/* 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_JIT_FLAGS_H_
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#define TENSORFLOW_COMPILER_JIT_FLAGS_H_
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#include <vector>
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#include "tensorflow/core/platform/types.h"
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#include "tensorflow/core/util/command_line_flags.h"
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namespace tensorflow {
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// Flags associated with the XLA bridge's mark_for_compilation_pass module.
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struct MarkForCompilationPassFlags {
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// Control compilation of operators into XLA computations on CPU and GPU
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// devices. 0 = use ConfigProto setting; -1 = off; 1 = on for things very
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// likely to be improved; 2 = on for everything.
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//
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// Experimental.
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int32 tf_xla_auto_jit;
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// Minimum number of operators in an XLA compilation. Ignored for operators
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// placed on an XLA device or operators explicitly marked for compilation.
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int32 tf_xla_min_cluster_size;
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// Maximum number of operators in an XLA compilation.
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int32 tf_xla_max_cluster_size;
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// Dump graphs during XLA compilation.
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bool tf_xla_clustering_debug;
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// Enables global JIT compilation for CPU via SessionOptions.
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bool tf_xla_cpu_global_jit;
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// "Compiler fuel" for clustering. Only this many ops will be marked as
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// eligible for clustering.
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int64 tf_xla_clustering_fuel;
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// tf_xla_fusion_only is effective only when global_jit_level is set to ON*
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// and overrides its behavior. If true, enable fusion of element-wise
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// operations only using XLA.
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bool tf_xla_fusion_only;
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// If tf_xla_disable_deadness_safety_checks_for_debugging is set to true then
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// we do not do deadness related safety checks. This is unsound in general,
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// but can be used as a debugging aid.
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bool tf_xla_disable_deadness_safety_checks_for_debugging;
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};
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// Flags associated with the XLA bridge's xla_device module.
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struct XlaDeviceFlags {
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// Switch the CPU device into "on-demand" mode, where instead of
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// autoclustering ops are compiled one by one just-in-time.
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// Enabling this mode by a legacy flag is a temporary mechanism. When this
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// feature is battle-tested, we will switch this to be a session option.
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bool tf_xla_compile_on_demand;
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};
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// Flags common to the _Xla* ops and their kernels.
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struct XlaOpsCommonFlags {
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// If true, _XlaCompile always refuses to compile the cluster, which means the
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// XLA clusters always run in the TF executor. Defaults to false.
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bool tf_xla_always_defer_compilation;
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};
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// Flags for the build_xla_ops pass.
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struct BuildXlaOpsPassFlags {
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// Enables lazy compilation for TF/XLA (only when auto-clustering) if true.
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// Defaults to true.
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bool tf_xla_enable_lazy_compilation;
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};
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// Return a pointer to the DumpGraphFlags struct;
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// repeated calls return the same pointer.
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// This should be called only after Flags::Parse() has returned.
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// Getters for flags structs defined above. The first call to any of these
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// parses TF_XLA_FLAGS for all of them. Those functions which return a pointer
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// always return the same pointer.
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MarkForCompilationPassFlags* GetMarkForCompilationPassFlags();
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const BuildXlaOpsPassFlags& GetBuildXlaOpsPassFlags();
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XlaDeviceFlags* GetXlaDeviceFlags();
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const XlaOpsCommonFlags& GetXlaOpsCommonFlags();
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// Appends the flag definitions associated with
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// MarkForCompilationPassFlags/DumpGraphFlags to `flag_list`.
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//
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// Has the side-effect of parsing TF_XLA_FLAGS if that hasn't happened yet.
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void AppendMarkForCompilationPassFlags(
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std::vector<tensorflow::Flag>* flag_list);
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} // namespace tensorflow
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#endif // TENSORFLOW_COMPILER_JIT_FLAGS_H_
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