//***************************************************************************** // Copyright 2017-2019 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 <algorithm> #include <cmath> #include <cstdint> #include <fstream> #include <iterator> #include <limits> #include <numeric> #include <sstream> #include <stdexcept> #include <vector> #include "gtest/gtest.h" #include "ngraph/frontend/onnx_import/onnx.hpp" #include "ngraph/ngraph.hpp" #include "util/all_close.hpp" #include "util/all_close_f.hpp" #include "util/ndarray.hpp" #include "util/test_case.hpp" #include "util/test_control.hpp" #include "util/test_tools.hpp" using namespace ngraph; static std::string s_manifest = "${MANIFEST}"; NGRAPH_TEST(onnx_${BACKEND_NAME}, model_lstm_fwd_with_clip) { auto function = onnx_import::import_onnx_model( file_util::path_join(SERIALIZED_ZOO, "onnx/lstm_fwd_with_clip.prototxt")); auto test_case = ngraph::test::NgraphTestCase(function, "${BACKEND_NAME}"); test_case.add_input<float>({-0.455351, -0.276391, -0.185934, -0.269585}); // X test_case.add_input<float>({-0.494659f, // W 0.0453352f, -0.487793f, 0.417264f, -0.0175329f, 0.489074f, -0.446013f, 0.414029f, -0.0091708f, -0.255364f, -0.106952f, -0.266717f, -0.0888852f, -0.428709f, -0.283349f, 0.208792f}); // W test_case.add_input<float>({0.146626f, -0.0620289f, -0.0815302f, 0.100482f, -0.219535f, -0.306635f, -0.28515f, -0.314112f, -0.228172f, 0.405972f, 0.31576f, 0.281487f, -0.394864f, 0.42111f, -0.386624f, -0.390225f}); // R test_case.add_input<float>({0.381619f, 0.0323954f, -0.14449f, 0.420804f, -0.258721f, 0.45056f, -0.250755f, 0.0967895f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f}); // B test_case.add_input<float>({0.2345f, 0.5235f, 0.4378f, 0.3475f, 0.8927f, 0.3456f}); // P test_case.add_expected_output<float>( Shape{2, 1, 1, 2}, {-0.02280854f, 0.02744377f, -0.03516197f, 0.03875681f}); // Y_data test_case.add_expected_output<float>(Shape{1, 1, 2}, {-0.03516197f, 0.03875681f}); // Y_h_data test_case.add_expected_output<float>(Shape{1, 1, 2}, {-0.07415761f, 0.07395997f}); // Y_c_data // We have to enlarge tolerance bits to 3 - it's only one bit more than default value. // The discrepancies may occur at most on 7th decimal position. test_case.set_tolerance(3); test_case.run(); } NGRAPH_TEST(onnx_${BACKEND_NAME}, model_lstm_fwd_mixed_seq) { auto function = onnx_import::import_onnx_model( file_util::path_join(SERIALIZED_ZOO, "onnx/lstm_fwd_mixed_seq.prototxt")); auto test_case = ngraph::test::NgraphTestCase(function, "${BACKEND_NAME}"); int hidden_size{3}; test_case.add_input<float>({1.f, 2.f, 10.f, 11.f}); // X test_case.add_input<float>( {0.1f, 0.2f, 0.3f, 0.4f, 1.f, 2.f, 3.f, 4.f, 10.f, 11.f, 12.f, 13.f}); // W test_case.add_input(std::vector<float>(4 * hidden_size * hidden_size, 0.1f)); // R test_case.add_input(std::vector<float>(8 * hidden_size, 0.0f)); // B test_case.add_input<int>({1, 2}); // seq_lengths test_case.add_expected_output<float>(Shape{2, 1, 2, 3}, {0.28828835f, 0.36581863f, 0.45679406f, 0.34526032f, 0.47220859f, 0.55850911f, 0.f, 0.f, 0.f, 0.85882828f, 0.90703777f, 0.92382453f}); // Y_data test_case.add_expected_output<float>( Shape{1, 2, 3}, {0.28828835f, 0.36581863f, 0.45679406f, 0.85882828f, 0.90703777f, 0.92382453f}); // Y_h_data test_case.add_expected_output<float>( Shape{1, 2, 3}, {0.52497941f, 0.54983425f, 0.5744428f, 1.3249796f, 1.51063104f, 1.61451544f}); // Y_c_data // We have to enlarge tolerance bits to 3 - it's only one bit