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fix format (#608)

pull/673/head
xuqifan897 2022-03-31 22:30:39 -07:00 committed by binmakeswell
parent f2da21a827
commit f2d2a1597a
1 changed files with 71 additions and 81 deletions
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152
colossalai/kernel/cuda_native/csrc/cpu_adam.h
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@ -21,11 +21,11 @@ SOFTWARE
*/
#pragma once
#include <cublas_v2.h>
#include <cuda.h>
#include <cuda_fp16.h>
#include <cuda_runtime_api.h>
#include <stdio.h>
#include <cuda.h>
#include <cublas_v2.h>
#if (__x86_64__ || __i386__)
#include <cpuid.h>
@ -48,8 +48,11 @@ SOFTWARE
#define SIMD_FMA(x, y, c) _mm512_fmadd_ps(x, y, c)
#define SIMD_SQRT(x) _mm512_sqrt_ps(x)
#define SIMD_DIV(x, y) _mm512_div_ps(x, y)
#define SIMD_LOAD_HALF(x) _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i*)(x)))
#define SIMD_STORE_HALF(x, d) _mm256_store_ps(x, _mm256_castsi256_ps(_mm512_cvtps_ph(d, _MM_FROUND_TO_NEAREST_INT)))
#define SIMD_LOAD_HALF(x) \
_mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(x)))
#define SIMD_STORE_HALF(x, d) \
_mm256_store_ps( \
x, _mm256_castsi256_ps(_mm512_cvtps_ph(d, _MM_FROUND_TO_NEAREST_INT)))
#elif defined(__AVX256__) or defined(__AVX2__)
#define SIMD_WIDTH 8
@ -62,102 +65,89 @@ SOFTWARE
#define SIMD_FMA(x, y, c) _mm256_fmadd_ps(x, y, c)
#define SIMD_SQRT(x) _mm256_sqrt_ps(x)
#define SIMD_DIV(x, y) _mm256_div_ps(x, y)
#define SIMD_LOAD_HALF(x) _mm256_cvtph_ps(_mm_loadu_si128((const __m128i*)(x)))
#define SIMD_STORE_HALF(x, d) _mm_store_ps(x, _mm_castsi128_ps(_mm256_cvtps_ph(d, _MM_FROUND_TO_NEAREST_INT)))
#define SIMD_LOAD_HALF(x) _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)(x)))
#define SIMD_STORE_HALF(x, d) \
_mm_store_ps( \
x, _mm_castsi128_ps(_mm256_cvtps_ph(d, _MM_FROUND_TO_NEAREST_INT)))
#endif
union AVX_Data {
#if defined(__AVX512__)
__m512 data;
__m512 data;
#elif defined(__AVX256__) or defined(__AVX2__)
__m256 data;
__m256 data;
#endif
// float data_f[16];
// float data_f[16];
};
#endif
#define STEP(SPAN) \
void Step_##SPAN(float* _params, \
float* grads, \
float* _exp_avg, \
float* _exp_avg_sq, \
size_t _param_size, \
bool param_half_precision = false, \
bool grad_half_precision = false, \
float loss_scale = -1);
#define STEP(SPAN) \
void Step_##SPAN(float *_params, float *grads, float *_exp_avg, \
float *_exp_avg_sq, size_t _param_size, \
bool param_half_precision = false, \
bool grad_half_precision = false, float loss_scale = -1);
class Adam_Optimizer {
public:
Adam_Optimizer(float alpha = 1e-3,
float betta1 = 0.9,
float betta2 = 0.999,
float eps = 1e-8,
float weight_decay = 0,
bool adamw_mode = true)
: _alpha(alpha),
_betta1(betta1),
_betta2(betta2),
_eps(eps),
_weight_decay(weight_decay),
_betta1_t(1.0),
_betta2_t(1.0),
_step(0),
_adamw_mode(adamw_mode){}
~Adam_Optimizer(){}
STEP(1)
STEP(4)
STEP(8)
inline void IncrementStep(size_t step, float beta1, float beta2)
{
if (beta1 != _betta1 || beta2 != _betta2) {
_step = step;
_betta1 = beta1;
_betta2 = beta2;
_betta1_t = std::pow(_betta1, step);
_betta2_t = std::pow(_betta2, step);
} else {
_step++;
if (_step != step) {
_betta1_t = std::pow(_betta1, step);
_betta2_t = std::pow(_betta2, step);
_step = step;
} else {
_betta1_t *= _betta1;
_betta2_t *= _betta2;
}
}
}
inline void update_state(float lr, float epsilon, float weight_decay, bool bias_correction)
{
_alpha = lr;
_eps = epsilon;
_weight_decay = weight_decay;
Adam_Optimizer(float alpha = 1e-3, float betta1 = 0.9, float betta2 = 0.999,
float eps = 1e-8, float weight_decay = 0,
bool adamw_mode = true)
: _alpha(alpha), _betta1(betta1), _betta2(betta2), _eps(eps),
_weight_decay(weight_decay), _betta1_t(1.0), _betta2_t(1.0), _step(0),
_adamw_mode(adamw_mode) {}
~Adam_Optimizer() {}
_bias_correction1 = 1.0f;
_bias_correction2 = 1.0f;
if (bias_correction == 1) {
_bias_correction1 = 1 - _betta1_t;
_bias_correction2 = 1 / sqrt(1 - _betta2_t);
}
STEP(1)
STEP(4)
STEP(8)
inline void IncrementStep(size_t step, float beta1, float beta2) {
if (beta1 != _betta1 || beta2 != _betta2) {
_step = step;
_betta1 = beta1;
_betta2 = beta2;
_betta1_t = std::pow(_betta1, step);
_betta2_t = std::pow(_betta2, step);
} else {
_step++;
if (_step != step) {
_betta1_t = std::pow(_betta1, step);
_betta2_t = std::pow(_betta2, step);
_step = step;
} else {
_betta1_t *= _betta1;
_betta2_t *= _betta2;
}
}
}
inline void update_state(float lr, float epsilon, float weight_decay,
bool bias_correction) {
_alpha = lr;
_eps = epsilon;
_weight_decay = weight_decay;
_bias_correction1 = 1.0f;
_bias_correction2 = 1.0f;
if (bias_correction == 1) {
_bias_correction1 = 1 - _betta1_t;
_bias_correction2 = 1 / sqrt(1 - _betta2_t);
}
}
private:
float _alpha;
float _betta1;
float _betta2;
float _eps;
float _weight_decay;
float _alpha;
float _betta1;
float _betta2;
float _eps;
float _weight_decay;
float _betta1_t;
float _betta2_t;
size_t _step;
float _betta1_t;
float _betta2_t;
size_t _step;
float _bias_correction1;
float _bias_correction2;
float _bias_correction1;
float _bias_correction2;
bool _adamw_mode;
bool _adamw_mode;
};