- // Tencent is pleased to support the open source community by making ncnn available.
- //
- // Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
- //
- // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
- // in compliance with the License. You may obtain a copy of the License at
- //
- // https://opensource.org/licenses/BSD-3-Clause
- //
- // 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 "layer/lstm.h"
- #include "testutil.h"
-
- static int test_lstm(const ncnn::Mat& a, int outch, int direction, int hidden_size = 0)
- {
- int input_size = a.w;
- int num_directions = direction == 2 ? 2 : 1;
- if (hidden_size == 0)
- hidden_size = outch;
-
- ncnn::ParamDict pd;
- pd.set(0, outch);
- pd.set(1, hidden_size * input_size * 4 * num_directions);
- pd.set(2, direction);
- pd.set(3, hidden_size);
-
- std::vector<ncnn::Mat> weights(hidden_size == 0 ? 3 : 4);
- weights[0] = RandomMat(hidden_size * input_size * 4 * num_directions);
- weights[1] = RandomMat(hidden_size * 4 * num_directions);
- weights[2] = RandomMat(outch * hidden_size * 4 * num_directions);
- if (hidden_size)
- {
- weights[3] = RandomMat(hidden_size * outch * num_directions);
- }
-
- int ret = test_layer<ncnn::LSTM>("LSTM", pd, weights, a);
- if (ret != 0)
- {
- fprintf(stderr, "test_lstm failed a.dims=%d a=(%d %d %d) outch=%d direction=%d hidden_size=%d\n", a.dims, a.w, a.h, a.c, outch, direction, hidden_size);
- }
-
- return ret;
- }
-
- int test_lstm_layer_with_hidden(const ncnn::Mat& a, int outch, int direction, int hidden_size = 0)
- {
- int input_size = a.w;
- int num_directions = direction == 2 ? 2 : 1;
- if (hidden_size == 0)
- hidden_size = outch;
-
- ncnn::ParamDict pd;
- pd.set(0, outch);
- pd.set(1, hidden_size * input_size * 4 * num_directions);
- pd.set(2, direction);
- pd.set(3, hidden_size);
-
- std::vector<ncnn::Mat> weights(hidden_size == 0 ? 3 : 4);
- weights[0] = RandomMat(hidden_size * input_size * 4 * num_directions);
- weights[1] = RandomMat(hidden_size * 4 * num_directions);
- weights[2] = RandomMat(outch * hidden_size * 4 * num_directions);
- if (hidden_size)
- {
- weights[3] = RandomMat(hidden_size * outch * num_directions);
- }
-
- // initial hidden state
- ncnn::Mat hidden = RandomMat(outch, num_directions);
-
- // initial cell state
- ncnn::Mat cell = RandomMat(hidden_size, num_directions);
-
- std::vector<ncnn::Mat> as(3);
- as[0] = a;
- as[1] = hidden;
- as[2] = cell;
-
- int ret = test_layer<ncnn::LSTM>("LSTM", pd, weights, as, 3);
- if (ret != 0)
- {
- fprintf(stderr, "test_lstm_layer_with_hidden failed a.dims=%d a=(%d %d %d) outch=%d direction=%d hidden_size=%d\n", a.dims, a.w, a.h, a.c, outch, direction, hidden_size);
- }
-
- return ret;
- }
-
- int test_lstm_layer_with_hidden_input(const ncnn::Mat& a, int outch, int direction, int hidden_size = 0)
- {
- int input_size = a.w;
- int num_directions = direction == 2 ? 2 : 1;
- if (hidden_size == 0)
- hidden_size = outch;
-
- ncnn::ParamDict pd;
- pd.set(0, outch);
- pd.set(1, hidden_size * input_size * 4 * num_directions);
- pd.set(2, direction);
- pd.set(3, hidden_size);
-
- std::vector<ncnn::Mat> weights(hidden_size == 0 ? 3 : 4);
- weights[0] = RandomMat(hidden_size * input_size * 4 * num_directions);
- weights[1] = RandomMat(hidden_size * 4 * num_directions);
- weights[2] = RandomMat(outch * hidden_size * 4 * num_directions);
- if (hidden_size)
- {
- weights[3] = RandomMat(hidden_size * outch * num_directions);
- }
-
- // initial hidden state
- ncnn::Mat hidden = RandomMat(outch, num_directions);
-
- // initial cell state
- ncnn::Mat cell = RandomMat(hidden_size, num_directions);
-
- std::vector<ncnn::Mat> as(3);
- as[0] = a;
