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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_COMPILER_XLA_LEGACY_FLAGS_GPU_COMPILER_FLAGS_H_
#define TENSORFLOW_COMPILER_XLA_LEGACY_FLAGS_GPU_COMPILER_FLAGS_H_
// Legacy flags for XLA's gpu_compiler module.
#include <vector>
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/command_line_flags.h"
namespace xla {
namespace legacy_flags {
// Append to *flag_list flag definitions associated with XLA's gpu_compiler
// module.
void AppendGpuCompilerFlags(std::vector<tensorflow::Flag>* flag_list);
// The values of flags associated with XLA's gpu_compiler module.
typedef struct {
bool xla_gpu_embed_ir; // Embed the LLVM IR module string in the resultant
// GpuExecutable.
string xla_cuda_data_dir; // If non-empty, specifies a local directory
// containing ptxas and nvvm libdevice files.
// Otherwise, by default, we use those from runfile
// directories.
string xla_ptxas_path; // The path to ptxas. Required to log stats of
// the ptx.
} GpuCompilerFlags;
// Return a pointer to the GpuCompilerFlags struct;
// repeated calls return the same pointer.
// This should be called only after Flags::Parse() has returned.
GpuCompilerFlags* GetGpuCompilerFlags();
} // namespace legacy_flags
} // namespace xla
#endif // TENSORFLOW_COMPILER_XLA_LEGACY_FLAGS_GPU_COMPILER_FLAGS_H_
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