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/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* 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.
*/
#pragma once
#ifdef __x86_64__
#include <immintrin.h>
#endif
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/conversions.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
// convert to float16 reducing mantissa, preserving exponent
void fp32_to_bfp16(const float* source, size_t size, float* dest);
// convert to float24 reducing mantissa, preserving exponent
void fp32_to_bfp24(const float* source, size_t size, float* dest);
// convert to float14 reducing mantissa, preserving exponent
void fp32_to_bfp14(const float* source, size_t size, float* dest);
void fp32_to_bfp16_scalar(const float* source, size_t size, float* dest);
// convert to IEEE float16
void fp32_to_fp16(const float* source, size_t size, float* dest);
// fp32 -> int32 -> += 1<< 15 -> fp32 -> truncation
void fp32_to_bfp16_round(const float* source, size_t size, float* dest);
// This is Caffe's InnerProductOp, with a name that fits its purpose better.
template <
void (*Q)(const float*, size_t, float*),
class Context,
class Engine = DefaultEngine,
bool TransposeWeight = true>
class FullyConnectedFakeLowpFPOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
FullyConnectedFakeLowpFPOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
axis_(this->template GetSingleArgument<int32_t>("axis", 1)),
axis_w_(this->template GetSingleArgument<int32_t>("axis_w", 1)),
float16_compute_(
this->template GetSingleArgument<bool>("float16_compute", false)) {}
~FullyConnectedFakeLowpFPOp() {}
template <
typename T_X,
typename T_W,
typename T_B,
typename T_Y,
typename MATH>
bool DoRunWithType();
bool RunOnDevice() override {
return DoRunWithType<
float, // X
float, // W
float, // B
float, // Y
float>(); // Math
}
protected:
size_t axis_{1};
size_t axis_w_{1};
// A local vector to cache the output shape so we don't need to recreate
// a vector object every time we run Run().
vector<int64_t> Y_shape_cache_;
Tensor bias_multiplier_;
bool float16_compute_;
};
template <
void (*Q)(const float*, size_t, float*),
class Context,
class Engine = DefaultEngine,
bool TransposeWeight = true>
class FullyConnectedGradientFakeLowpFPOp : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
FullyConnectedGradientFakeLowpFPOp(
const OperatorDef& operator_def,
Workspace* ws)
: Operator<Context>(operator_def, ws),
axis_(this->template GetSingleArgument<int32_t>("axis", 1)),
axis_w_(this->template GetSingleArgument<int32_t>("axis_w", 1)),
float16_compute_(
this->template GetSingleArgument<bool>("float16_compute", false)) {}
~FullyConnectedGradientFakeLowpFPOp() {}
template <
typename T_X,
typename T_W,
typename T_DY,
typename T_B,
typename T_DX,
typename T_DW,
typename T_DB,
typename MATH>
bool DoRunWithType();
bool RunOnDevice() override {
return DoRunWithType<
float, // X
float, // W
float, // dY
float, // B
float, // dX
float, // dW
float, // dB
float>(); // Math
}
protected:
size_t axis_{1};
size_t axis_w_{1};
Tensor bias_multiplier_;
bool float16_compute_;
};
} // namespace caffe2
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