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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/dataset.h"
#include "tensorflow/core/framework/partial_tensor_shape.h"
#include "tensorflow/core/framework/tensor.h"
namespace tensorflow {
namespace {
// See documentation in ../ops/dataset_ops.cc for a high-level
// description of the following op.
class AssertNextDatasetOp : public UnaryDatasetOpKernel {
public:
explicit AssertNextDatasetOp(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 {
std::vector<string> transformations;
OP_REQUIRES_OK(ctx, ParseVectorArgument<string>(ctx, "transformations",
&transformations));
*output =
new Dataset(ctx, input, transformations, output_types_, output_shapes_);
}
private:
class Dataset : public GraphDatasetBase {
public:
Dataset(OpKernelContext* ctx, const DatasetBase* input,
const std::vector<string>& transformations,
const DataTypeVector& output_types,
const std::vector<PartialTensorShape>& output_shapes)
: GraphDatasetBase(ctx),
input_(input),
transformations_(transformations),
output_types_(output_types),
output_shapes_(output_shapes) {
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, "::Assert")}));
}
const DataTypeVector& output_dtypes() const override {
return output_types_;
}
const std::vector<PartialTensorShape>& output_shapes() const override {
return output_shapes_;
}
string DebugString() const override {
return "AssertNextDatasetOp::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));
Node* transformations_node = nullptr;
TF_RETURN_IF_ERROR(b->AddVector(transformations_, &transformations_node));
TF_RETURN_IF_ERROR(b->AddDataset(
this, {input_graph_node, transformations_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 {
std::vector<string> tokens =
str_util::Split(prefix(), ':', str_util::SkipEmpty());
if (dataset()->transformations_.size() > tokens.size() - 2) {
return errors::InvalidArgument(
"Asserted next ", dataset()->transformations_.size(),
" transformations but encountered only ", tokens.size() - 2, ".");
}
int n = tokens.size();
for (size_t i = 0; i < dataset()->transformations_.size(); ++i) {
if (dataset()->transformations_[i] != tokens[n - 2 - i]) {
return errors::InvalidArgument(
"Asserted ", dataset()->transformations_[i],
" transformation at offset ", i, " but encountered ",
tokens[n - 2 - i], " transformation instead.");
}
}
return dataset()->input_->MakeIterator(ctx, prefix(), &input_impl_);
}
Status GetNextInternal(IteratorContext* ctx,
std::vector<Tensor>* out_tensors,
bool* end_of_sequence) override {
return input_impl_->GetNext(ctx, out_tensors, end_of_sequence);
}
protected:
Status SaveInternal(IteratorStateWriter* writer) override {
TF_RETURN_IF_ERROR(SaveParent(writer, input_impl_));
return Status::OK();
}
Status RestoreInternal(IteratorContext* ctx,
IteratorStateReader* reader) override {
TF_RETURN_IF_ERROR(RestoreParent(ctx, reader, input_impl_));
return Status::OK();
}
private:
std::unique_ptr<IteratorBase> input_impl_;
};
const DatasetBase* input_;
const std::vector<string> transformations_;
const DataTypeVector output_types_;
const std::vector<PartialTensorShape> output_shapes_;
};
DataTypeVector output_types_;
std::vector<PartialTensorShape> output_shapes_;
};
REGISTER_KERNEL_BUILDER(Name("AssertNextDataset").Device(DEVICE_CPU),
AssertNextDatasetOp);
} // namespace
} // namespace tensorflow
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