diff options
Diffstat (limited to 'thirdparty/oidn/mkl-dnn/src/common/convolution.cpp')
| -rw-r--r-- | thirdparty/oidn/mkl-dnn/src/common/convolution.cpp | 200 |
1 files changed, 200 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/common/convolution.cpp b/thirdparty/oidn/mkl-dnn/src/common/convolution.cpp new file mode 100644 index 0000000000..0c5c02bcd1 --- /dev/null +++ b/thirdparty/oidn/mkl-dnn/src/common/convolution.cpp @@ -0,0 +1,200 @@ +/******************************************************************************* +* 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 mkldnn { +namespace impl { +status_t conv_desc_init(convolution_desc_t *conv_desc, + prop_kind_t prop_kind, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *weights_desc, + const memory_desc_t *bias_desc, const memory_desc_t *dst_desc, + const dims_t strides, const dims_t dilates, + const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + bool args_ok = true + && !any_null(conv_desc, src_desc, weights_desc, dst_desc, strides, + padding_l) + && one_of(alg_kind, convolution_auto, convolution_direct, convolution_winograd) + && one_of(padding_kind, padding_kind::padding_zero); + if (!args_ok) return invalid_arguments; + + if (padding_r == nullptr) padding_r = padding_l; + + auto cd = convolution_desc_t(); + cd.primitive_kind = primitive_kind::convolution; + cd.prop_kind = prop_kind; + cd.alg_kind = alg_kind; + + cd.diff_src_desc = cd.src_desc = zero_md(); + cd.diff_dst_desc = cd.dst_desc = zero_md(); + cd.diff_weights_desc = cd.weights_desc = zero_md(); + cd.diff_bias_desc = cd.bias_desc = zero_md(); + + const bool is_fwd = one_of(prop_kind, forward_training, forward_inference); + const bool with_bias = + bias_desc && bias_desc->format_kind != format_kind::undef; + const bool with_groups = weights_desc->ndims == src_desc->ndims + 1; + + (prop_kind == backward_data ? cd.diff_src_desc : cd.src_desc) = *src_desc; + (is_fwd ? cd.dst_desc : cd.diff_dst_desc) = *dst_desc; + (prop_kind == backward_weights ? cd.diff_weights_desc : cd.weights_desc) = + *weights_desc; + if (with_bias) + (prop_kind == backward_weights ? cd.diff_bias_desc : cd.bias_desc) = + *bias_desc; + + int sp_dims = src_desc->ndims - 2; + utils::array_copy(cd.strides, strides, sp_dims); + utils::array_copy(cd.padding[0], padding_l, sp_dims); + utils::array_copy(cd.padding[1], padding_r, sp_dims); + if (dilates) + utils::array_copy(cd.dilates, dilates, sp_dims); + else + utils::array_set(cd.dilates, 0, sp_dims); + + cd.padding_kind = padding_kind; + cd.accum_data_type = types::default_accum_data_type(src_desc->data_type, + weights_desc->data_type, dst_desc->data_type, prop_kind); + + const int g = with_groups ? weights_desc->dims[0] : 1; + const int bias_dim = prop_kind == backward_data + ? src_desc->dims[1] + : dst_desc->dims[1]; + + bool consistency = true + && memory_desc_wrapper(weights_desc).nelems() + && src_desc->ndims == dst_desc->ndims + && utils::one_of(src_desc->ndims, 3, 4, 5) + && utils::one_of(weights_desc->ndims, src_desc->ndims, + src_desc->ndims + 1) + && (with_bias ? bias_desc->ndims == 1 : true) + && (with_bias ? bias_desc->dims[0] == bias_dim : true) + && src_desc->dims[0] == dst_desc->dims[0] + && src_desc->dims[1] == g * weights_desc->dims[with_groups + 1] + && dst_desc->dims[1] == g * weights_desc->dims[with_groups + 0]; + for (int i = 2; i < src_desc->ndims; ++i) + { + int src = src_desc->dims[i]; + int ker = weights_desc->dims[with_groups + i]; + int dil = cd.dilates[i - 2]; + int pad_l = padding_l[i - 2]; + int pad_r = padding_r[i - 2]; + int str = strides[i - 2]; + int dst = dst_desc->dims[i]; + int ker_range = 1 + (ker - 1) * (dil + 1); + + if (str < 1) return invalid_arguments; + consistency = consistency + && dil >= 0 + && pad_l >= 0 + && pad_r + str > 0 + && (src - ker_range + pad_l + pad_r) / str + 1 == dst; + } + if (!consistency) return invalid_arguments; + + *conv_desc = cd; + return success; +} +} +} + +status_t mkldnn_convolution_forward_desc_init(convolution_desc_t *conv_desc, + prop_kind_t prop_kind, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *weights_desc, + const memory_desc_t *bias_desc, const memory_desc_t *dst_desc, + const dims_t strides, 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 mkldnn::impl::conv_desc_init(conv_desc, prop_kind, alg_kind, src_desc, + weights_desc, bias_desc, dst_desc, strides, nullptr, + padding_l, padding_r, padding_kind); +} + +status_t mkldnn_dilated_convolution_forward_desc_init( + convolution_desc_t *conv_desc, prop_kind_t prop_kind, + alg_kind_t alg_kind, const memory_desc_t *src_desc, + const memory_desc_t *weights_desc, const memory_desc_t *bias_desc, + const memory_desc_t *dst_desc, const dims_t strides, + const dims_t dilates, 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 mkldnn::impl::conv_desc_init(conv_desc, prop_kind, alg_kind, src_desc, + weights_desc, bias_desc, dst_desc, strides, dilates, + padding_l, padding_r, padding_kind); +} + +status_t mkldnn_convolution_backward_data_desc_init( + convolution_desc_t *conv_desc, alg_kind_t alg_kind, + const memory_desc_t *diff_src_desc, const memory_desc_t *weights_desc, + const memory_desc_t *diff_dst_desc, const dims_t strides, + const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + return mkldnn::impl::conv_desc_init(conv_desc, backward_data, alg_kind, diff_src_desc, + weights_desc, nullptr, diff_dst_desc, strides, nullptr, + padding_l, padding_r, padding_kind); +} + +status_t mkldnn_dilated_convolution_backward_data_desc_init( + convolution_desc_t *conv_desc, alg_kind_t alg_kind, + const memory_desc_t *diff_src_desc, const memory_desc_t *weights_desc, + const memory_desc_t *diff_dst_desc, const dims_t strides, + const dims_t dilates, const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + return mkldnn::impl::conv_desc_init(conv_desc, backward_data, alg_kind, diff_src_desc, + weights_desc, nullptr, diff_dst_desc, strides, dilates, + padding_l, padding_r, padding_kind); +} + +status_t mkldnn_convolution_backward_weights_desc_init( + convolution_desc_t *conv_desc, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *diff_weights_desc, + const memory_desc_t *diff_bias_desc, + const memory_desc_t *diff_dst_desc, const dims_t strides, + const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + return mkldnn::impl::conv_desc_init(conv_desc, backward_weights, alg_kind, src_desc, + diff_weights_desc, diff_bias_desc, diff_dst_desc, strides, + nullptr, padding_l, padding_r, padding_kind); +} + +status_t mkldnn_dilated_convolution_backward_weights_desc_init( + convolution_desc_t *conv_desc, alg_kind_t alg_kind, + const memory_desc_t *src_desc, const memory_desc_t *diff_weights_desc, + const memory_desc_t *diff_bias_desc, + const memory_desc_t *diff_dst_desc, const dims_t strides, + const dims_t dilates, const dims_t padding_l, const dims_t padding_r, + padding_kind_t padding_kind) { + return mkldnn::impl::conv_desc_init(conv_desc, backward_weights, alg_kind, src_desc, + diff_weights_desc, diff_bias_desc, diff_dst_desc, strides, + dilates, padding_l, padding_r, padding_kind); +} + +// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s |