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Diffstat (limited to 'tests/nnfw_api/src/ValidationTestMultipleSessions.test.cc')
| -rw-r--r-- | tests/nnfw_api/src/ValidationTestMultipleSessions.test.cc | 140 |
1 files changed, 140 insertions, 0 deletions
diff --git a/tests/nnfw_api/src/ValidationTestMultipleSessions.test.cc b/tests/nnfw_api/src/ValidationTestMultipleSessions.test.cc new file mode 100644 index 000000000..ef00dc6bd --- /dev/null +++ b/tests/nnfw_api/src/ValidationTestMultipleSessions.test.cc @@ -0,0 +1,140 @@ +/* + * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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 "fixtures.h" +#include "one_op_tests/WhileTestModel.h" + +TEST_F(ValidationTestTwoSessions, neg_two_sessions_create) +{ + ASSERT_EQ(nnfw_create_session(&_session1), NNFW_STATUS_NO_ERROR); + ASSERT_EQ(nnfw_create_session(nullptr), NNFW_STATUS_UNEXPECTED_NULL); + + ASSERT_EQ(nnfw_close_session(_session1), NNFW_STATUS_NO_ERROR); +} + +class AveragePoolModel +{ +public: + AveragePoolModel(int N, int H, int W, int C) + { + CircleGen cgen; + int in = cgen.addTensor({{N, H, W, C}, circle::TensorType::TensorType_FLOAT32}); + int out = cgen.addTensor({{N, H / 2, W / 2, C}, circle::TensorType::TensorType_FLOAT32}); + cgen.addOperatorAveragePool2D({{in}, {out}}, circle::Padding_SAME, 2, 2, 2, 2, + circle::ActivationFunctionType_NONE); + cgen.setInputsAndOutputs({in}, {out}); + cbuf = cgen.finish(); + }; + + CircleBuffer cbuf; +}; + +TEST_F(ValidationTestTwoSessionsCreated, two_sessions_run_simple_AaveragePool_model) +{ + constexpr int N = 64, H = 64, W = 64, C = 3; + AveragePoolModel model(N, H, W, C); + + NNFW_ENSURE_SUCCESS( + nnfw_load_circle_from_buffer(_session1, model.cbuf.buffer(), model.cbuf.size())); + NNFW_ENSURE_SUCCESS( + nnfw_load_circle_from_buffer(_session2, model.cbuf.buffer(), model.cbuf.size())); + + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session1, "cpu")); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session2, "cpu")); + + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session2)); + + constexpr int input_count = N * H * W * C; + constexpr int output_count = N * H / 2 * W / 2 * C; + + std::vector<float> in_buf1(input_count); // any value + std::vector<float> out_buf1(output_count); + + NNFW_ENSURE_SUCCESS(nnfw_set_input(_session1, 0, NNFW_TYPE_TENSOR_FLOAT32, in_buf1.data(), + in_buf1.size() * sizeof(float))); + NNFW_ENSURE_SUCCESS(nnfw_set_output(_session1, 0, NNFW_TYPE_TENSOR_FLOAT32, out_buf1.data(), + out_buf1.size() * sizeof(float))); + + std::vector<float> in_buf2(input_count); // any value + std::vector<float> out_buf2(output_count); + + NNFW_ENSURE_SUCCESS(nnfw_set_input(_session2, 0, NNFW_TYPE_TENSOR_FLOAT32, in_buf2.data(), + in_buf2.size() * sizeof(float))); + NNFW_ENSURE_SUCCESS(nnfw_set_output(_session2, 0, NNFW_TYPE_TENSOR_FLOAT32, out_buf2.data(), + out_buf2.size() * sizeof(float))); + + NNFW_ENSURE_SUCCESS(nnfw_run_async(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_run_async(_session2)); + + NNFW_ENSURE_SUCCESS(nnfw_await(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_await(_session2)); + + SUCCEED(); +} + +TEST_F(ValidationTestTwoSessionsCreated, neg_two_sessions_model_load) +{ + constexpr int N = 64, H = 64, W = 64, C = 3; + AveragePoolModel model(N, H, W, C); + + NNFW_ENSURE_SUCCESS( + nnfw_load_circle_from_buffer(_session1, model.cbuf.buffer(), model.cbuf.size())); + ASSERT_EQ(nnfw_load_circle_from_buffer(nullptr, model.cbuf.buffer(), model.cbuf.size()), + NNFW_STATUS_UNEXPECTED_NULL); +} + +TEST_F(ValidationTestTwoSessionsCreated, two_sessions_run_simple_While_model) +{ + WhileModelLoop10 model; + + NNFW_ENSURE_SUCCESS( + nnfw_load_circle_from_buffer(_session1, model.cbuf.buffer(), model.cbuf.size())); + NNFW_ENSURE_SUCCESS( + nnfw_load_circle_from_buffer(_session2, model.cbuf.buffer(), model.cbuf.size())); + + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session1, "cpu")); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session2, "cpu")); + + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session2)); + + std::vector<float> in_buf1(model.inputCount()); // any value + std::vector<float> out_buf1(model.outputputCount()); + + NNFW_ENSURE_SUCCESS(nnfw_set_input(_session1, 0, NNFW_TYPE_TENSOR_FLOAT32, in_buf1.data(), + in_buf1.size() * model.sizeOfDType())); + NNFW_ENSURE_SUCCESS(nnfw_set_output(_session1, 0, NNFW_TYPE_TENSOR_FLOAT32, out_buf1.data(), + out_buf1.size() * model.sizeOfDType())); + + std::vector<float> in_buf2(model.inputCount()); // any value + std::vector<float> out_buf2(model.outputputCount()); + + NNFW_ENSURE_SUCCESS(nnfw_set_input(_session2, 0, NNFW_TYPE_TENSOR_FLOAT32, in_buf2.data(), + in_buf2.size() * model.sizeOfDType())); + NNFW_ENSURE_SUCCESS(nnfw_set_output(_session2, 0, NNFW_TYPE_TENSOR_FLOAT32, out_buf2.data(), + out_buf2.size() * model.sizeOfDType())); + + NNFW_ENSURE_SUCCESS(nnfw_run_async(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_run_async(_session2)); + + NNFW_ENSURE_SUCCESS(nnfw_await(_session1)); + NNFW_ENSURE_SUCCESS(nnfw_await(_session2)); + + SUCCEED(); +} + +// TODO Write two-session-test with large models run by threads |