/*******************************************************************************simple_simple_reduce_index
* Copyright 2019 Intel Corporation
*
* 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.
*******************************************************************************/
#include "gpu/intel/include/dispatch.h"
#include "gpu/intel/include/types.h"
#if VECT_DT_N == 1
#define VECT_CHAR_TO_INT convert_int
#else
#define VECT_CHAR_TO_INT CONCAT2(convert_int, VECT_DT_N)
#endif
int simple_reduce_index(int x[5]) {
int dim[5] = {MB, IC, ID, IH, IW} dim[REDUCE_DIM_IDX] = 1 return x[0] * (dim[2] * dim[3] * dim[4]) + x[2] * (dim[3] * dim[4])
+ x[3] * dim[4] + x[4]}
NAMED_KERNEL_ATTR(CALC)
__kernel void simple_calculate_mean_variance(
__global DATA_T *src, __global float *mean, __global float *variance) {
int x[5] x[0] = GWS_GET_STAT_MB() x[1] = GWS_GET_STAT_IC() x[2] = GWS_GET_STAT_ID() x[3] = GWS_GET_STAT_IH() x[4] = GWS_GET_STAT_IW()
// sum of all src elements from given C
VECT_FLOAT_T src_sum = 0 // sum of all src^2 elements from given C
VECT_FLOAT_T src_pow_sum = 0
for (int i = 0 x[REDUCE_DIM_IDX] = i int src_off = SRC_OFF(x[0], x[1], x[2], x[3], x[4]) VECT_FLOAT_T src_vect = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&src[src_off]))) src_sum += src_vect src_pow_sum += src_vect * src_vect }
#if VECT_DT_N == 1
float sum = src_sum float pow_sum = src_pow_sum#else // VECT_DT_N == 1
float sum = 0 float pow_sum = 0 for (int i = 0 sum += src_sum[i] pow_sum += src_pow_sum[i] }
#endif // VECT_DT_N == 1
x[REDUCE_DIM_IDX] = 0 int reduce_idx = simple_reduce_index(x)
float total_sum = sub_group_reduce_add(sum) float total_pow_sum = sub_group_reduce_add(pow_sum) int local_id = get_sub_group_local_id() if (local_id == 0) {
float calc_mean = total_sum / (MB * ID * IH * IW) float calc_variance
= total_pow_sum / (MB * ID * IH * IW) - calc_mean * calc_mean mean[x[1]] = calc_mean variance[x[1]] = calc_variance < 0 ? 0 : calc_variance }
}
KERNEL_ATTR
__kernel void simple_bnorm_fwd(__global DATA_T *src, __global float *mean,
__global float *variance, __global DATA_T *dst, __global float *scale,
__global float *shift, __global char *ws, float eps,
__global DATA_T *src_add, float relu_alpha) {
const int n = GWS_GET_MB() const int c = GWS_GET_IC() const int d = GWS_GET_ID() const int h = GWS_GET_IH() const int w = GWS_GET_IW()#if USE_SCALE == 1
float sm = scale[c]#else
float sm = 1#endif
#if USE_SHIFT == 1
float sv = shift[c]#else
float sv = 0#endif
#if SAVE_STATS == 0
variance += IC#endif
float v_mean = mean[c] float v_variance = variance[c] const int off = SRC_OFF(n, c, d, h, w) float v0 = TO_DEF_ACC_DATA_T(src[off]) float sqrt_variance = 1.0f / sqrt(v_variance + eps) float bn_res = sm * (v0 - v_mean) * sqrt_variance + sv#if FUSE_BN_ADD_RELU == 1
bn_res += TO_DEF_ACC_DATA_T(src_add[off])#endif
#if FUSE_BN_RELU == 1
if (bn_res <= 0) {
bn_res = 0#if IS_TRAINING == 1
ws[off] = 0 } else {
ws[off] = -1#endif
}
#endif
#if WITH_RELU
#if WITH_LEAKY_RELU
if (bn_res < 0) { bn_res *= relu_alpha#else
bn_res = max(bn_res, 0.0f)#endif //WITH_LEAKY_RELU
#endif //WITH_RELU
dst[off] = TO_DATA_T(bn_res)}
#if IS_BWD
#if MB_BLOCK == 16
