From e7744fc9abfc171d97c381c6c0622f61015ddd2a Mon Sep 17 00:00:00 2001 From: yvette Date: Fri, 13 Nov 2020 15:23:20 +0800 Subject: [PATCH] move compareOutput into /test --- mindspore/lite/src/common/file_utils.cc | 32 -------- mindspore/lite/src/common/file_utils.h | 3 - mindspore/lite/src/common/file_utils_ext.cc | 65 ---------------- mindspore/lite/src/common/file_utils_ext.h | 27 ------- mindspore/lite/test/CMakeLists.txt | 1 - mindspore/lite/test/common/common_test.h | 75 ++++++++++++++++-- mindspore/lite/test/ut/internal/infer_test.cc | 2 +- .../src/kernel/fp32/arithmetic_fp32_test.cc | 4 +- .../src/kernel/fp32/bias_add_fp32_test.cc | 4 +- .../src/kernel/fp32/reduce_fp32_test.cc | 8 +- .../kernel/arm/common/strided_slice_tests.cc | 2 +- .../kernel/arm/fp16/reduce_fp16_tests.cc | 2 +- .../kernel/arm/fp32/activation_fp32_test.cc | 6 +- .../kernel/arm/fp32/argminmax_fp32_test.cc | 28 +++---- .../kernel/arm/fp32/arithmetic_fp32_tests.cc | 62 +++++++-------- .../arm/fp32/batch_to_space_fp32_test.cc | 16 ++-- .../kernel/arm/fp32/batchnorm_fp32_tests.cc | 6 +- .../arm/fp32/constant_of_shape_fp32_test.cc | 2 +- .../kernel/arm/fp32/conv1x1_fp32_tests.cc | 44 +++++------ .../fp32/convolution_depthwise_fp32_tests.cc | 10 +-- .../runtime/kernel/arm/fp32/crop_fp32_test.cc | 44 +++++------ .../arm/fp32/deconvolution_fp32_tests.cc | 77 +++++++++---------- .../arm/fp32/depth_to_space_fp32_test.cc | 4 +- .../arm/fp32/detection_post_process_test.cc | 16 ++-- .../arm/fp32/fullconnection_fp32_tests.cc | 43 +++++------ .../arm/fp32/instance_norm_fp32_tests.cc | 4 +- .../kernel/arm/fp32/l2norm_fp32_test.cc | 8 +- .../arm/fp32/lsh_projection_fp32_tests.cc | 6 +- .../kernel/arm/fp32/lstm_fp32_tests.cc | 24 +++--- .../kernel/arm/fp32/matmul_fp32_tests.cc | 20 ++--- .../fp32/non_max_suppression_fp32_tests.cc | 3 +- .../runtime/kernel/arm/fp32/pad_fp32_test.cc | 10 +-- .../kernel/arm/fp32/power_fp32_tests.cc | 15 ++-- .../kernel/arm/fp32/reduce_fp32_tests.cc | 28 +++---- .../arm/fp32/resize_bilinear_fp32_tests.cc | 32 ++++---- .../resize_nearest_neighbor_fp32_tests.cc | 32 ++++---- .../kernel/arm/fp32/roi_pooling_fp32_tests.cc | 8 +- .../kernel/arm/fp32/scale_fp32_tests.cc | 6 +- .../arm/fp32/space_to_batch_fp32_tests.cc | 18 ++--- .../arm/fp32/space_to_depth_fp32_tests.cc | 4 +- .../arm/fp32/sparse_to_dense_fp32_tests.cc | 10 +-- .../kernel/arm/fp32/stack_fp32_test.cc | 6 +- .../arm/fp32/strided_slice_fp32_tests.cc | 24 +++--- .../kernel/arm/fp32/transpose_fp32_tests.cc | 8 +- .../fp32_grad/activation_grad_fp32_tests.cc | 16 ++-- .../fp32_grad/arithmetic_grad_fp32_tests.cc | 53 +++++++------ .../arm/fp32_grad/bias_grad_fp32_tests.cc | 2 +- .../kernel/arm/fp32_grad/bn_grad_fp32_test.cc | 11 ++- .../fp32_grad/convolution_grad_fp32_tests.cc | 19 +++-- .../deconvolution_grad_fp32_tests.cc | 14 ++-- .../kernel/arm/fp32_grad/network_test.cc | 9 +-- .../arm/fp32_grad/pooling_grad_fp32_tests.cc | 19 +++-- .../softmax_crossentropy_fp32_tests.cc | 4 +- .../arm/fp32_grad/softmax_grad_fp32_tests.cc | 11 ++- .../arm/int8/arithmetic_self_int8_tests.cc | 32 ++++---- .../kernel/arm/int8/batchnorm_int8_test.cc | 4 +- .../kernel/arm/int8/concat_int8_tests.cc | 6 +- .../kernel/arm/int8/conv_1x1_int8_tests.cc | 14 ++-- .../kernel/arm/int8/crop_int8_tests.cc | 20 ++--- .../kernel/arm/int8/deconv_int8_tests.cc | 40 +++++----- .../arm/int8/fullconnection_int8_tests.cc | 2 +- .../kernel/arm/int8/gatherNd_int8_test.cc | 2 +- .../kernel/arm/int8/gather_int8_test.cc | 2 +- .../kernel/arm/int8/matmul_int8_tests.cc | 6 +- .../runtime/kernel/arm/int8/mul_int8_tests.cc | 10 +-- .../runtime/kernel/arm/int8/pad_int8_tests.cc | 6 +- .../kernel/arm/int8/power_int8_tests.cc | 4 +- .../kernel/arm/int8/prelu_int8_tests.cc | 2 +- .../kernel/arm/int8/quant_dtype_cast_tests.cc | 4 +- .../kernel/arm/int8/reshape_int8_tests.cc | 4 +- .../kernel/arm/int8/softmax_int8_tests.cc | 2 +- .../kernel/arm/int8/split_int8_tests.cc | 16 ++-- .../kernel/arm/int8/squeeze_int8_tests.cc | 2 +- .../kernel/arm/int8/unsqueeze_int8_tests.cc | 2 +- .../runtime/kernel/opencl/batchnorm_tests.cc | 6 +- .../src/runtime/kernel/opencl/concat_tests.cc | 8 +- .../src/runtime/kernel/opencl/fill_tests.cc | 4 +- .../src/runtime/kernel/opencl/hswish_tests.cc | 2 +- .../ut/src/runtime/kernel/opencl/pad_tests.cc | 4 +- .../kernel/opencl/sparse_to_dense_tests.cc | 12 +-- .../src/runtime/kernel/opencl/stack_tests.cc | 4 +- .../runtime/kernel/opencl/to_format_tests.cc | 2 +- 82 files changed, 574 insertions(+), 655 deletions(-) delete mode 100644 mindspore/lite/src/common/file_utils_ext.cc delete mode 100644 mindspore/lite/src/common/file_utils_ext.h diff --git a/mindspore/lite/src/common/file_utils.cc b/mindspore/lite/src/common/file_utils.cc index cd65c1b921..6683e2a3fd 100644 --- a/mindspore/lite/src/common/file_utils.cc +++ b/mindspore/lite/src/common/file_utils.cc @@ -84,37 +84,5 @@ std::string RealPath(const char *path) { std::string res = resolvedPath.get(); return res; } - -int CompareOutputData(const float *output_data, size_t output_size, const float *correct_data, size_t data_size) { - if (output_size != data_size) { - printf("compare failed, output_size %zu isn't equal to data_size %zu.\n", output_size, data_size); - return 0; - } - float error = 0; - for (size_t i = 0; i < data_size; i++) { - float abs = fabs(output_data[i] - correct_data[i]); - if (abs > 0.00001) { - error += abs; - } - } - error /= data_size; - - if (error > 0.0001) { - printf("has accuracy error!\n"); - printf("%f\n", error); - return 1; - } - return 0; -} - -int CompareOutput(const float *output_data, size_t output_num, const std::string &file_path) { - size_t ground_truth_size = 0; - auto ground_truth = reinterpret_cast(mindspore::lite::ReadFile(file_path.c_str(), &ground_truth_size)); - size_t ground_truth_num = ground_truth_size / sizeof(float); - printf("ground truth num : %zu\n", ground_truth_num); - int res = CompareOutputData(output_data, output_num, ground_truth, ground_truth_num); - delete[] ground_truth; - return res; -} } // namespace lite } // namespace mindspore diff --git a/mindspore/lite/src/common/file_utils.h b/mindspore/lite/src/common/file_utils.h index b22225c166..46475fcd26 100644 --- a/mindspore/lite/src/common/file_utils.h +++ b/mindspore/lite/src/common/file_utils.h @@ -58,9 +58,6 @@ inline int WriteToBin(const std::string &file_path, void *data, size_t size) { return 0; } -int CompareOutputData(const float *output_data, size_t output_num, const float *correct_data, size_t data_size); -int CompareOutput(const float *output_data, size_t output_num, const std::string &file_path); - std::string GetAndroidPackageName(); std::string GetAndroidPackagePath(); } // namespace lite diff --git a/mindspore/lite/src/common/file_utils_ext.cc b/mindspore/lite/src/common/file_utils_ext.cc deleted file mode 100644 index b8ba1353e5..0000000000 --- a/mindspore/lite/src/common/file_utils_ext.cc +++ /dev/null @@ -1,65 +0,0 @@ -/** - * Copyright 2020 Huawei Technologies Co., Ltd - * - * 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 -#include -#include -#include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" - -namespace mindspore { -namespace lite { -static float CompareOutputRelativeData(const float *output_data, const float *correct_data, int data_size) { - float error = 0; - - // relative error - float diffSum = 0.0f; - float sum = 0.0f; - for (int i = 0; i < data_size; i++) { - sum += std::abs(correct_data[i]); - } - for (int i = 0; i < data_size; i++) { - float diff = std::abs(output_data[i] - correct_data[i]); - diffSum += diff; - } - error = diffSum / sum; - return error; -} - -int CompareRelativeOutput(const float *output_data, std::string file_path) { - size_t output_size; - auto ground_truth = reinterpret_cast(mindspore::lite::ReadFile(file_path.c_str(), &output_size)); - if (ground_truth == nullptr) { - return 1; - } - size_t output_num = output_size / sizeof(float); - float error = CompareOutputRelativeData(output_data, ground_truth, output_num); - delete[] ground_truth; - if (error > 1e-4) { - return 1; - } - return 0; -} - -float RelativeOutputError(const float *output_data, std::string file_path) { - size_t output_size = 0; - auto ground_truth = reinterpret_cast(mindspore::lite::ReadFile(file_path.c_str(), &output_size)); - size_t output_num = output_size / sizeof(float); - float error = CompareOutputRelativeData(output_data, ground_truth, output_num); - delete[] ground_truth; - return error; -} -} // namespace lite -} // namespace mindspore diff --git a/mindspore/lite/src/common/file_utils_ext.h b/mindspore/lite/src/common/file_utils_ext.h deleted file mode 100644 index f81c2e434c..0000000000 --- a/mindspore/lite/src/common/file_utils_ext.h +++ /dev/null @@ -1,27 +0,0 @@ -/** - * Copyright 2020 Huawei Technologies Co., Ltd - * - * 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. - */ - -#ifndef MINDSPORE_LITE_COMMON_FILE_UTILS_EXT_H_ -#define MINDSPORE_LITE_COMMON_FILE_UTILS_EXT_H_ -#include - -namespace mindspore { -namespace lite { -int CompareRelativeOutput(const float *output_data, std::string file_path); -float RelativeOutputError(const float *output_data, std::string file_path); -} // namespace lite -} // namespace mindspore -#endif // MINDSPORE_LITE_COMMON_FILE_UTILS_EXT_H_ diff --git a/mindspore/lite/test/CMakeLists.txt b/mindspore/lite/test/CMakeLists.txt index b3ce4be0d7..cff972f2b3 100644 --- a/mindspore/lite/test/CMakeLists.txt +++ b/mindspore/lite/test/CMakeLists.txt @@ -144,7 +144,6 @@ set(TEST_LITE_SRC ${LITE_DIR}/src/scheduler.cc ${LITE_DIR}/src/common/graph_util.cc ${LITE_DIR}/src/common/file_utils.cc - ${LITE_DIR}/src/common/file_utils_ext.cc ${LITE_DIR}/src/common/utils.cc ${LITE_DIR}/src/common/string_util.cc ${LITE_DIR}/tools/common/graph_util.cc diff --git a/mindspore/lite/test/common/common_test.h b/mindspore/lite/test/common/common_test.h index 80371a4229..99d25b167b 100644 --- a/mindspore/lite/test/common/common_test.h +++ b/mindspore/lite/test/common/common_test.h @@ -22,6 +22,8 @@ #include #include #include "gtest/gtest.h" +#include "src/common/file_utils.h" + namespace mindspore { class CommonTest : public testing::Test { public: @@ -34,7 +36,7 @@ class CommonTest : public testing::Test { virtual void TearDown(); template - void PrintData(std::string name, T *output_data, int size) { + void PrintData(const std::string &name, T *output_data, int size) { std::cout << "The " << name << " is as follows:" << std::endl; if (typeid(output_data[0]) == typeid(uint8_t) || typeid(output_data[0]) == typeid(int8_t)) { for (int i = 0; i < std::min(size, 100); i++) { @@ -49,14 +51,22 @@ class CommonTest : public testing::Test { } template - static void CompareOutputData(T *output_data, T *correct_data, int size, float err_bound) { + static int CompareOutputData(const T *output_data, const T *correct_data, int size, float err_bound = 1e-4) { + float error = 0; for (int i = 0; i < size; i++) { - T abs = fabs(output_data[i] - correct_data[i]); - ASSERT_LE(abs, err_bound); + T diff = std::fabs(output_data[i] - correct_data[i]); + if (diff > 0.00001) { + error += diff; + } } + error /= static_cast(size); + if (error > err_bound) { + return 1; + } + return 0; } - void CompareOutputInt8(int8_t *output_data, int8_t *correct_data, int size, float err_percent) { + static void CompareOutputInt8(int8_t *output_data, int8_t *correct_data, int size, float err_percent) { int bias_count = 0; for (int i = 0; i < size; i++) { int8_t diff = abs(output_data[i] - correct_data[i]); @@ -65,11 +75,62 @@ class CommonTest : public testing::Test { bias_count++; } } - float bias_percent = static_cast(bias_count) / size; + float bias_percent = static_cast(bias_count) / static_cast(size); ASSERT_LE(bias_percent, err_percent); } - void ReadFile(const char *file, size_t *size, char **buf) { + static int CompareOutput(const float *output_data, size_t output_num, const std::string &file_path) { + size_t ground_truth_size = 0; + auto ground_truth = reinterpret_cast(lite::ReadFile(file_path.c_str(), &ground_truth_size)); + size_t ground_truth_num = ground_truth_size / sizeof(float); + printf("ground truth num : %zu\n", ground_truth_num); + int res = CompareOutputData(output_data, ground_truth, ground_truth_num); + delete[] ground_truth; + return res; + } + + static float CompareOutputRelativeData(const float *output_data, const float *correct_data, int data_size) { + float error = 0; + + // relative error + float diffSum = 0.0f; + float sum = 0.0f; + for (int i = 0; i < data_size; i++) { + sum += std::abs(correct_data[i]); + } + for (int i = 0; i < data_size; i++) { + float diff = std::abs(output_data[i] - correct_data[i]); + diffSum += diff; + } + error = diffSum / sum; + return error; + } + + static int CompareRelativeOutput(const float *output_data, const std::string &file_path) { + size_t output_size; + auto ground_truth = reinterpret_cast(mindspore::lite::ReadFile(file_path.c_str(), &output_size)); + if (ground_truth == nullptr) { + return 1; + } + size_t output_num = output_size / sizeof(float); + float error = CompareOutputRelativeData(output_data, ground_truth, output_num); + delete[] ground_truth; + if (error > 1e-4) { + return 1; + } + return 0; + } + + static float RelativeOutputError(const float *output_data, const std::string &file_path) { + size_t output_size = 0; + auto ground_truth = reinterpret_cast(mindspore::lite::ReadFile(file_path.c_str(), &output_size)); + size_t output_num = output_size / sizeof(float); + float error = CompareOutputRelativeData(output_data, ground_truth, output_num); + delete[] ground_truth; + return error; + } + + static void ReadFile(const char *file, size_t *size, char **buf) { ASSERT_NE(nullptr, file); ASSERT_NE(nullptr, size); ASSERT_NE(nullptr, buf); diff --git a/mindspore/lite/test/ut/internal/infer_test.cc b/mindspore/lite/test/ut/internal/infer_test.cc index aa3805c851..0b4e18bb1e 100644 --- a/mindspore/lite/test/ut/internal/infer_test.cc +++ b/mindspore/lite/test/ut/internal/infer_test.cc @@ -72,7 +72,7 @@ TEST_F(InferTest, TestSession) { std::cout << *(reinterpret_cast(outvec.at(0)->data_) + i) << " "; } std::cout << "\n"; - CompareOutputData(reinterpret_cast(outvec.at(0)->data_), expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outvec.at(0)->data_), expect_out, kOutSize, 0.000001)); DestroyTensor(in); DestroyTensor(out); } diff --git a/mindspore/lite/test/ut/internal/src/kernel/fp32/arithmetic_fp32_test.cc b/mindspore/lite/test/ut/internal/src/kernel/fp32/arithmetic_fp32_test.cc index 2030933ff6..6c36401395 100644 --- a/mindspore/lite/test/ut/internal/src/kernel/fp32/arithmetic_fp32_test.cc +++ b/mindspore/lite/test/ut/internal/src/kernel/fp32/arithmetic_fp32_test.cc @@ -90,8 +90,8 @@ TEST_F(TestInternalArithmeticFp32, MulTest) { out_tensors[0]->data_ = new float[correct_out.size()]; DoArithmetic(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct_out.data(), correct_out.size(), - 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct_out.data(), + correct_out.size(), 0.00001)); delete[] out_tensors[0]->data_; delete node; diff --git a/mindspore/lite/test/ut/internal/src/kernel/fp32/bias_add_fp32_test.cc