- as[1] = hidden;
- as[2] = cell;
-
- int ret = test_layer<ncnn::LSTM>("LSTM", pd, weights, as, 1);
- if (ret != 0)
- {
- fprintf(stderr, "test_lstm_layer_with_hidden_input failed a.dims=%d a=(%d %d %d) outch=%d direction=%d hidden_size=%d\n", a.dims, a.w, a.h, a.c, outch, direction, hidden_size);
- }
-
- return ret;
- }
-
- int test_lstm_layer_with_hidden_output(const ncnn::Mat& a, int outch, int direction, int hidden_size = 0)
- {
- int input_size = a.w;
- int num_directions = direction == 2 ? 2 : 1;
- if (hidden_size == 0)
- hidden_size = outch;
-
- ncnn::ParamDict pd;
- pd.set(0, outch);
- pd.set(1, hidden_size * input_size * 4 * num_directions);
- pd.set(2, direction);
- pd.set(3, hidden_size);
-
- std::vector<ncnn::Mat> weights(hidden_size == 0 ? 3 : 4);
- weights[0] = RandomMat(hidden_size * input_size * 4 * num_directions);
- weights[1] = RandomMat(hidden_size * 4 * num_directions);
- weights[2] = RandomMat(outch * hidden_size * 4 * num_directions);
- if (hidden_size)
- {
- weights[3] = RandomMat(hidden_size * outch * num_directions);
- }
-
- std::vector<ncnn::Mat> as(1);
- as[0] = a;
-
- int ret = test_layer<ncnn::LSTM>("LSTM", pd, weights, as, 3);
- if (ret != 0)
- {
- fprintf(stderr, "test_lstm_layer_with_hidden_output failed a.dims=%d a=(%d %d %d) outch=%d direction=%d hidden_size=%d\n", a.dims, a.w, a.h, a.c, outch, direction, hidden_size);
- }
-
- return ret;
- }
-
- static int test_lstm_0()
- {
- return 0
- || test_lstm(RandomMat(4, 1), 2, 2)
- || test_lstm(RandomMat(8, 2), 2, 2)
- || test_lstm(RandomMat(16, 8), 7, 2)
- || test_lstm(RandomMat(17, 8), 8, 2)
- || test_lstm(RandomMat(19, 15), 8, 2)
- || test_lstm(RandomMat(5, 16), 16, 2)
- || test_lstm(RandomMat(3, 16), 8, 2)
- || test_lstm(RandomMat(8, 16), 16, 2)
- || test_lstm(RandomMat(2, 5), 17, 2, 15);
- }
-
- static int test_lstm_1()
- {
- return 0
- || test_lstm_layer_with_hidden(RandomMat(4, 4), 1, 2)
- || test_lstm_layer_with_hidden(RandomMat(8, 2), 2, 2)
- || test_lstm_layer_with_hidden(RandomMat(16, 8), 7, 2)
- || test_lstm_layer_with_hidden(RandomMat(17, 8), 8, 2)
- || test_lstm_layer_with_hidden(RandomMat(19, 15), 8, 2)
- || test_lstm_layer_with_hidden(RandomMat(5, 16), 16, 2)
- || test_lstm_layer_with_hidden(RandomMat(3, 16), 8, 2)
- || test_lstm_layer_with_hidden(RandomMat(2, 5), 99, 2, 33)
- || test_lstm_layer_with_hidden(RandomMat(4, 4), 1, 1)
- || test_lstm_layer_with_hidden(RandomMat(8, 2), 2, 1)
- || test_lstm_layer_with_hidden(RandomMat(16, 8), 7, 1)
- || test_lstm_layer_with_hidden(RandomMat(17, 8), 8, 1)
- || test_lstm_layer_with_hidden(RandomMat(19, 15), 8, 1)
- || test_lstm_layer_with_hidden(RandomMat(5, 16), 16, 1)
- || test_lstm_layer_with_hidden(RandomMat(3, 16), 8, 1)
- || test_lstm_layer_with_hidden(RandomMat(2, 5), 99, 1, 33)
- || test_lstm_layer_with_hidden(RandomMat(4, 2), 1, 0)
- || test_lstm_layer_with_hidden(RandomMat(8, 2), 2, 0)
- || test_lstm_layer_with_hidden(RandomMat(16, 8), 7, 0)
- || test_lstm_layer_with_hidden(RandomMat(17, 8), 8, 0)
- || test_lstm_layer_with_hidden(RandomMat(19, 15), 8, 0)
- || test_lstm_layer_with_hidden(RandomMat(5, 16), 16, 0)
- || test_lstm_layer_with_hidden(RandomMat(3, 16), 8, 0)
- || test_lstm_layer_with_hidden(RandomMat(2, 5), 17, 0, 15)
-
- || test_lstm_layer_with_hidden_input(RandomMat(4, 4), 1, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(8, 2), 2, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(16, 8), 7, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(17, 8), 8, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(19, 15), 8, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(5, 16), 16, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(3, 16), 8, 2)