#define MB16
#endif
NAMED_KERNEL_ATTR(CALC)
__kernel void simple_calculate_stats(__global DATA_T *src, __global float *mean,
__global DATA_T *diff_dst, __global char *ws,
__global float *reduce_temp) {
const int mb = GWS_GET_STAT_MB() const int stat_mb_block_idx = mb / MB_BLOCK
const int c = GWS_GET_STAT_IC()
const int sp_beg = GWS_GET_STAT_SP() const int stat_sp_block = GWS_GET_STAT_SP_BLOCK() const int stat_sp_nblocks = ID * IH * IW / stat_sp_block const int stat_sp_block_idx = sp_beg / stat_sp_block
const int mb_sp_idx
= stat_mb_block_idx * stat_sp_nblocks + stat_sp_block_idx
const int s_off = c * ID * IH * IW * MB_BLOCK + mb * IC * ID * IH * IW
+ sp_beg * MB_BLOCK * IC_BLOCK src += s_off diff_dst += s_off#if FUSE_BN_RELU == 1
ws += s_off#endif
VECT_FLOAT_T diff_gamma0 = 0.0f, diff_beta0 = 0.0f VECT_FLOAT_T diff_gamma1 = 0.0f, diff_beta1 = 0.0f float v_mean = as_float(
intel_sub_group_block_read((const __global uint *)&mean[c]))
for (int sp = sp_beg VECT_FLOAT_T dd0 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&diff_dst[0]))) VECT_FLOAT_T ss0 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&src[0])))#ifdef MB16
VECT_FLOAT_T dd1 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(VECT_BLOCK_READ(
(const __global BLOCK_DATA_T *)&diff_dst[8 * 16]))) VECT_FLOAT_T ss1 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&src[8 * 16])))#endif
#if FUSE_BN_RELU == 1
VECT_INT_T ws0 = VECT_CHAR_TO_INT(AS_VECT_CHAR_T(
VECT_UCHAR_READ((const __global uchar *)&ws[0]))) dd0 = select((VECT_FLOAT_T)0.0f, dd0, ws0)#ifdef MB16
VECT_INT_T ws1 = VECT_CHAR_TO_INT(AS_VECT_CHAR_T(
VECT_UCHAR_READ((const __global uchar *)&ws[8 * 16]))) dd1 = select((VECT_FLOAT_T)0.0f, dd1, ws1)#endif
ws += MB_BLOCK * IC_BLOCK#endif
diff_gamma0 = fma((ss0 - (VECT_FLOAT_T)v_mean), dd0, diff_gamma0) diff_beta0 += dd0#ifdef MB16
diff_gamma1 = fma((ss1 - (VECT_FLOAT_T)v_mean), dd1, diff_gamma1) diff_beta1 += dd1#endif
src += MB_BLOCK * IC_BLOCK diff_dst += MB_BLOCK * IC_BLOCK }
#ifdef MB16
float v_diff_gamma = 0.0f, v_diff_beta = 0.0 for (int i = 0 v_diff_gamma += diff_gamma0[i] + diff_gamma1[i] v_diff_beta += diff_beta0[i] + diff_beta1[i] }
#else
float v_diff_gamma = diff_gamma0, v_diff_beta = diff_beta0#endif
intel_sub_group_block_write(
(__global uint *)&reduce_temp[mb_sp_idx * IC + c],
as_uint(v_diff_gamma)) intel_sub_group_block_write(
(__global uint *)&reduce_temp[REDUCE_STAT_NBLOCKS * IC
+ mb_sp_idx * IC + c],
as_uint(v_diff_beta))}
NAMED_KERNEL_ATTR(REDUCE)
__kernel void simple_reduce_stats(__global float *reduce_temp,
__global float *diff_scale, __global float *diff_shift,
__global float *variance, float eps) {
const int c = GWS_GET_REDUCE_STAT_IC() reduce_temp += c float diff_gamma = 0.0f, diff_beta = 0.0f for (int i = 0 diff_gamma += reduce_temp[i * IC] diff_beta += reduce_temp[REDUCE_STAT_NBLOCKS * IC + i * IC] }
float sqrt_variance = 1.0f / sqrt(variance[c] + eps)
diff_scale[c] = diff_gamma * sqrt_variance#if USE_SHIFT == 1
diff_shift[c] = diff_beta#else
// When USE_SHIFT == 0, `diff_shift` is a second part of reduce_temp
diff_shift[REDUCE_STAT_NBLOCKS * IC + c] = diff_beta#endif
}
KERNEL_ATTR
