights/weight.bin b/compiled/palm_detection_lite.mlmodelc/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..043eda9315d255543fd92882c62f5e74fa26bace --- /dev/null +++ b/compiled/palm_detection_lite.mlmodelc/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:69aefba80f0f30eeb483c358942a62345aad4e8d766f581287d298dfac16f652 +size 1926208 diff --git a/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..403e3b25f11a5a612b0a60507b83b217dbfa7b14 --- /dev/null +++ b/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c36c508ee2308d2235cc8edf3d398fff913b36c259dc2270374d3ea2553f5ed0 +size 65255 diff --git a/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..98e05dc3602e993864827b494bd0aed1ee59bc99 --- /dev/null +++ b/coreml/face_detection_short_range.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:57d6801e4691739cfc3734fd554c2998c016ae19451e0a68d07fce60438753f8 +size 205120 diff --git a/coreml/face_detection_short_range.mlpackage/Manifest.json b/coreml/face_detection_short_range.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c63bd282834cb59ca33b678968f7edbbb1cbeec9 --- /dev/null +++ b/coreml/face_detection_short_range.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "584CCC32-BECB-4939-8462-B047FDC32B06": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + }, + "F5A1F09E-B7AA-4B22-B48F-EB2423BBC405": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + } + }, + "rootModelIdentifier": "F5A1F09E-B7AA-4B22-B48F-EB2423BBC405" +} diff --git a/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..920bcff6471ca715ce9d27a076a60cbd8437e6a5 --- /dev/null +++ b/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:aad982609e4f461c9050b47c45ffa57b867195c202235d1905d5b8bcd23e2de5 +size 80326 diff --git a/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..3bc41206850333aa2680a5fb7c26c27178f5ede7 --- /dev/null +++ b/coreml/face_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:da5fc514baaf96f67f0931b5ed66f1d62b685121198f1f56f96effba8296c614 +size 1212536 diff --git a/coreml/face_landmark.mlpackage/Manifest.json b/coreml/face_landmark.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9693a174b2f83644eddf72c420751b58ee3da5e6 --- /dev/null +++ b/coreml/face_landmark.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "0CC954FC-412E-49C6-86A4-DC749E364D8A": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + }, + "8023CA55-1A5C-449E-BE28-69B6E1197FBA": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + } + }, + "rootModelIdentifier": "0CC954FC-412E-49C6-86A4-DC749E364D8A" +} diff --git a/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..475cde33697c893a36a0a4619350b93a9a6c70a3 --- /dev/null +++ b/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7c9e860e3358ca17a276a9f7f9bae8081f2238a92c2375dcc377ff2d07f96af2 +size 97392 diff --git a/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..fd84947b27f22ae8b9a298203277de1e312d3d6b --- /dev/null +++ b/coreml/hand_landmark_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:acc3ed6c4b578362d20343862c7c86e0a31c87847f447d556f3e41288cf3b81b +size 5438654 diff --git a/coreml/hand_landmark_full.mlpackage/Manifest.json b/coreml/hand_landmark_full.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..292c33b02aef7d94c07248ec895287a1221af6ac --- /dev/null +++ b/coreml/hand_landmark_full.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "03DDF8FD-446C-4AA9-BF92-EAC7141DADDE": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + }, + "56E37D1E-5C8C-4B39-8AFA-8222E12B40C2": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + } + }, + "rootModelIdentifier": "03DDF8FD-446C-4AA9-BF92-EAC7141DADDE" +} diff --git a/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..b29e217649179d3bc616d8da591df1619821bef4 --- /dev/null +++ b/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2df375a8a39120351818ef1083f6642f64938f451cb1e271bc109929c667a85e +size 98902 diff --git a/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..9a8f9006b5c4ebd562b2654b96d69f55286095e7 --- /dev/null +++ b/coreml/hand_landmark_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a501a09f7dbf9053985e9351253ec84f039ddf8443624cf32687bb68b5e17668 +size 2030526 diff --git a/coreml/hand_landmark_lite.mlpackage/Manifest.json b/coreml/hand_landmark_lite.