d04bfee679
These are deprecated in favor of instruction-level fast math, and most of LLVM's backend code was updated to use those instead. Not having them gives us more fine-grained control of fast math flags without loss of performance. Disabling UnsafeFPMath has the side effect of requiring __truncdfhf2 for double->half conversions, so provide that. Also always allow FMA formation, while it's not IEEE754 compliant it never decreases accuracy. PiperOrigin-RevId: 281801638 Change-Id: I2d96220fefebad4d11b1dab8f75b06ccb88a05bf
31 lines
1.1 KiB
C
31 lines
1.1 KiB
C
/* Copyright 2018 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_CPU_RUNTIME_FP16_H_
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#define TENSORFLOW_COMPILER_XLA_SERVICE_CPU_RUNTIME_FP16_H_
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#include "tensorflow/core/platform/types.h"
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// Converts an F32 value to a F16.
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extern "C" tensorflow::uint16 __gnu_f2h_ieee(float);
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// Converts an F16 value to a F32.
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extern "C" float __gnu_h2f_ieee(tensorflow::uint16);
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// Converts an F64 value to a F16.
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extern "C" tensorflow::uint16 __truncdfhf2(double);
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#endif // TENSORFLOW_COMPILER_XLA_SERVICE_CPU_RUNTIME_FP16_H_
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