| /* Copyright 2017 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 "tensorflow/core/kernels/data/tensor_dataset_op.h" |
| |
| #include "tensorflow/core/framework/partial_tensor_shape.h" |
| #include "tensorflow/core/framework/tensor.h" |
| #include "tensorflow/core/graph/graph.h" |
| #include "tensorflow/core/kernels/data/dataset_utils.h" |
| #include "tensorflow/core/kernels/data/name_utils.h" |
| |
| namespace tensorflow { |
| namespace data { |
| |
| // See documentation in ../../ops/dataset_ops.cc for a high-level |
| // description of the following op. |
| |
| /* static */ constexpr const char* const TensorDatasetOp::kDatasetType; |
| /* static */ constexpr const char* const TensorDatasetOp::kComponents; |
| /* static */ constexpr const char* const TensorDatasetOp::kToutput_types; |
| /* static */ constexpr const char* const TensorDatasetOp::kOutputShapes; |
| |
| constexpr char kFromTensor[] = "FromTensor"; |
| constexpr char kProduced[] = "produced"; |
| |
| class TensorDatasetOp::Dataset : public DatasetBase { |
| public: |
| Dataset(OpKernelContext* ctx, std::vector<Tensor> tensors) |
| : DatasetBase(DatasetContext(ctx)), tensors_(std::move(tensors)) { |
| for (const Tensor& t : tensors_) { |
| dtypes_.push_back(t.dtype()); |
| shapes_.emplace_back(t.shape().dim_sizes()); |
| } |
| } |
| |
| std::unique_ptr<IteratorBase> MakeIteratorInternal( |
| const string& prefix) const override { |
| return absl::make_unique<Iterator>(Iterator::Params{ |
| this, name_utils::IteratorPrefix(kFromTensor, prefix)}); |
| } |
| |
| const DataTypeVector& output_dtypes() const override { return dtypes_; } |
| |
| const std::vector<PartialTensorShape>& output_shapes() const override { |
| return shapes_; |
| } |
| |
| string DebugString() const override { |
| return name_utils::DatasetDebugString(kDatasetType); |
| } |
| |
| int64 Cardinality() const override { return 1LL; } |
| |
| Status CheckExternalState() const override { return Status::OK(); } |
| |
| protected: |
| Status AsGraphDefInternal(SerializationContext* ctx, |
| DatasetGraphDefBuilder* b, |
| Node** output) const override { |
| std::vector<Node*> components; |
| components.reserve(tensors_.size()); |
| for (const Tensor& t : tensors_) { |
| Node* node; |
| if (ctx->serialize_data_tensors()) { |
| TF_RETURN_IF_ERROR(b->AddTensor(t, &node)); |
| } else { |
| TF_RETURN_IF_ERROR(b->AddPlaceholder(t, &node)); |
| DCHECK_NE(ctx->input_list(), nullptr); |
| ctx->input_list()->emplace_back(node->name(), t); |
| } |
| components.emplace_back(node); |
| } |
| AttrValue dtypes; |
| b->BuildAttrValue(dtypes_, &dtypes); |
| TF_RETURN_IF_ERROR(b->AddDataset(this, {}, {{0, components}}, |
| {{kToutput_types, dtypes}}, output)); |
| return Status::OK(); |
| } |
| |
| private: |
| class Iterator : public DatasetIterator<Dataset> { |
| public: |
| explicit Iterator(const Params& params) |
| : DatasetIterator<Dataset>(params), produced_(false) {} |
| |
| Status GetNextInternal(IteratorContext* ctx, |
| std::vector<Tensor>* out_tensors, |
| bool* end_of_sequence) override { |
| mutex_lock l(mu_); |
| if (!produced_) { |
| *out_tensors = dataset()->tensors_; |
| produced_ = true; |
| *end_of_sequence = false; |
| return Status::OK(); |
| } else { |
| *end_of_sequence = true; |
| return Status::OK(); |
| } |
| } |
| |
| protected: |
| std::shared_ptr<model::Node> CreateNode( |
| IteratorContext* ctx, model::Node::Args args) const override { |
| return model::MakeSourceNode(std::move(args)); |
| } |
| |
| Status SaveInternal(IteratorStateWriter* writer) override { |
| mutex_lock l(mu_); |
| if (produced_) |
| TF_RETURN_IF_ERROR(writer->WriteScalar(full_name(kProduced), "")); |
| return Status::OK(); |
| } |
| |
| Status RestoreInternal(IteratorContext* ctx, |
| IteratorStateReader* reader) override { |
| mutex_lock l(mu_); |
| produced_ = reader->Contains(full_name(kProduced)); |
| return Status::OK(); |
| } |
| |
| private: |
| mutex mu_; |
| bool produced_ GUARDED_BY(mu_); |
| }; |
| |
| const std::vector<Tensor> tensors_; |
| DataTypeVector dtypes_; |
| std::vector<PartialTensorShape> shapes_; |
| }; |
| |
| TensorDatasetOp::TensorDatasetOp(OpKernelConstruction* ctx) |
| : DatasetOpKernel(ctx) { |
| OP_REQUIRES_OK(ctx, ctx->GetAttr(kToutput_types, &output_types_)); |
| OP_REQUIRES_OK(ctx, ctx->GetAttr(kOutputShapes, &output_shapes_)); |
| } |
| |
| void TensorDatasetOp::MakeDataset(OpKernelContext* ctx, DatasetBase** output) { |
| OpInputList inputs; |
| OP_REQUIRES_OK(ctx, ctx->input_list(kComponents, &inputs)); |
| std::vector<Tensor> components(inputs.begin(), inputs.end()); |
| *output = new Dataset(ctx, std::move(components)); |
| OP_REQUIRES_OK(ctx, |
| VerifyTypesMatch((*output)->output_dtypes(), output_types_)); |
| OP_REQUIRES_OK( |
| ctx, VerifyShapesCompatible((*output)->output_shapes(), output_shapes_)); |
| } |
| |
| namespace { |
| REGISTER_KERNEL_BUILDER(Name("TensorDataset").Device(DEVICE_CPU), |
| TensorDatasetOp); |
| } // namespace |
| } // namespace data |
| } // namespace tensorflow |