6de4957aba
This is useful because it reduces the number of kTuple ops within the loop, which can be expensive. (Normally these would be removed by tuple simplifier, but that doesn't operate across computation boundaries.) But it's also useful because it unlocks further optimization opportunities. For example, it makes it easier to remove dead loop parameters. PiperOrigin-RevId: 220846222
54 lines
2.1 KiB
C++
54 lines
2.1 KiB
C++
/* Copyright 2017 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_XLA_SERVICE_WHILE_LOOP_SIMPLIFIER_H_
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#define TENSORFLOW_COMPILER_XLA_SERVICE_WHILE_LOOP_SIMPLIFIER_H_
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#include "tensorflow/compiler/xla/service/hlo_module.h"
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#include "tensorflow/compiler/xla/service/hlo_pass_interface.h"
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#include "tensorflow/compiler/xla/statusor.h"
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namespace xla {
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// HLO pass that makes the following transformations on while loops:
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//
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// - A while loop with static trip count of 0 is deleted.
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//
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// - A while loop with static trip count of 1 is replaced by its body (sans
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// loop).
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//
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// - Elements of a while loop's tuple that the loop doesn't use are removed
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// from the tuple.
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//
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// - If the while loop's parameter is a nested tuple, it's flattened to a
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// single-level tuple. This is good because it usually reduces the number of
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// kTuple instructions, but also because it unlocks additional optimizations
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// (e.g. removing unused loop parameters).
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//
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// Flattening nested while loop tuples adds a whole mess of likely unnecessary
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// kGetTupleElement and kTuple operations to the graph. We expect that tuple
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// simplifier will be run afterwards.
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//
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class WhileLoopSimplifier : public HloModulePass {
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public:
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~WhileLoopSimplifier() override {}
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absl::string_view name() const override { return "simplify-while-loops"; }
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StatusOr<bool> Run(HloModule* module) override;
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};
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_SERVICE_WHILE_LOOP_SIMPLIFIER_H_
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