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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.
==============================================================================*/
#ifndef TENSORFLOW_CORE_GRAPPLER_OPTIMIZERS_DATA_VECTORIZATION_VECTORIZER_H_
#define TENSORFLOW_CORE_GRAPPLER_OPTIMIZERS_DATA_VECTORIZATION_VECTORIZER_H_
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/status.h"
namespace tensorflow {
namespace grappler {
namespace vectorization_utils {
// Describes a tensor with its operation Node and output position
typedef std::pair<Node*, int> Port;
// Interface for vectorization of TensorFlow operations. See `CastVectorizer`
// for an example.
class Vectorizer {
public:
virtual ~Vectorizer() {}
// Vectorizes an operation, `node`, by adding Node(s) to `outer_scope`
// that produce the same vector output(s) as executing `node`'s op
// on elements of the vector inputs. The new Node(s) collectively have the
// same number of input and output ports as the node being converted.
// Adds mappings for the new nodes' input and output ports to `inputs` and
// `outputs` respectively, where the i'th Port in inputs/outputs
// corresponds to the i'th input/output port of the node to be converted.
virtual Status Vectorize(const Node& node, Graph* outer_scope,
std::vector<Port>* input_ports,
std::vector<Port>* output_ports) = 0;
};
} // namespace vectorization_utils
} // namespace grappler
} // namespace tensorflow
#endif // TENSORFLOW_CORE_GRAPPLER_OPTIMIZERS_DATA_VECTORIZATION_VECTORIZER_H_
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