more than default value. // The discrepancies may occur at most on 7th decimal position. test_case.set_tolerance(3); test_case.run(); } NGRAPH_TEST(onnx_${BACKEND_NAME}, model_lstm_fwd_hardsigmoid_activation) { auto function = onnx_import::import_onnx_model( file_util::path_join(SERIALIZED_ZOO, "onnx/lstm_fwd_hardsigmoid_activation.prototxt")); auto test_case = ngraph::test::NgraphTestCase(function, "${BACKEND_NAME}"); // X test_case.add_input<float>({-0.455351f, -0.276391f, -0.185934f, -0.269585f}); // W test_case.add_input<float>({-0.494659f, 0.0453352f, -0.487793f, 0.417264f, -0.0175329f, 0.489074f, -0.446013f, 0.414029f, -0.0091708f, -0.255364f, -0.106952f, -0.266717f, -0.0888852f, -0.428709f, -0.283349f, 0.208792f}); // R test_case.add_input<float>({0.146626f, -0.0620289f, -0.0815302f, 0.100482f, -0.219535f, -0.306635f, -0.28515f, -0.314112f, -0.228172f, 0.405972f, 0.31576f, 0.281487f, -0.394864f, 0.42111f, -0.386624f, -0.390225f}); // Y test_case.add_expected_output<float>(Shape{2, 1, 1, 2}, {0.09086666f, 0.04378549f, 0.12914555f, 0.00257774f}); // Y_h test_case.add_expected_output<float>(Shape{1, 1, 2}, {0.12914555f, 0.00257774f}); // Y_c test_case.add_expected_output<float>(Shape{1, 1, 2}, {0.19017234f, 0.00356848f}); // The discrepancies occur at most at 18th mantissa bit - 8th decimal position. test_case.set_tolerance(6); test_case.run(); } NGRAPH_TEST(onnx_${BACKEND_NAME}, model_lstm_fwd_large_batch_no_clip) { auto function = onnx_import::import_onnx_model( file_util::path_join(SERIALIZED_ZOO, "onnx/lstm_fwd_large_batch_no_clip.prototxt")); auto test_case = ngraph::test::NgraphTestCase(function, "${BACKEND_NAME}"); std::size_t seq_length = 2; std::size_t batch_size = 32; std::size_t input_size = 1; std::size_t hidden_size = 3; std::vector<float> in_X(seq_length * batch_size * input_size); std::iota(std::begin(in_X), std::end(in_X), 1.f); std::vector<float> in_R(4 * hidden_size * hidden_size, 0.1f); // X test_case.add_input<float>(in_X); // W test_case.add_input<float>( {0.1f, 0.2f, 0.3f, 0.4f, 1.f, 2.f, 3.f, 4.f, 10.f, 11.f, 12.f, 13.f}); // R test_case.add_input<float>(in_R); // Y_h_data test_case.add_expected_output<float>( Shape{1, batch_size, hidden_size}, {0.90387899f, 0.9135572f, 0.91772245f, 0.90897038f, 0.92132433f, 0.92825467f, 0.91365823f, 0.92815113f, 0.93676105f, 0.91799162f, 0.93406357f, 0.94344562f, 0.92199681f, 0.93912057f, 0.94859476f, 0.92569357f, 0.94340185f, 0.95250664f, 0.92909964f, 0.94699686f, 0.95545127f, 0.93223207f, 0.94999634f, 0.95765468f, 0.93510761f, 0.9524867f, 0.95929726f, 0.93774272f, 0.9545467f, 0.96051891f, 0.9401536f, 0.95624603f, 0.96142619f, 0.94235605f, 0.95764499f, 0.96209939f, 0.94436539f, 0.95879495f, 0.96259862f, 0.94619635f, 0.95973921f, 0.96296872f, 0.94786299f, 0.96051397f, 0.96324302f, 0.94937864f, 0.96114929f, 0.96344629f, 0.95075587f, 0.96167006f, 0.96359692f, 0.95200645f, 0.96209679f, 0.96370852f, 0.95314133f, 0.9624464f, 0.9637912f, 0.95417069f, 0.96273278f, 0.96385246f, 0.95510395f, 0.96296733f, 0.96389785f, 0.95594975f, 0.96315942f, 0.96393147f, 0.95671607f, 0.96331673f, 0.96395638f, 0.9574102f, 0.96344554f, 0.96397483f, 0.9580388f, 0.96355102f, 0.9639885f, 0.95860795f, 0.96363739f, 0.96399863f, 0.95912322f, 0.96370811f, 0.96400613f, 0.95958963f, 0.96376601f, 0.96401169f, 0.96001179f, 0.96381342f, 0.96401581f, 0.96039386f, 0.96385224f, 0.96401886f, 0.96073964f, 0.96388402f, 0.96402112f, 0.96105254f, 0.96391004f, 0.96402279f}); test_case.run(); }