wehub-resource-sync
67 lines
2.3 KiB
C++
67 lines
2.3 KiB
C++
/* Copyright 2020 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 <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/functional_ops.h"
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#include "tensorflow/core/framework/attr_value.pb.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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absl::Status PartitionedCallGrad(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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NameAttrList f;
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TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "f", &f));
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for (const auto& attr : op.node()->attrs()) {
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(*f.mutable_attr())[attr.first] = attr.second;
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}
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std::vector<Output> func_inputs;
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std::vector<DataType> input_dtypes;
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const int num_inputs = op.num_inputs();
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func_inputs.reserve(num_inputs + grad_inputs.size());
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input_dtypes.reserve(num_inputs);
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for (int i = 0; i < num_inputs; i++) {
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func_inputs.push_back(op.input(i));
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input_dtypes.push_back(op.input_type(i));
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}
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func_inputs.insert(std::end(func_inputs), std::begin(grad_inputs),
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std::end(grad_inputs));
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auto grad = SymbolicGradient(scope, func_inputs, input_dtypes, f);
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if (!scope.ok()) return scope.status();
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for (int i = 0; i < num_inputs; i++) {
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grad_outputs->push_back(grad[i]);
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}
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return scope.status();
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}
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REGISTER_GRADIENT_OP("PartitionedCall", PartitionedCallGrad);
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REGISTER_GRADIENT_OP("StatefulPartitionedCall", PartitionedCallGrad);
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} // anonymous namespace
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} // namespace ops
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} // namespace tensorflow
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