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-rw-r--r--thirdparty/oidn/mkl-dnn/src/common/lrn.cpp91
1 files changed, 91 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/common/lrn.cpp b/thirdparty/oidn/mkl-dnn/src/common/lrn.cpp
new file mode 100644
index 0000000000..fcf18b556f
--- /dev/null
+++ b/thirdparty/oidn/mkl-dnn/src/common/lrn.cpp
@@ -0,0 +1,91 @@
+/*******************************************************************************
+* 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 lrn_desc_init(lrn_desc_t *lrn_desc,
+ prop_kind_t prop_kind, alg_kind_t alg_kind,
+ const memory_desc_t *data_desc, const memory_desc_t *diff_data_desc,
+ dim_t local_size, float alpha, float beta, float k) {
+ bool args_ok = true
+ && !any_null(lrn_desc, data_desc)
+ && one_of(alg_kind, lrn_within_channel, lrn_across_channels)
+ && one_of(prop_kind, forward_training, forward_inference, backward_data)
+ && IMPLICATION(prop_kind == backward_data, diff_data_desc != nullptr);
+ if (!args_ok) return invalid_arguments;
+
+ auto ld = lrn_desc_t();
+ ld.primitive_kind = primitive_kind::lrn;
+ ld.prop_kind = prop_kind;
+ ld.alg_kind = alg_kind;
+
+ const bool is_fwd = one_of(prop_kind, forward_training, forward_inference);
+
+ ld.data_desc = *data_desc;
+ if (!is_fwd)
+ ld.diff_data_desc = *diff_data_desc;
+ else
+ ld.diff_data_desc = zero_md();
+ ld.local_size = local_size;
+ ld.lrn_alpha = alpha;
+ ld.lrn_beta = beta;
+ ld.lrn_k = k;
+
+ bool consistency = true
+ && ld.data_desc.ndims == 4;
+ if (ld.prop_kind == backward_data)
+ consistency = consistency
+ && ld.diff_data_desc.ndims == 4
+ && array_cmp(ld.diff_data_desc.dims, ld.data_desc.dims, 4);
+ if (!consistency) return invalid_arguments;
+
+ *lrn_desc = ld;
+ return success;
+}
+}
+
+status_t mkldnn_lrn_forward_desc_init(lrn_desc_t *lrn_desc,
+ prop_kind_t prop_kind, alg_kind_t alg_kind,
+ const memory_desc_t *data_desc, dim_t local_size, float alpha,
+ float beta, float k) {
+ if (!one_of(prop_kind, forward_training, forward_inference))
+ return invalid_arguments;
+ return lrn_desc_init(lrn_desc, prop_kind, alg_kind, data_desc, nullptr,
+ local_size, alpha, beta, k);
+}
+
+status_t mkldnn_lrn_backward_desc_init(lrn_desc_t *lrn_desc,
+ alg_kind_t alg_kind, const memory_desc_t *data_desc,
+ const memory_desc_t *diff_data_desc, dim_t local_size, float alpha,
+ float beta, float k) {
+ return lrn_desc_init(lrn_desc, backward_data, alg_kind, data_desc,
+ diff_data_desc, local_size, alpha, beta, k);
+}
+
+// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s