wehub-resource-sync
139 lines
5.8 KiB
C++
139 lines
5.8 KiB
C++
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <string>
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#include <vector>
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#include "absl/status/status.h"
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#include "tensorflow/cc/framework/grad_op_registry.h"
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#include "tensorflow/cc/framework/gradients.h"
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#include "tensorflow/cc/ops/image_ops_internal.h"
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#include "tensorflow/cc/ops/standard_ops.h"
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#include "tensorflow/core/framework/types.pb.h"
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namespace tensorflow {
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namespace ops {
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namespace {
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REGISTER_NO_GRADIENT_OP("NonMaxSuppression");
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REGISTER_NO_GRADIENT_OP("NonMaxSuppressionV2");
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REGISTER_NO_GRADIENT_OP("NonMaxSuppressionV3");
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REGISTER_NO_GRADIENT_OP("NonMaxSuppressionV4");
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REGISTER_NO_GRADIENT_OP("NonMaxSuppressionV5");
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absl::Status ResizeNearestNeighborGradHelper(
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const Scope& scope, const Operation& op,
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const std::vector<Output>& grad_inputs, std::vector<Output>* grad_outputs) {
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bool align_corners;
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TF_RETURN_IF_ERROR(
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GetNodeAttr(op.node()->attrs(), "align_corners", &align_corners));
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bool half_pixel_centers;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "half_pixel_centers",
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&half_pixel_centers));
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// The internal gradient implementation needs the shape of the input image.
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// x_shape = shape(x)[1:3]
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// = slice(shape(x), {1}, {3 - 1})
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auto x_shape = Slice(scope, Shape(scope, op.input(0)), {1}, {2});
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grad_outputs->push_back(internal::ResizeNearestNeighborGrad(
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scope, grad_inputs[0], x_shape,
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internal::ResizeNearestNeighborGrad::AlignCorners(align_corners)
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.HalfPixelCenters(half_pixel_centers)));
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grad_outputs->push_back(NoGradient());
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return scope.status();
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}
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REGISTER_GRADIENT_OP("ResizeNearestNeighbor", ResizeNearestNeighborGradHelper);
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absl::Status ResizeBilinearGradHelper(const Scope& scope, const Operation& op,
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const std::vector<Output>& grad_inputs,
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std::vector<Output>* grad_outputs) {
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bool align_corners;
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TF_RETURN_IF_ERROR(
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GetNodeAttr(op.node()->attrs(), "align_corners", &align_corners));
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bool half_pixel_centers;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "half_pixel_centers",
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&half_pixel_centers));
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grad_outputs->push_back(internal::ResizeBilinearGrad(
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scope, grad_inputs[0], op.input(0),
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internal::ResizeBilinearGrad::AlignCorners(align_corners)
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.HalfPixelCenters(half_pixel_centers)));
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grad_outputs->push_back(NoGradient());
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return scope.status();
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}
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REGISTER_GRADIENT_OP("ResizeBilinear", ResizeBilinearGradHelper);
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absl::Status ResizeBicubicGradHelper(const Scope& scope, const Operation& op,
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const std::vector<Output>& grad_inputs,
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std::vector<Output>* grad_outputs) {
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bool align_corners;
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TF_RETURN_IF_ERROR(
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GetNodeAttr(op.node()->attrs(), "align_corners", &align_corners));
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bool half_pixel_centers;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "half_pixel_centers",
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&half_pixel_centers));
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grad_outputs->push_back(internal::ResizeBicubicGrad(
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scope, grad_inputs[0], op.input(0),
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internal::ResizeBicubicGrad::AlignCorners(align_corners)
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.HalfPixelCenters(half_pixel_centers)));
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grad_outputs->push_back(NoGradient());
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return scope.status();
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}
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REGISTER_GRADIENT_OP("ResizeBicubic", ResizeBicubicGradHelper);
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absl::Status ScaleAndTranslateGradHelper(const Scope& scope,
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const Operation& op,
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const std::vector<Output>& grad_inputs,
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std::vector<Output>* grad_outputs) {
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std::string kernel_type;
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TF_RETURN_IF_ERROR(
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GetNodeAttr(op.node()->attrs(), "kernel_type", &kernel_type));
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bool antialias;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "antialias", &antialias));
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grad_outputs->push_back(internal::ScaleAndTranslateGrad(
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scope, grad_inputs[0], op.input(0), op.input(2), op.input(3),
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internal::ScaleAndTranslateGrad::KernelType(kernel_type)
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.Antialias(antialias)));
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grad_outputs->push_back(NoGradient());
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grad_outputs->push_back(NoGradient());
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grad_outputs->push_back(NoGradient());
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return scope.status();
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}
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REGISTER_GRADIENT_OP("ScaleAndTranslate", ScaleAndTranslateGradHelper);
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absl::Status CropAndResizeGradHelper(const Scope& scope, const Operation& op,
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const std::vector<Output>& grad_inputs,
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std::vector<Output>* grad_outputs) {
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DataType input_type;
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std::string method;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "method", &method));
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "T", &input_type));
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auto image_shape = Shape(scope, op.input(0));
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grad_outputs->push_back(CropAndResizeGradImage(
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scope, grad_inputs[0], op.input(1), op.input(2), image_shape, input_type,
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CropAndResizeGradImage::Method(method)));
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grad_outputs->push_back(CropAndResizeGradBoxes(
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scope, grad_inputs[0], op.input(0), op.input(1), op.input(2)));
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grad_outputs->push_back(NoGradient());
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grad_outputs->push_back(NoGradient());
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return scope.status();
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}
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REGISTER_GRADIENT_OP("CropAndResize", CropAndResizeGradHelper);
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} // anonymous namespace
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} // namespace ops
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} // namespace tensorflow
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