257 lines
10 KiB
C++
257 lines
10 KiB
C++
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// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#include "layer/rnn.h"
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#include "testutil.h"
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static int test_rnn(const ncnn::Mat& a, int outch, int direction)
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{
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int input_size = a.w;
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int num_directions = direction == 2 ? 2 : 1;
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ncnn::ParamDict pd;
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pd.set(0, outch);
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pd.set(1, outch * input_size * num_directions);
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pd.set(2, direction);
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std::vector<ncnn::Mat> weights(3);
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weights[0] = RandomMat(outch * input_size * num_directions);
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weights[1] = RandomMat(outch * num_directions);
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weights[2] = RandomMat(outch * outch * num_directions);
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int ret = test_layer<ncnn::RNN>("RNN", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_rnn failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
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}
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return ret;
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}
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int test_rnn_layer_with_hidden(const ncnn::Mat& a, int outch, int direction)
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{
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int input_size = a.w;
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int num_directions = direction == 2 ? 2 : 1;
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ncnn::ParamDict pd;
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pd.set(0, outch);
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pd.set(1, outch * input_size * num_directions);
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pd.set(2, direction);
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std::vector<ncnn::Mat> weights(3);
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weights[0] = RandomMat(outch * input_size * num_directions);
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weights[1] = RandomMat(outch * num_directions);
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weights[2] = RandomMat(outch * outch * num_directions);
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// initial hidden state
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ncnn::Mat hidden = RandomMat(outch, num_directions);
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std::vector<ncnn::Mat> as(2);
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as[0] = a;
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as[1] = hidden;
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int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 2);
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if (ret != 0)
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{
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fprintf(stderr, "test_rnn_layer_with_hidden failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
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}
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return ret;
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}
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int test_rnn_layer_with_hidden_input(const ncnn::Mat& a, int outch, int direction)
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{
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int input_size = a.w;
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int num_directions = direction == 2 ? 2 : 1;
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ncnn::ParamDict pd;
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pd.set(0, outch);
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pd.set(1, outch * input_size * num_directions);
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pd.set(2, direction);
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std::vector<ncnn::Mat> weights(3);
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weights[0] = RandomMat(outch * input_size * num_directions);
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weights[1] = RandomMat(outch * num_directions);
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weights[2] = RandomMat(outch * outch * num_directions);
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// initial hidden state
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ncnn::Mat hidden = RandomMat(outch, num_directions);
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std::vector<ncnn::Mat> as(2);
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as[0] = a;
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as[1] = hidden;
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int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 1);
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if (ret != 0)
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{
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fprintf(stderr, "test_rnn_layer_with_hidden_input failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
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}
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return ret;
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}
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int test_rnn_layer_with_hidden_output(const ncnn::Mat& a, int outch, int direction)
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{
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int input_size = a.w;
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int num_directions = direction == 2 ? 2 : 1;
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ncnn::ParamDict pd;
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pd.set(0, outch);
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pd.set(1, outch * input_size * num_directions);
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pd.set(2, direction);
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std::vector<ncnn::Mat> weights(3);
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weights[0] = RandomMat(outch * input_size * num_directions);
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weights[1] = RandomMat(outch * num_directions);
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weights[2] = RandomMat(outch * outch * num_directions);
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std::vector<ncnn::Mat> as(1);
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as[0] = a;
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int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 2);
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if (ret != 0)
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{
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fprintf(stderr, "test_rnn_layer_with_hidden_output failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
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}
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return ret;
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}
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static int test_rnn_0()
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{
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return 0
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|| test_rnn(RandomMat(4, 1), 2, 2)
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|| test_rnn(RandomMat(8, 2), 2, 2)
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|| test_rnn(RandomMat(16, 8), 7, 2)
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|| test_rnn(RandomMat(17, 8), 8, 2)
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|| test_rnn(RandomMat(19, 15), 8, 2)
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|| test_rnn(RandomMat(5, 16), 16, 2)
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|| test_rnn(RandomMat(3, 16), 8, 2)
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|| test_rnn(RandomMat(8, 16), 16, 2)
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|| test_rnn(RandomMat(2, 5), 17, 2);
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}
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static int test_rnn_1()
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{
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return 0
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|| test_rnn_layer_with_hidden(RandomMat(4, 4), 1, 2)
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|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 2)
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|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 2)
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|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 2)
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|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 2)
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|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 2)
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|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 2)
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|| test_rnn_layer_with_hidden(RandomMat(2, 5), 99, 2)
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|| test_rnn_layer_with_hidden(RandomMat(4, 4), 1, 1)
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|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 1)
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|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 1)
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|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 1)
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|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 1)
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|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 1)
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|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 1)
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|| test_rnn_layer_with_hidden(RandomMat(2, 5), 99, 1)
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|| test_rnn_layer_with_hidden(RandomMat(4, 2), 1, 0)
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|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 0)
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|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 0)
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|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 0)
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|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 0)
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|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 0)
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|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 0)
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|| test_rnn_layer_with_hidden(RandomMat(2, 5), 17, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(4, 4), 1, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 99, 2)
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|| test_rnn_layer_with_hidden_input(RandomMat(4, 4), 1, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 99, 1)
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|| test_rnn_layer_with_hidden_input(RandomMat(4, 2), 1, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 0)
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|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 17, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(4, 4), 1, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 99, 2)
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|| test_rnn_layer_with_hidden_output(RandomMat(4, 4), 1, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 99, 1)
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|| test_rnn_layer_with_hidden_output(RandomMat(4, 2), 1, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 0)
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|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 17, 0);
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}
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static int test_rnn_2()
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{
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return 0
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|| test_rnn(RandomMat(4, 1), 1, 0)
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|| test_rnn(RandomMat(8, 2), 2, 0)
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|| test_rnn(RandomMat(16, 8), 7, 0)
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|| test_rnn(RandomMat(17, 8), 8, 0)
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|| test_rnn(RandomMat(19, 15), 8, 0)
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|| test_rnn(RandomMat(5, 16), 16, 0)
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|| test_rnn(RandomMat(3, 16), 8, 0)
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|| test_rnn(RandomMat(8, 16), 16, 0)
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|| test_rnn(RandomMat(2, 5), 17, 0);
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}
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static int test_rnn_3()
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{
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return 0
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|| test_rnn(RandomMat(4, 1), 1, 1)
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|| test_rnn(RandomMat(8, 2), 2, 1)
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|| test_rnn(RandomMat(16, 8), 7, 1)
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|| test_rnn(RandomMat(17, 8), 8, 1)
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|| test_rnn(RandomMat(19, 15), 8, 1)
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|| test_rnn(RandomMat(5, 16), 16, 1)
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|| test_rnn(RandomMat(3, 16), 8, 1)
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|| test_rnn(RandomMat(8, 16), 16, 1)
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|| test_rnn(RandomMat(2, 5), 17, 1);
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}
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int main()
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{
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SRAND(7767517);
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return test_rnn_0() || test_rnn_1() || test_rnn_2() || test_rnn_3();
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}
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