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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.
==============================================================================*/
// This header declares functions which may be called by the generated code on
// the CPU. Calls to these functions must be resolved explicitly in the JIT in
// xla::cpu::SimpleResolver. It also defines a per-CpuExecutable context
// which is used to cache expensive state and resources utilized by the
// aforementioned functions.
#ifndef TENSORFLOW_COMPILER_XLA_SERVICE_CPU_CPU_RUNTIME_SSE4_1_H_
#define TENSORFLOW_COMPILER_XLA_SERVICE_CPU_CPU_RUNTIME_SSE4_1_H_
#include "tensorflow/core/platform/macros.h"
namespace xla {
namespace cpu {
namespace runtime {
constexpr char kExpV4F32[] = "__xla_cpu_runtime_ExpV4F32";
constexpr char kLogV4F32[] = "__xla_cpu_runtime_LogV4F32";
constexpr char kTanhV4F32[] = "__xla_cpu_runtime_TanhV4F32";
typedef float V4F32 __attribute__((__vector_size__(16)));
// The following functions are vectorized versions of a selection of libm
// library functions.
// References to these functions are created by the LLVM vectorizer.
V4F32 ExpV4F32(V4F32 x) TF_ATTRIBUTE_WEAK;
V4F32 LogV4F32(V4F32 x) TF_ATTRIBUTE_WEAK;
V4F32 TanhV4F32(V4F32 x) TF_ATTRIBUTE_WEAK;
} // namespace runtime
} // namespace cpu
} // namespace xla
#endif // TENSORFLOW_COMPILER_XLA_SERVICE_CPU_CPU_RUNTIME_SSE4_1_H_
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