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/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include <map>
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/kernels/data/dataset.h"
namespace tensorflow {
namespace {
// The purpose of identity dataset is to serve as a placeholder when performing
// optimizations. It is not expected to be surfaced in the Python API.
class IdentityDatasetOp : public UnaryDatasetOpKernel {
public:
explicit IdentityDatasetOp(OpKernelConstruction* ctx)
: UnaryDatasetOpKernel(ctx) {
OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_));
OP_REQUIRES_OK(ctx, ctx->GetAttr("output_shapes", &output_shapes_));
}
protected:
void MakeDataset(OpKernelContext* ctx, DatasetBase* input,
DatasetBase** output) override {
*output = new Dataset(ctx, input);
}
private:
class Dataset : public GraphDatasetBase {
public:
Dataset(OpKernelContext* ctx, const DatasetBase* input)
: GraphDatasetBase(ctx), input_(input) {
input_->Ref();
}
~Dataset() override { input_->Unref(); }
std::unique_ptr<IteratorBase> MakeIteratorInternal(
const string& prefix) const override {
return std::unique_ptr<IteratorBase>(
new Iterator({this, strings::StrCat(prefix, "::Identity")}));
}
const DataTypeVector& output_dtypes() const override {
return input_->output_dtypes();
}
const std::vector<PartialTensorShape>& output_shapes() const override {
return input_->output_shapes();
}
string DebugString() const override { return "IdentityDatasetOp::Dataset"; }
protected:
Status AsGraphDefInternal(OpKernelContext* ctx, DatasetGraphDefBuilder* b,
Node** output) const override {
Node* input_graph_node = nullptr;
TF_RETURN_IF_ERROR(b->AddParentDataset(ctx, input_, &input_graph_node));
TF_RETURN_IF_ERROR(b->AddDataset(this, {input_graph_node}, output));
return Status::OK();
}
private:
class Iterator : public DatasetIterator<Dataset> {
public:
explicit Iterator(const Params& params)
: DatasetIterator<Dataset>(params) {}
Status Initialize(IteratorContext* ctx) override {
return errors::Unimplemented(strings::StrCat(prefix(), "::Initialize"));
}
Status GetNextInternal(IteratorContext* ctx,
std::vector<Tensor>* out_tensors,
bool* end_of_sequence) override {
return errors::Unimplemented(
strings::StrCat(prefix(), "::GetNextInternal"));
}
};
const DatasetBase* const input_;
};
DataTypeVector output_types_;
std::vector<PartialTensorShape> output_shapes_;
};
REGISTER_KERNEL_BUILDER(Name("IdentityDataset").Device(DEVICE_CPU),
IdentityDatasetOp);
} // namespace
} // namespace tensorflow
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