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/* 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.
==============================================================================*/
#ifndef TENSORFLOW_GRAPPLER_COSTS_GRAPH_PROPERTIES_H_
#define TENSORFLOW_GRAPPLER_COSTS_GRAPH_PROPERTIES_H_
#include <unordered_map>
#include <vector>
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/grappler/clusters/cluster.h"
#include "tensorflow/core/grappler/costs/op_performance_data.pb.h"
#include "tensorflow/core/grappler/grappler_item.h"
namespace tensorflow {
namespace grappler {
class SymbolicShapeRefiner;
class TopoQueue;
// A TensorFlow model to optimize.
// Models are represented by the combination of a graph, one of more fetch
// nodes, and potentially a set of nodes to feed.
class GraphProperties {
public:
// Factory method for creating a GrapplerShapes from a MetaGraphDef.
// Returns nullptr if the given meta_graph cannot be converted.
explicit GraphProperties(const GrapplerItem& item) : item_(item) {}
Status InferStatically();
Status InferDynamically(Cluster* cluster);
Status InferFromCostGraph(const CostGraphDef& cost_graph);
// Stores `item_.graph` with the inferred output shapes to `output_graph_def`.
Status AnnotateOutputShapes(GraphDef* output_graph_def) const;
// Return the properties of node inputs/outputs, including data types and
// shapes. Note that the dimensions in the shapes can be negative. We use the
// -1 value to denote that we don't know anything about a dimension. We use
// values strictly less than -1 to encode symbolic dimensions: although we
// don't know the actual value of the symbolic dimension, we know that all the
// dimensions denoted by the same negative value are the equal.
bool HasInputProperties(const string& name) const;
bool HasOutputProperties(const string& name) const;
const std::vector<OpInfo::TensorProperties>& GetInputProperties(
const string& node_name) const;
const std::vector<OpInfo::TensorProperties>& GetOutputProperties(
const string& node_name) const;
static void FillTensorPropertiesFromContext(
const shape_inference::ShapeHandle&, const DataType&,
shape_inference::InferenceContext*,
std::unordered_map<const shape_inference::Dimension*, int>* dim_ids,
OpInfo::TensorProperties*);
private:
// Inputs
GrapplerItem item_;
std::map<string, std::vector<OpInfo::TensorProperties>> input_properties_;
std::map<string, std::vector<OpInfo::TensorProperties>> output_properties_;
const std::vector<OpInfo::TensorProperties> missing_properties_;
// Merges shapes <shapes_and_types>, determined from an EnqueueV2 node, into
// <*queue_shapes_and_types>.
static Status MergeEnqueueShapesAndTypes(
SymbolicShapeRefiner* shape_refiner, const Node* qnode,
const std::vector<shape_inference::ShapeAndType>& shapes_and_types,
std::vector<shape_inference::ShapeAndType>* queue_shapes_and_types);
// Relaxes shapes <shapes_and_types>, determined from an EnqueueV2 node, into
// <*queue_shapes_and_types>.
static Status RelaxEnqueueShapesAndMergeTypes(
SymbolicShapeRefiner* shape_refiner, const Node* qnode,
const std::vector<shape_inference::ShapeAndType>& shapes_and_types,
std::vector<shape_inference::ShapeAndType>* queue_shapes_and_types);
// Update the shapes for qnode. If output shapes of qnode have changed,
// enqueue its fanout in 'new_shapes'.
static Status UpdateResource(
const Node* qnode, const std::unordered_set<const Node*>& queue_inputs,
SymbolicShapeRefiner* shape_refiner, bool relax, TopoQueue* new_shapes);
// Update the output shapes of a Merge node, and enqueue its fanout in
// new_shapes if needed.
static Status UpdateMergeNode(SymbolicShapeRefiner* shape_refiner,
const Node* node, bool relax,
TopoQueue* new_shapes);
// Process the Enter node, and enqueue its fanout in new_shapes if needed.
static Status UpdateEnter(SymbolicShapeRefiner* shape_refiner,
const Node* node, bool relax,
TopoQueue* new_shapes);
// Update the shapes for node 'n'. If output shapes for n have changed,
// enqueue its fanout in 'new_shapes'.
static Status UpdateShapes(SymbolicShapeRefiner* shape_refiner, bool relax,
const Node* n, TopoQueue* new_shapes);
// Propagate the shapes for the nodes enqueued in new_shapes and their
// transitive fanout until a fixed point is reached.
Status PropagateShapes(
SymbolicShapeRefiner* shape_refiner, bool relax, TopoQueue* new_shapes,
const std::unordered_map<const Node*, std::unordered_set<const Node*>>&
resources) const;
};
} // end namespace grappler
} // end namespace tensorflow
#endif // TENSORFLOW_GRAPPLER_COSTS_GRAPH_PROPERTIES_H_
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