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4ba451a1278943958e559eaff10677b49addf9c9 --- /dev/null +++ b/coreml/hand_landmark_lite.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "0D40E5C7-527A-49E1-87CF-F88B7EFE364C": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + }, + "1BBB9CBA-0CC4-4CD5-912D-6FF881750625": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + } + }, + "rootModelIdentifier": "0D40E5C7-527A-49E1-87CF-F88B7EFE364C" +} diff --git a/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..5f7963e0f49d9f17eee653806196ecea57089dd0 --- /dev/null +++ b/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:89afdc44eb7b6a9cf818c807517805a98a4fabbc13a36d91741e5d16b0787be1 +size 141437 diff --git a/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..4ab15d29d0782c8d45d16765b1b978aeb810c625 --- /dev/null +++ b/coreml/iris_landmark.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8503c3a6396c2616f4879916f08ff3702cc9fe7d9f1a62618396fc3b5747859b +size 1311710 diff --git a/coreml/iris_landmark.mlpackage/Manifest.json b/coreml/iris_landmark.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9874c003963abf4ee6afa2ceccf62ae83303f46b --- /dev/null +++ b/coreml/iris_landmark.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "9FDC6884-68BF-4927-B4AD-7582D875DE27": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + }, + "B27337E8-E046-489B-B78A-C70BB78862EB": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + } + }, + "rootModelIdentifier": "9FDC6884-68BF-4927-B4AD-7582D875DE27" +} diff --git a/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..4c9f146265c9594cd5433a890a5e351a767fd47e --- /dev/null +++ b/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ec8389c9d46d56d78da4aa8ee6f87da454eb006163e345af9243395562bd6bd0 +size 158948 diff --git a/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..d7b0983ce159c64d8da879c34676a0385e73e26b --- /dev/null +++ b/coreml/palm_detection_full.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1305c52bab2d07badb9e18671b925475d9cc9b9c48d3f916185f7f7c93ddd3f1 +size 2272384 diff --git a/coreml/palm_detection_full.mlpackage/Manifest.json b/coreml/palm_detection_full.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..934b65657fff77c65a437aadbfa84a8837ed489b --- /dev/null +++ b/coreml/palm_detection_full.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "0544E9FE-1609-4B64-8680-C5727CF85118": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + }, + "7E1E7442-178F-4DF5-B2C7-974BB16B8C4C": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + } + }, + "rootModelIdentifier": "7E1E7442-178F-4DF5-B2C7-974BB16B8C4C" +} diff --git a/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel b/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel new file mode 100644 index 0000000000000000000000000000000000000000..e7e4683b5bb18ca42999f411549115943f3c5ba8 --- /dev/null +++ b/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/model.mlmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0222265b7b34000b1d52f1a7a2d4f0001269c75994693e0fed75e77a2c38b920 +size 135956 diff --git a/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin b/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin new file mode 100644 index 0000000000000000000000000000000000000000..043eda9315d255543fd92882c62f5e74fa26bace --- /dev/null +++ b/coreml/palm_detection_lite.mlpackage/Data/com.apple.CoreML/weights/weight.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:69aefba80f0f30eeb483c358942a62345aad4e8d766f581287d298dfac16f652 +size 1926208 diff --git a/coreml/palm_detection_lite.mlpackage/Manifest.json b/coreml/palm_detection_lite.mlpackage/Manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8c7a2a58afc56c50f160fc51a132ff9bc1b0d47a --- /dev/null +++ b/coreml/palm_detection_lite.mlpackage/Manifest.json @@ -0,0 +1,18 @@ +{ + "fileFormatVersion": "1.0.0", + "itemInfoEntries": { + "24E1225B-B35E-4A32-9E59-33081E821771": { + "author": "com.apple.CoreML", + "description": "CoreML Model Specification", + "name": "model.mlmodel", + "path": "com.apple.CoreML/model.mlmodel" + }, + "A11DD8CD-2486-4B86-B6FE-AD48BD17EA26": { + "author": "com.apple.CoreML", + "description": "CoreML Model Weights", + "name": "weights", + "path": "com.apple.CoreML/weights" + } + }, + "rootModelIdentifier": "24E1225B-B35E-4A32-9E59-33081E821771" +}