1 files changed, 0 insertions, 91 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/simple_sum.cpp b/thirdparty/oidn/mkl-dnn/src/cpu/simple_sum.cpp
deleted file mode 100644
index f0947573a9..0000000000
--- a/thirdparty/oidn/mkl-dnn/src/cpu/simple_sum.cpp
+++ /dev/null
@@ -1,91 +0,0 @@
-/*******************************************************************************
-* Copyright 2017-2018 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 "mkldnn_thread.hpp"
-
-#include "simple_sum.hpp"
-
-namespace mkldnn {
-namespace impl {
-namespace cpu {
-
-template <data_type_t data_type>
-status_t simple_sum_t<data_type>::execute(const exec_ctx_t &ctx) const {
-    auto output = CTX_OUT_MEM(data_t *, MKLDNN_ARG_DST);
-
-    const memory_desc_wrapper o_d(pd()->dst_md());
-    output += o_d.blk_off(0);
-
-    const int num_arrs = pd()->n_inputs();
-    const data_t *input_ptrs[max_num_arrs];
-    const size_t nelems = o_d.nelems();
-
-    for (int a = 0; a < num_arrs; ++a) {
-        const memory_desc_wrapper i_d(pd()->src_md(a));
-        input_ptrs[a] = CTX_IN_MEM(const data_t *, MKLDNN_ARG_MULTIPLE_SRC + a)
-            + i_d.blk_off(0);
-    }
-
-    const size_t block_size = 16 * 1024 / sizeof(data_type);
-    const size_t blocks_number = nelems / block_size;
-    const size_t tail = nelems % block_size;
-
-    const auto scales = pd()->scales();
-    parallel(0, [&](const int ithr, const int nthr) {
-        size_t start{0}, end{0};
-        balance211(blocks_number, nthr, ithr, start, end);
-
-        for (size_t nb = start; nb < end; ++nb) {
-            size_t start_e = nb * block_size;
-            size_t end_e = start_e + block_size;
-
-            PRAGMA_OMP_SIMD()
-            for (size_t e = start_e; e < end_e; e++) {
-                output[e] = data_t(scales[0] * input_ptrs[0][e]);
-            }
-            for (int a = 1; a < num_arrs; a++) {
-                PRAGMA_OMP_SIMD()
-                for (size_t e = start_e; e < end_e; e++) {
-                    output[e] += data_t(scales[a] * input_ptrs[a][e]);
-                }
-            }
-        }
-
-        if (tail != 0 && ithr == nthr - 1) {
-            size_t start_e = nelems - tail;
-            size_t end_e = nelems;
-
-            PRAGMA_OMP_SIMD()
-            for (size_t e = start_e; e < end_e; e++) {
-                output[e] = data_t(scales[0] * input_ptrs[0][e]);
-            }
-            for (int a = 1; a < num_arrs; a++) {
-                PRAGMA_OMP_SIMD()
-                for (size_t e = start_e; e < end_e; e++) {
-                    output[e] += data_t(scales[a] * input_ptrs[a][e]);
-                }
-            }
-        }
-    });
-
-    return status::success;
-}
-
-template struct simple_sum_t<data_type::f32>;
-
-}
-}
-}