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// Copyright (c) Microsoft Corporation.
// SPDX-License-Identifier: Apache-2.0
// DeepSpeed Team
#pragma once
#include <cuda.h>
#include <cuda_fp16.h>
#include <stdio.h>
template <typename T>
class Dropout {
public:
struct Config {
float ratio;
uint32_t dim;
bool training;
Config(float r, uint32_t d) : ratio(r), dim(d), training(true) {}
float RATIO() const { return training ? ratio : 0.0; }
inline void SetDim(uint32_t d) { dim = d; }
};
Dropout(const Config& config) : _config(config), _mask(nullptr) {}
virtual ~Dropout() {}
void Forward(int bsz, T* out, const T* vals, cudaStream_t stream, bool bwd = false)
{
launch_dropout<T>(
out, vals, _mask, bsz * _config.dim, _config.dim, _config.RATIO(), stream, bwd);
}
void ForwardWithBias(int bsz, T* vals, const T* bias, cudaStream_t stream)
{
launch_dropout<T>(vals, bias, _mask, bsz, _config.dim, _config.RATIO(), stream);
}
void ForwardWithBias(int bsz,
T* out,
const T* vals,
const T* residual,
const T* bias,
cudaStream_t stream)
{
launch_dropout<T>(
out, vals, residual, bias, _mask, bsz, _config.dim, _config.RATIO(), stream);
}
void Backward(int bsz, T* d_vals, cudaStream_t stream)
{
launch_dropout_grad<T>(d_vals, _mask, bsz * _config.dim, _config.RATIO(), stream);
}
void Backward(int bsz, T* d_vals_out, const T* d_vals, cudaStream_t stream)
{
launch_dropout_grad<T>(
d_vals_out, d_vals, _mask, bsz * _config.dim, _config.RATIO(), stream);
}
bool HasDropout() const { return _config.RATIO() > 0.0; }
void SetTrainingMode(bool training) { _config.training = training; }
void SetMask(uint8_t* mask)
{
if (!mask) { throw std::runtime_error("Dropout mask is null."); }
_mask = mask;
}
Config GetConfig() const { return _config; }
inline void SetDimension(uint32_t dim) { _config.SetDim(dim); }
private:
uint8_t* _mask;
Config _config;
};
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