diff options
Diffstat (limited to 'thirdparty/oidn/mkl-dnn/src/common/pooling.cpp')
| -rw-r--r-- | thirdparty/oidn/mkl-dnn/src/common/pooling.cpp | 114 |
1 files changed, 114 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/common/pooling.cpp b/thirdparty/oidn/mkl-dnn/src/common/pooling.cpp new file mode 100644 index 0000000000..be96e654ff --- /dev/null +++ b/thirdparty/oidn/mkl-dnn/src/common/pooling.cpp @@ -0,0 +1,114 @@ +/******************************************************************************* +* Copyright 2016-2018 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 <assert.h> +#include "mkldnn.h" + +#include "c_types_map.hpp" +#include "type_helpers.hpp" +#include "utils.hpp" + +using namespace mkldnn::impl; +using namespace mkldnn::impl::utils; +using namespace mkldnn::impl::status; +using namespace mkldnn::impl::prop_kind; +using namespace mkldnn::impl::alg_kind; +using namespace mkldnn::impl::types; + +namespace { +status_t pooling_desc_init(pooling_desc_t *pool_desc, + prop_kind_t prop_kind, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *dst_desc, + const dims_t strides, const dims_t kernel, const dims_t padding_l, + const dims_t padding_r, padding_kind_t padding_kind) { + bool args_ok = true + && !any_null(pool_desc, src_desc, dst_desc, strides, kernel, padding_l) + && one_of(alg_kind, pooling_max, + pooling_avg_include_padding, + pooling_avg_exclude_padding) + && one_of(padding_kind, padding_kind::padding_zero); + if (!args_ok) return invalid_arguments; + + if (padding_r == nullptr) padding_r = padding_l; + + auto pd = pooling_desc_t(); + pd.primitive_kind = primitive_kind::pooling; + pd.prop_kind = prop_kind; + pd.alg_kind = alg_kind; + pd.src_desc.ndims = src_desc->ndims; + + const bool is_fwd = one_of(prop_kind, forward_training, forward_inference); + + pd.diff_src_desc = pd.src_desc = zero_md(); + pd.diff_dst_desc = pd.dst_desc = zero_md(); + + (is_fwd ? pd.src_desc : pd.diff_src_desc) = *src_desc; + (is_fwd ? pd.dst_desc : pd.diff_dst_desc) = *dst_desc; + + int sp_dims = src_desc->ndims - 2; + utils::array_copy(pd.strides, strides, sp_dims); + utils::array_copy(pd.kernel, kernel, sp_dims); + utils::array_copy(pd.padding[0], padding_l, sp_dims); + utils::array_copy(pd.padding[1], padding_r, sp_dims); + + pd.padding_kind = padding_kind; + if (one_of(alg_kind, pooling_max, pooling_avg_include_padding, + pooling_avg_exclude_padding)) { + pd.accum_data_type = types::default_accum_data_type( + src_desc->data_type, dst_desc->data_type); + } else { + pd.accum_data_type = dst_desc->data_type; + } + + bool consistency = true + && utils::one_of(src_desc->ndims, 4, 5) + && utils::one_of(dst_desc->ndims, 4, 5) + && src_desc->dims[0] == dst_desc->dims[0] + && src_desc->dims[1] == dst_desc->dims[1]; + for (int i = 2; i < src_desc->ndims; ++i) + consistency = consistency && ( + (src_desc->dims[i] - kernel[i - 2] + padding_l[i - 2] + + padding_r[i - 2]) / strides[i - 2] + 1 + == dst_desc->dims[i]); + if (!consistency) return invalid_arguments; + + *pool_desc = pd; + return success; +} +} + +status_t mkldnn_pooling_forward_desc_init(pooling_desc_t *pool_desc, + prop_kind_t prop_kind, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *dst_desc, + const dims_t strides, const dims_t kernel, const dims_t padding_l, + const dims_t padding_r, padding_kind_t padding_kind) { + if (!one_of(prop_kind, forward_training, forward_inference)) + return invalid_arguments; + return pooling_desc_init(pool_desc, prop_kind, alg_kind, src_desc, + dst_desc, strides, kernel, padding_l, padding_r, padding_kind); +} + +status_t mkldnn_pooling_backward_desc_init(pooling_desc_t *pool_desc, + alg_kind_t alg_kind, const memory_desc_t *diff_src_desc, + const memory_desc_t *diff_dst_desc, const dims_t strides, + const dims_t kernel, const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + return pooling_desc_init(pool_desc, prop_kind::backward_data, alg_kind, + diff_src_desc, diff_dst_desc, strides, kernel, padding_l, + padding_r, padding_kind); +} + +// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s |