Currently, collects the runtime of each pass and how many times the pass was run. In the future, we can add more things like the size of the HLO graph before/after each pass. PiperOrigin-RevId: 243212129
83 lines
3.2 KiB
C++
83 lines
3.2 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_HLO_PASS_INTERFACE_H_
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#define TENSORFLOW_COMPILER_XLA_SERVICE_HLO_PASS_INTERFACE_H_
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#include "tensorflow/compiler/xla/service/hlo_module.h"
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#include "tensorflow/compiler/xla/service/hlo_module_group.h"
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#include "tensorflow/compiler/xla/status_macros.h"
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#include "tensorflow/compiler/xla/statusor.h"
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#include "tensorflow/compiler/xla/types.h"
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#include "tensorflow/core/platform/macros.h"
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namespace xla {
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// Base class for HLO passes. These are used with the HloPassPipeline to
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// organize a sequence of passes. An HLO pass should not extend this class
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// directly; it should extend HloModulePass or HloModuleGroupPass.
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class HloPassInterface {
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public:
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virtual ~HloPassInterface() = default;
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virtual absl::string_view name() const = 0;
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// Run the pass on the given HLO module. Returns whether it modified the
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// module.
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virtual StatusOr<bool> Run(HloModule* module) = 0;
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// Run the pass on the given HLO module group. Returns whether it modified the
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// module group. Ideally, the module group variant would be named "Run" as
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// well, but C++ does not handle overloaded virtual methods well.
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virtual StatusOr<bool> RunOnModuleGroup(HloModuleGroup* module_group) = 0;
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virtual bool IsPassPipeline() { return false; }
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};
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// Base class for passes which are module-scoped.
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class HloModulePass : public HloPassInterface {
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public:
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// Runs the pass on a module group by iterating through each module in the
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// group.
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StatusOr<bool> RunOnModuleGroup(HloModuleGroup* module_group) override {
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bool changed = false;
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for (HloModule* module : module_group->modules()) {
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TF_ASSIGN_OR_RETURN(bool module_changed, Run(module));
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changed |= module_changed;
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}
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return changed;
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};
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// Update the layout of a Shape to one that is supported by a given backend.
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// One can call this function after modifying the Shape in case that modifying
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// the Shape requires changes to the layout for the given Backend.
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//
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// TODO(b/129084868): Make this Backend dependent instead of requiring
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// deriving from the pass the and overriding this function.
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virtual void UpdateLayout(Shape* shape) {}
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};
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// Base class for passes which are module-group scoped. These passes cannot run
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// on an HLO module.
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class HloModuleGroupPass : public HloPassInterface {
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public:
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StatusOr<bool> Run(HloModule* module) override {
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return InternalError("Module group pass cannot be run on a module");
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}
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};
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_SERVICE_HLO_PASS_INTERFACE_H_
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