- || test_lstm_layer_with_hidden_input(RandomMat(2, 5), 99, 2, 33)
- || test_lstm_layer_with_hidden_input(RandomMat(4, 4), 1, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(8, 2), 2, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(16, 8), 7, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(17, 8), 8, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(19, 15), 8, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(5, 16), 16, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(3, 16), 8, 1)
- || test_lstm_layer_with_hidden_input(RandomMat(2, 5), 99, 1, 33)
- || test_lstm_layer_with_hidden_input(RandomMat(4, 2), 1, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(8, 2), 2, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(16, 8), 7, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(17, 8), 8, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(19, 15), 8, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(5, 16), 16, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(3, 16), 8, 0)
- || test_lstm_layer_with_hidden_input(RandomMat(2, 5), 17, 0, 15)
-
- || test_lstm_layer_with_hidden_output(RandomMat(4, 4), 1, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(8, 2), 2, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(16, 8), 7, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(17, 8), 8, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(19, 15), 8, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(5, 16), 16, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(3, 16), 8, 2)
- || test_lstm_layer_with_hidden_output(RandomMat(2, 5), 99, 2, 33)
- || test_lstm_layer_with_hidden_output(RandomMat(4, 4), 1, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(8, 2), 2, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(16, 8), 7, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(17, 8), 8, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(19, 15), 8, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(5, 16), 16, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(3, 16), 8, 1)
- || test_lstm_layer_with_hidden_output(RandomMat(2, 5), 99, 1, 33)
- || test_lstm_layer_with_hidden_output(RandomMat(4, 2), 1, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(8, 2), 2, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(16, 8), 7, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(17, 8), 8, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(19, 15), 8, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(5, 16), 16, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(3, 16), 8, 0)
- || test_lstm_layer_with_hidden_output(RandomMat(2, 5), 17, 0, 15);
- }
-
- static int test_lstm_2()
- {
- return 0
- || test_lstm(RandomMat(4, 1), 1, 0)
- || test_lstm(RandomMat(8, 2), 2, 0)
- || test_lstm(RandomMat(16, 8), 7, 0)
- || test_lstm(RandomMat(17, 8), 8, 0)
- || test_lstm(RandomMat(19, 15), 8, 0)
- || test_lstm(RandomMat(5, 16), 16, 0)
- || test_lstm(RandomMat(3, 16), 8, 0)
- || test_lstm(RandomMat(8, 16), 16, 0)
- || test_lstm(RandomMat(2, 5), 17, 0, 15);
- }
- static int test_lstm_3()
- {
- return 0
- || test_lstm(RandomMat(4, 1), 1, 1)
- || test_lstm(RandomMat(8, 2), 2, 1)
- || test_lstm(RandomMat(16, 8), 7, 1)
- || test_lstm(RandomMat(17, 8), 8, 1)
- || test_lstm(RandomMat(19, 15), 8, 1)
- || test_lstm(RandomMat(5, 16), 16, 1)
- || test_lstm(RandomMat(3, 16), 8, 1)
- || test_lstm(RandomMat(8, 16), 16, 1)
- || test_lstm(RandomMat(2, 5), 17, 1, 15);
- }
-
- int main()
- {
- SRAND(7767517);
- return 0 || test_lstm_0() || test_lstm_1() || test_lstm_2() || test_lstm_3();
- }
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