wehub-resource-sync
68 lines
2.4 KiB
C++
68 lines
2.4 KiB
C++
/* Copyright 2022 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_JIT_XLA_COMPILE_UTIL_H_
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#define TENSORFLOW_COMPILER_JIT_XLA_COMPILE_UTIL_H_
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#include <memory>
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#include <string>
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#include "tensorflow/compiler/tf2xla/xla_argument.h"
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#include "tensorflow/core/graph/graph.h"
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namespace tensorflow {
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// The number of compiler threads to use for asynchronous device compilation.
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inline constexpr int64_t kNumAsyncDeviceCompilerThreads = 10;
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enum class DeviceCompileMode {
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kLazy,
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kStrict,
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kAsync,
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};
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enum class DeviceCompileState {
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kUncompiled,
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kCompiling,
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kCompiled,
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};
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// Creates a single-node graph using the specified `node_def` as the only op
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// apart from the arg and retval nodes corresponding to `args` and
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// `result_types` respectively.
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absl::StatusOr<std::unique_ptr<Graph>> CreateSingleOpGraph(
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const NodeDef& node_def, absl::Span<const XlaArgument> args,
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absl::Span<const DataType> result_types);
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// Checks if single device compilation and execution with PJRT is enabled for
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// `device_type` in either the XlaLaunch op or the XlaCompileOnDemand op.
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bool UsePjRtForSingleDeviceCompilation(const DeviceType& device_type);
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// Gets the resource name of the PjRt DeviceCompiler for `device_type`.
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std::string GetPjRtDeviceCompilerResourceName(const DeviceType& device_type);
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// Gets the resource name of the DeviceCompilationProfiler for `device_type`
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// when PjRt is used for compilation and execution.
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std::string GetPjRtDeviceCompilationProfilerResourceName(
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const DeviceType& device_type);
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// Gets the ResourceMgr where the DeviceCompiler is/should be stored for the
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// given `device_type`.
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absl::StatusOr<ResourceMgr*> GetResourceMgrForDeviceCompiler(
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const OpKernelContext& ctx, const DeviceType& device_type);
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} // namespace tensorflow
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#endif // TENSORFLOW_COMPILER_JIT_XLA_COMPILE_UTIL_H_
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