__kernel void simple_bnorm_bwd(__global DATA_T *src, __global float *mean,
__global float *variance, __global DATA_T *diff_dst,
__global float *scale, __global char *ws, __global DATA_T *diff_src,
__global float *diff_scale, __global float *diff_shift, float eps,
__global DATA_T *diff_src_add) {
const int n = GWS_GET_MB() const int c = GWS_GET_IC() const int d = GWS_GET_ID() const int h = GWS_GET_IH() const int w = GWS_GET_IW()
#if USE_SCALE == 1
float gamma = as_float(
intel_sub_group_block_read((const __global uint *)&scale[c]))#else
float gamma = 1.0f#endif
float v_variance = as_float(
intel_sub_group_block_read((const __global uint *)&variance[c])) float sqrt_variance = 1.0f / sqrt(v_variance + eps)
#if CALCULATE_STATS == 1
float v_mean = as_float(
intel_sub_group_block_read((const __global uint *)&mean[c])) float diff_gamma = as_float(
intel_sub_group_block_read((const __global uint *)&diff_scale[c]))#if USE_SHIFT == 1
float diff_beta = as_float(
intel_sub_group_block_read((const __global uint *)&diff_shift[c]))#else
float diff_beta = as_float(intel_sub_group_block_read(
(const __global uint *)&diff_shift[REDUCE_STAT_NBLOCKS * IC + c]))#endif // #if USE_SHIFT == 1
#endif
const uint d_off = SRC_OFF(n, c, d, h, w) diff_src += d_off#if FUSE_BN_ADD_RELU == 1
diff_src_add += d_off#endif
diff_dst += d_off src += d_off
VECT_FLOAT_T blockD0 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&diff_dst[0])))#ifdef MB16
VECT_FLOAT_T blockD1 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(VECT_BLOCK_READ(
(const __global BLOCK_DATA_T *)&diff_dst[8 * IC_BLOCK])))#endif
#if FUSE_BN_RELU == 1
ws += d_off VECT_INT_T blockWS0 = VECT_CHAR_TO_INT(
AS_VECT_CHAR_T(VECT_UCHAR_READ((const __global uchar *)&ws[0]))) blockD0 = select((VECT_FLOAT_T)0.0f, blockD0, blockWS0)#if FUSE_BN_ADD_RELU == 1
VECT_BLOCK_WRITE((__global BLOCK_DATA_T *)&diff_src_add[0],
AS_VECT_BLOCK_DATA_T(CONVERT_VECTOR_DATA_T(blockD0)))#endif
#ifdef MB16
VECT_INT_T blockWS1 = VECT_CHAR_TO_INT(AS_VECT_CHAR_T(
VECT_UCHAR_READ((const __global uchar *)&ws[8 * IC_BLOCK]))) blockD1 = select((VECT_FLOAT_T)0.0f, blockD1, blockWS1)#if FUSE_BN_ADD_RELU == 1
VECT_BLOCK_WRITE((__global BLOCK_DATA_T *)&diff_src_add[8 * 16],
AS_VECT_BLOCK_DATA_T(CONVERT_VECTOR_DATA_T(blockD1)))#endif
#endif
#endif
gamma *= sqrt_variance
#if CALCULATE_STATS == 1
diff_gamma *= sqrt_variance diff_gamma /= (MB * ID * IH * IW) diff_beta /= (MB * ID * IH * IW)
VECT_FLOAT_T blockS0 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(
VECT_BLOCK_READ((const __global BLOCK_DATA_T *)&src[0]))) blockD0 -= fma((VECT_FLOAT_T)diff_gamma, (blockS0 - (VECT_FLOAT_T)v_mean),
(VECT_FLOAT_T)diff_beta)#ifdef MB16
VECT_FLOAT_T blockS1 = CONVERT_VECT_FLOAT_T(AS_VECT_DATA_T(VECT_BLOCK_READ(
(const __global BLOCK_DATA_T *)&src[8 * IC_BLOCK]))) blockD1 -= fma((VECT_FLOAT_T)diff_gamma, (blockS1 - (VECT_FLOAT_T)v_mean),
(VECT_FLOAT_T)diff_beta)#endif
#endif
blockD0 *= gamma VECT_BLOCK_WRITE((__global BLOCK_DATA_T *)&diff_src[0],
AS_VECT_BLOCK_DATA_T(CONVERT_VECTOR_DATA_T(blockD0)))#ifdef MB16
blockD1 *= gamma VECT_BLOCK_WRITE((__global BLOCK_DATA_T *)&diff_src[8 * 16],
AS_VECT_BLOCK_DATA_T(CONVERT_VECTOR_DATA_T(blockD1)))#endif
}
#endif