1 files changed, 0 insertions, 113 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/rnn/cell_rnn.cpp b/thirdparty/oidn/mkl-dnn/src/cpu/rnn/cell_rnn.cpp
deleted file mode 100644
index 4536e8dfad..0000000000
--- a/thirdparty/oidn/mkl-dnn/src/cpu/rnn/cell_rnn.cpp
+++ /dev/null
@@ -1,113 +0,0 @@
-/*******************************************************************************
-* 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.
-*******************************************************************************/
-
-/*
- * Cell execution of Vanilla RNN
- */
-
-#include "math_utils.hpp"
-#include "mkldnn_thread.hpp"
-
-#include "ref_rnn.hpp"
-
-namespace mkldnn {
-namespace impl {
-namespace cpu {
-
-using namespace mkldnn::impl::utils;
-using namespace mkldnn::impl::math;
-using namespace rnn_utils;
-
-template <>
-float activation<alg_kind::eltwise_relu, prop_kind::forward>(
-        float dd, float s, float alpha, float cliping) {
-    return relu_fwd<float>(s, alpha);
-}
-
-template <>
-float activation<alg_kind::eltwise_relu, prop_kind::backward>(
-        float dd, float s, float alpha, float cliping) {
-    return relu_bwd<float>(dd, s, alpha);
-}
-
-template <>
-float activation<alg_kind::eltwise_tanh, prop_kind::forward>(
-        float dd, float s, float alpha, float cliping) {
-    return tanh_fwd<float>(s);
-}
-
-template <>
-float activation<alg_kind::eltwise_tanh, prop_kind::backward>(
-        float dd, float s, float alpha, float cliping) {
-    return dd * one_m_square<float>(s);
-}
-
-template <>
-float activation<alg_kind::eltwise_logistic, prop_kind::forward>(
-        float dd, float s, float alpha, float cliping) {
-    return logistic_fwd<float>(s);
-}
-
-template <>
-float activation<alg_kind::eltwise_logistic, prop_kind::backward>(
-        float dd, float s, float alpha, float cliping) {
-    return dd * x_m_square<float>(s);
-}
-
-template <>
-rnn_elemwise_sig(ref_rnn_fwd_f32_t::rnn_elemwise) {
-    ws_gates_aoc_t ws_gates(rnn, ws_gates_);
-    bias_aoc_t bias(rnn, bias_);
-    ws_states_aoc_t states_t_l(rnn, states_t_l_);
-    ws_states_aoc_t states_tm1_l(rnn, states_tm1_l_);
-
-    parallel_nd(rnn.mb, [&](int i) {
-        for (int j = 0; j < rnn.dic; j++) {
-            const float h
-                    = activation_func(0, ws_gates(i, 0, j) + bias(0, j), 0, 0);
-            ws_gates(i, 0, j) = states_t_l(i, j) = h;
-        }
-    });
-}
-
-template <>
-rnn_elemwise_sig(ref_rnn_fwd_u8s8_t::rnn_elemwise) {
-    assert(!"VANILLA RNN int8 is not supported");
-}
-
-template <>
-rnn_elemwise_sig(ref_rnn_bwd_f32_t::rnn_elemwise) {
-    ws_gates_aoc_t ws_gates(rnn, ws_gates_);
-    bias_aoc_t bias(rnn, bias_);
-    ws_states_aoc_t states_t_l(rnn, states_t_l_);
-    ws_states_aoc_t states_tm1_l(rnn, states_tm1_l_);
-    ws_diff_states_aoc_t diff_states_t_l(rnn, diff_states_t_l_);
-    ws_diff_states_aoc_t diff_states_tp1_l(rnn, diff_states_tp1_l_);
-    ws_diff_states_aoc_t diff_states_t_lp1(rnn, diff_states_t_lp1_);
-
-    parallel_nd(rnn.mb, [&](int i) {
-        for (int j = 0; j < rnn.dic; ++j) {
-            const float dH = diff_states_t_lp1(rnn.n_states, i, j)
-                    + diff_states_tp1_l(0, i, j);
-            auto g = ws_gates(i, 0, j);
-            ws_gates(i, 0, j) = activation_func(dH, g, 0, 0);
-        }
-    });
-}
-
-}
-}
-}