98 lines
3.5 KiB
C++
98 lines
3.5 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_COMPILER_TF2XLA_RESOURCE_UTIL_H_
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#define TENSORFLOW_COMPILER_TF2XLA_RESOURCE_UTIL_H_
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#include <string>
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#include "absl/container/flat_hash_map.h"
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#include "absl/container/flat_hash_set.h"
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#include "absl/hash/hash.h"
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#include "absl/strings/str_cat.h"
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#include "tensorflow/core/common_runtime/function.h"
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#include "tensorflow/core/graph/graph.h"
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#include "tensorflow/core/lib/core/errors.h"
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#include "tensorflow/stream_executor/lib/statusor.h"
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namespace tensorflow {
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class ResourceUsageAnalysis {
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public:
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// NodeInfo is a triple of function_name:node_name:op to uniquely identity a
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// node in graph. ResourceUsageAnalysis uses it to represent resource sources
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// and users.
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class NodeInfo {
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public:
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absl::optional<std::string> function_name_;
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std::string node_name_;
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std::string op_;
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NodeInfo() {}
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NodeInfo(const absl::optional<std::string>& function_name,
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std::string node_name, std::string op)
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: function_name_(function_name),
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node_name_(std::move(node_name)),
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op_(std::move(op)) {}
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std::string DebugString() const {
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return absl::StrJoin({function_name_.value_or(""), node_name_, op_}, ":");
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}
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bool operator==(const NodeInfo& o) const {
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return function_name_ == o.function_name_ && node_name_ == o.node_name_ &&
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op_ == o.op_;
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}
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template <typename H>
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friend H AbslHashValue(H h, const NodeInfo& o) {
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return H::combine(std::move(h), o.function_name_, o.node_name_, o.op_);
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}
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};
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// This method analyzes a Tensorflow graph and finds all operations that
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// create Stack/TensorArray resources and all the operations that consume
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// resource created by them.
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//
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// Note that _Arg nodes that introduce resources are not considered sources.
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// Note again that Control Flow v1 nodes
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// (Enter/Exit/Switch/Merge/NextIteration) are not supported. Graphs contain
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// these nodes cause analysis failures. However Control Flow v2 nodes
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// (While/If) will be supported.
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//
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// TODO(b/135628319): Support analyzing functional while/if as pass-through
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// ops.
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//
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// For example, consider following subgraph:
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//
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// TensorArrayOp -> Identity -> TensorArrayWriteOp
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//
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// It should be able to tell that TensorArrayWriteOp actually operates on the
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// resource created by TensorArrayOp even though there might be
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// non-resource-specific operations like Identity (or other pass-through
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// operations).
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//
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// source_to_path maps the nodes that creates resources to all nodes that
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// operate on the corresponding resource, not including sources themselves. It
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// is cleared upon calling this method.
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static Status Analyze(
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const Graph* graph, FunctionLibraryRuntime* lib_runtime,
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absl::flat_hash_map<NodeInfo, absl::flat_hash_set<NodeInfo>>*
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source_to_path);
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};
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} // namespace tensorflow
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#endif // TENSORFLOW_COMPILER_TF2XLA_RESOURCE_UTIL_H_
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