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-rw-r--r--thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp199
1 files changed, 199 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp b/thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp
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+/*******************************************************************************
+* Copyright 2018 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 "c_types_map.hpp"
+#include "type_helpers.hpp"
+#include "mkldnn_thread.hpp"
+#include "mkldnn_traits.hpp"
+#include "math_utils.hpp"
+
+#include "ref_deconvolution.hpp"
+
+namespace mkldnn {
+namespace impl {
+namespace cpu {
+
+void ref_deconvolution_fwd_t::compute_fwd_bias(const data_t *bias,
+ data_t *dst) const {
+ const memory_desc_wrapper dst_d(pd()->dst_md());
+
+ const int G = pd()->G();
+ const int MB = pd()->MB();
+ const int OH = pd()->OH();
+ const int OW = pd()->OW();
+ const int OD = pd()->OD();
+ const int OC = pd()->OC() / G;
+ const int ndims = pd()->desc()->src_desc.ndims;
+
+ parallel_nd(MB, G, OC, OD, OH, OW,
+ [&](int mb, int g, int oc, int od, int oh, int ow) {
+ auto b = bias[g * OC + oc];
+ switch (ndims) {
+ case 5: dst[dst_d.off(mb, g * OC + oc, od, oh, ow)] += b; break;
+ case 4: dst[dst_d.off(mb, g * OC + oc, oh, ow)] += b; break;
+ case 3: dst[dst_d.off(mb, g * OC + oc, ow)] += b; break;
+ default: assert(!"invalid dimension size");
+ }
+ });
+}
+
+void ref_deconvolution_fwd_t::compute_fwd_bias_ncdhw(const data_t *bias,
+ data_t *dst) const {
+ const memory_desc_wrapper dst_d(pd()->dst_md());
+
+ const int MB = pd()->MB();
+ const int OC = pd()->OC();
+ const int SP = pd()->OW()*pd()->OH()*pd()->OD();
+
+ parallel_nd(MB, OC, [&](int mb, int oc) {
+ PRAGMA_OMP_SIMD()
+ for (int sp = 0; sp < SP; ++sp) {
+ auto offset = (size_t)(mb * OC + oc) * SP + sp;
+ dst[offset] += bias[oc];
+ }
+ });
+}
+
+template <int blksize>
+void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc(const data_t *bias,
+ data_t *dst) const {
+ const memory_desc_wrapper dst_d(pd()->dst_md());
+
+ const int MB = pd()->MB();
+ const int OC = pd()->OC();
+ const int SP = pd()->OW() * pd()->OH() * pd()->OD();
+
+ const ptrdiff_t stride_mb = dst_d.blocking_desc().strides[0];
+
+ parallel_nd(MB, utils::div_up(OC, blksize), SP,
+ [&](int mb, int oc_blk, int sp) {
+ int oc = oc_blk * blksize;
+ auto offset = mb * stride_mb + oc * SP + sp * blksize;
+ const int blk = nstl::min(blksize, OC - oc);
+
+ PRAGMA_OMP_SIMD()
+ for (int i = 0; i < blk; ++i)
+ dst[offset + i] += bias[oc + i];
+ });
+}
+
+void ref_deconvolution_bwd_weights_t::compute_bwd_bias(const data_t *diff_dst,
+ data_t *diff_bias) const {
+ const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
+
+ const int G = pd()->G();
+ const int MB = pd()->MB();
+ const int OH = pd()->OH();
+ const int OW = pd()->OW();
+ const int OC = pd()->OC() / G;
+ const int OD = pd()->OD();
+ const int ndims = pd()->desc()->src_desc.ndims;
+
+ parallel_nd(G, OC, [&](int g, int oc) {
+ data_t db = 0;
+ for (int mb = 0; mb < MB; ++mb) {
+ for (int od = 0; od < OD; ++od) {
+ for (int oh = 0; oh < OH; ++oh) {
+ for (int ow = 0; ow < OW; ++ow) {
+ switch (ndims) {
+ case 5:
+ db += diff_dst[diff_dst_d.off(
+ mb, g * OC + oc, od, oh, ow)];
+ break;
+ case 4:
+ db += diff_dst[diff_dst_d.off(
+ mb, g * OC + oc, oh, ow)];
+ break;
+ case 3:
+ db += diff_dst[diff_dst_d.off(mb, g * OC + oc, ow)];
+ break;
+ default: assert(!"invalid dimension size");
+ }
+ }
+ }
+ }
+ }
+ diff_bias[g * OC + oc] = db;
+ });
+}
+
+void ref_deconvolution_bwd_weights_t::compute_bwd_bias_ncdhw(
+ const data_t *diff_dst, data_t *diff_bias) const {
+ const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
+
+ const int OC = pd()->OC();
+ const int MB = pd()->MB();
+ const int SP = pd()->OH()*pd()->OW()*pd()->OD();
+
+ parallel_nd(OC, [&](int oc) {
+ data_t db = 0;
+ for (int mb = 0; mb < MB; ++mb) {
+ PRAGMA_OMP_SIMD()
+ for (int sp = 0; sp < SP; ++sp) {
+ auto offset = (size_t)(mb * OC + oc) * SP + sp;
+ db += diff_dst[offset];
+ }
+ }
+ diff_bias[oc] = db;
+ });
+}
+
+template <int blksize>
+void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc(
+ const data_t *diff_dst, data_t *diff_bias) const {
+ const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
+
+ const int OC = pd()->OC();
+ const int MB = pd()->MB();
+ const int SP = pd()->OH() * pd()->OW() * pd()->OD();
+
+ const ptrdiff_t stride_mb = diff_dst_d.blocking_desc().strides[0];
+
+ parallel_nd(utils::div_up(OC, blksize), [&](int ocb) {
+ data_t db[blksize] = {0};
+
+ for (int mb = 0; mb < MB; ++mb) {
+ for (int sp = 0; sp < SP; ++sp) {
+ auto offset = mb * stride_mb + (ocb * SP + sp) * blksize;
+
+ PRAGMA_OMP_SIMD()
+ for (int i = 0; i < blksize; ++i)
+ db[i] += diff_dst[offset+i];
+ }
+ }
+
+ const int blk = nstl::min(blksize, OC - ocb * blksize);
+
+ PRAGMA_OMP_SIMD()
+ for (int i = 0; i < blk; ++i)
+ diff_bias[ocb * blksize + i] = db[i];
+ });
+}
+
+template void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc<8>(
+ const data_t *diff_dst, data_t *diff_bias) const;
+template void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc<16>(
+ const data_t *diff_dst, data_t *diff_bias) const;
+template void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc<8>(
+ const data_t *diff_dst, data_t *diff_bias) const;
+template void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc<16>(
+ const data_t *diff_dst, data_t *diff_bias) const;
+
+}
+}
+}
+
+// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-22 01:47:14 +0000