b/mindspore/lite/test/ut/internal/src/kernel/fp32/bias_add_fp32_test.cc index d7766688de..b88791b818 100644 --- a/mindspore/lite/test/ut/internal/src/kernel/fp32/bias_add_fp32_test.cc +++ b/mindspore/lite/test/ut/internal/src/kernel/fp32/bias_add_fp32_test.cc @@ -82,8 +82,8 @@ TEST_F(TestInternalBiasAddFp32, BiasAddTest) { out_tensors[0]->data_ = new float[correct_out.size()]; DoBiasAdd(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct_out.data(), correct_out.size(), - 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct_out.data(), + correct_out.size(), 0.00001)); delete out_tensors[0]->data_; delete node; diff --git a/mindspore/lite/test/ut/internal/src/kernel/fp32/reduce_fp32_test.cc b/mindspore/lite/test/ut/internal/src/kernel/fp32/reduce_fp32_test.cc index 1a4b0c7421..b175f53e89 100644 --- a/mindspore/lite/test/ut/internal/src/kernel/fp32/reduce_fp32_test.cc +++ b/mindspore/lite/test/ut/internal/src/kernel/fp32/reduce_fp32_test.cc @@ -77,7 +77,7 @@ TEST_F(TestInternalReduceFp32, ReduceSumOneAxisTest) { DoReduce(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 24, 0.00001)); delete out_tensors[0]->data_; delete node; delete params; @@ -126,7 +126,7 @@ TEST_F(TestInternalReduceFp32, ReduceSumAllAxisTest) { DoReduce(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 1, 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 1, 0.00001)); delete out_tensors[0]->data_; delete node; delete params; @@ -180,7 +180,7 @@ TEST_F(TestInternalReduceFp32, ReduceMeanOneAxisTest) { DoReduce(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 24, 0.00001)); delete out_tensors[0]->data_; delete node; delete params; @@ -234,7 +234,7 @@ TEST_F(TestInternalReduceFp32, ReduceMeanAllAxisTest) { DoReduce(in_tensors, out_tensors, node, &allocator); - CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 1, 0.00001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(out_tensors.front()->data_), correct, 1, 0.00001)); delete out_tensors[0]->data_; delete node; delete params; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/common/strided_slice_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/common/strided_slice_tests.cc index e938311b08..115ee9f481 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/common/strided_slice_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/common/strided_slice_tests.cc @@ -71,7 +71,7 @@ TEST_F(TestStridedSlice, StridedSlice) { EXPECT_EQ(0, ret); float expect[2] = {0.2390374, 0.05051243}; - CompareOutputData(output_data, expect, 2, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, expect, 2, 0.000001)); in_tensor.set_data(nullptr); out_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp16/reduce_fp16_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp16/reduce_fp16_tests.cc index dd33f7a3f9..aecd9816fe 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp16/reduce_fp16_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp16/reduce_fp16_tests.cc @@ -95,7 +95,7 @@ TEST_F(TestReduceFp16, Mean) { int num_axis = 1; int thread_num = 1; Prepare(input_shape, output_shape, in, out, num_axis, axes, thread_num); - CompareOutputData(out, correct, 24, 1e-3); + ASSERT_EQ(0, CompareOutputData(out, correct, 24, 1e-3)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/activation_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/activation_fp32_test.cc index b5f8f87b3a..7a867717c9 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/activation_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/activation_fp32_test.cc @@ -132,7 +132,7 @@ TEST_F(TestActivationFp32, HSwishFp32) { kernel->Run(); std::vector expect_output = {-0, -0.33333334, -0.33333334, 0, 0.6666667, 5, 6, 7}; - CompareOutputData(output.data(), expect_output.data(), 8, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_output.data(), 8, 0.00001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); @@ -176,7 +176,7 @@ TEST_F(TestActivationFp32, HardTanh1) { kernel->Run(); std::vector expect_output = {-1.0, -1.0, -0.5, 0.0, 0.5, 1.0, 1.0, 1.0}; - CompareOutputData(output.data(), expect_output.data(), 8, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_output.data(), 8, 0.00001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); @@ -220,7 +220,7 @@ TEST_F(TestActivationFp32, HardTanh2) { kernel->Run(); std::vector expect_output = {-2.0, -2.0, -1.0, 0.0, 1.0, 2.0, 2.0, 2.0}; - CompareOutputData(output.data(), expect_output.data(), 8, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_output.data(), 8, 0.00001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/argminmax_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/argminmax_fp32_test.cc index b944317ced..ea417b5597 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/argminmax_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/argminmax_fp32_test.cc @@ -44,7 +44,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest1) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, except_out.data(), except_out.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.000001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest1_keep_dim) { @@ -69,7 +69,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest1_keep_dim) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, except_out.data(), except_out.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.000001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest_axis2_keep_dim) { @@ -95,7 +95,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest_axis2_keep_dim) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, except_out.data(), except_out.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.000001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest2) { @@ -112,7 +112,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest2) { param.get_max_ = true; param.keep_dims_ = false; ArgMinMax(in.data(), out, shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.000001)); } TEST_F(TestArgMinMaxTestFp32, ArgMinTest2) { @@ -129,7 +129,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMinTest2) { param.get_max_ = false; param.keep_dims_ = false; ArgMinMax(in.data(), out, shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.000001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest3_axis2_out_data) { @@ -146,7 +146,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest3_axis2_out_data) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[10]; ArgMaxDim2(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest3_axis2_out_index) { @@ -163,7 +163,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest3_axis2_out_index) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[10]; ArgMaxDim2(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest4_axis3_out_data) { @@ -180,7 +180,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest4_axis3_out_data) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[6]; ArgMaxDim3(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest4_axis3_out_index) { @@ -197,7 +197,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest4_axis3_out_index) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[6]; ArgMaxDim3(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest5_axis1_out_index) { @@ -215,7 +215,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest5_axis1_out_index) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[24]; ArgMaxDim1(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest5_axis1_out_data) { @@ -234,7 +234,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest5_axis1_out_data) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[24]; ArgMaxDim1(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest6_axis0_out_index) { @@ -251,7 +251,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest6_axis0_out_index) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[16]; ArgMaxDim0(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMaxTest6_axis0_out_data) { @@ -268,7 +268,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMaxTest6_axis0_out_data) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[16]; ArgMaxDim0(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } TEST_F(TestArgMinMaxTestFp32, ArgMinTest1_axis3_out_data) { @@ -285,7 +285,7 @@ TEST_F(TestArgMinMaxTestFp32, ArgMinTest1_axis3_out_data) { ComputeStrides(out_shape.data(), param.out_strides_, out_shape.size()); float out[6]; ArgMinDim3(in.data(), out, in_shape.data(), ¶m); - CompareOutputData(out, except_out.data(), except_out.size(), 0.00001); + ASSERT_EQ(0, CompareOutputData(out, except_out.data(), except_out.size(), 0.00001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/arithmetic_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/arithmetic_fp32_tests.cc index 1c39ff059d..bd46f0b417 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/arithmetic_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/arithmetic_fp32_tests.cc @@ -123,7 +123,7 @@ TEST_F(TestArithmeticTestFp32, AddTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastAdd(in_ptr, add_ptr, tile_data0, tile_data1, out, size, add_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -166,7 +166,7 @@ TEST_F(TestArithmeticTestFp32, MulTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastMul(in_ptr, add_ptr, tile_data0, tile_data1, out, size, mul_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -209,7 +209,7 @@ TEST_F(TestArithmeticTestFp32, DivTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastDiv(in_ptr, add_ptr, tile_data0, tile_data1, out, size, div_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -229,7 +229,7 @@ TEST_F(TestArithmeticTestFp32, DivTest2) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, correct_out.data(), kOutSize, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out.data(), kOutSize, 0.00001)); } TEST_F(TestArithmeticTestFp32, FloorDivTest) { @@ -263,7 +263,7 @@ TEST_F(TestArithmeticTestFp32, FloorDivTest) { auto tile_data1 = new float[size]; int ret = BroadcastFloorDiv(in_ptr, add_ptr, tile_data0, tile_data1, out, size, fdiv_param); EXPECT_EQ(ret, 0); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -303,7 +303,7 @@ TEST_F(TestArithmeticTestFp32, FloorModTest) { auto tile_data1 = new float[size]; int ret = BroadcastFloorMod(in_ptr, add_ptr, tile_data0, tile_data1, out, size, fmod_param); EXPECT_EQ(ret, 0); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -342,7 +342,7 @@ TEST_F(TestArithmeticTestFp32, LogicalAndTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastLogicalAnd(in_ptr, add_ptr, tile_data0, tile_data1, out, size, logical_and_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -383,7 +383,7 @@ TEST_F(TestArithmeticTestFp32, LogicalOrTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastLogicalOr(in_ptr, add_ptr, tile_data0, tile_data1, out, size, logical_or_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -427,7 +427,7 @@ TEST_F(TestArithmeticTestFp32, MaximumTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastMaximum(in_ptr, add_ptr, tile_data0, tile_data1, out, size, maximum_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -471,7 +471,7 @@ TEST_F(TestArithmeticTestFp32, MinimumTest) { auto tile_data0 = new float[size]; auto tile_data1 = new float[size]; BroadcastMinimum(in_ptr, add_ptr, tile_data0, tile_data1, out, size, minimum_param); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -507,7 +507,7 @@ TEST_F(TestArithmeticTestFp32, SquaredDifferenceTest) { auto tile_data1 = new float[size]; BroadcastSub(in_ptr, add_ptr, tile_data0, tile_data1, out, size, add_param); ElementMul(out, out, out, size); - CompareOutputData(out, correct_out_ptr, size, 0.00001); + ASSERT_EQ(0, CompareOutputData(out, correct_out_ptr, size, 0.00001)); delete[] out; delete[] tile_data0; @@ -581,7 +581,7 @@ TEST_F(TestArithmeticTestFp32, MulFp32) { 2.547916, -3.8308315, -0.56281954, 9.992072, -1.8067529, 1.42546}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -655,7 +655,7 @@ TEST_F(TestArithmeticTestFp32, MulReluFp32) { 2.547916, 0, 0, 9.992072, 0, 1.42546}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -728,7 +728,7 @@ TEST_F(TestArithmeticTestFp32, MulRelu6Fp32) { 1.1281147, 0, 2.547916, 0, 0, 6, 0, 1.42546}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -753,7 +753,7 @@ TEST_F(TestArithmeticTestFp32, MulInt0) { int correct_data[12] = {0, 2, 2, 9, 8, 5, 18, 14, 8, 27, 20, 11}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulInt1) { @@ -774,7 +774,7 @@ TEST_F(TestArithmeticTestFp32, MulInt1) { int correct_data[12] = {0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulInt2) { @@ -795,7 +795,7 @@ TEST_F(TestArithmeticTestFp32, MulInt2) { int correct_data[12] = {0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulInt3) { @@ -816,7 +816,7 @@ TEST_F(TestArithmeticTestFp32, MulInt3) { int correct_data[12] = {0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulReluInt0) { @@ -837,7 +837,7 @@ TEST_F(TestArithmeticTestFp32, MulReluInt0) { int correct_data[12] = {0, 1, 2, 0, 4, 5, 0, 7, 8, 0, 10, 11}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulReluInt1) { @@ -858,7 +858,7 @@ TEST_F(TestArithmeticTestFp32, MulReluInt1) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 7, 8, 9, 10, 11}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulReluInt2) { @@ -879,7 +879,7 @@ TEST_F(TestArithmeticTestFp32, MulReluInt2) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 7, 8, 9, 10, 11}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulReluInt3) { @@ -900,7 +900,7 @@ TEST_F(TestArithmeticTestFp32, MulReluInt3) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 7, 8, 9, 10, 11}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulRelu6Int0) { @@ -921,7 +921,7 @@ TEST_F(TestArithmeticTestFp32, MulRelu6Int0) { int correct_data[12] = {0, 1, 2, 0, 4, 5, 0, 6, 6, 0, 6, 6}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulRelu6Int1) { @@ -942,7 +942,7 @@ TEST_F(TestArithmeticTestFp32, MulRelu6Int1) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 6, 6, 6, 6, 6}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulRelu6Int2) { @@ -963,7 +963,7 @@ TEST_F(TestArithmeticTestFp32, MulRelu6Int2) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 6, 6, 6, 6, 6}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, MulRelu6Int3) { @@ -984,7 +984,7 @@ TEST_F(TestArithmeticTestFp32, MulRelu6Int3) { int correct_data[12] = {0, 0, 0, 0, 0, 0, 6, 6, 6, 6, 6, 6}; - CompareOutputData(out_data, correct_data, 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, correct_data, 12, err_tol)); } TEST_F(TestArithmeticTestFp32, AddReluFp32) { @@ -1053,7 +1053,7 @@ TEST_F(TestArithmeticTestFp32, AddReluFp32) { 11.572254, 9.565813, 1.6258626, 7.629906, 0, 4.0682936, 0, 0, 13.641247, 0, 3.548678}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -1125,7 +1125,7 @@ TEST_F(TestArithmeticTestFp32, AddRelu6Fp32) { 0, 6, 6, 1.6258626, 6, 0, 4.0682936, 0, 0, 6, 0, 3.548678}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -1199,7 +1199,7 @@ TEST_F(TestArithmeticTestFp32, DivReluFp32) { 5.56195764, 0, 0, 0, 0, 0.71874648}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -1271,7 +1271,7 @@ TEST_F(TestArithmeticTestFp32, DivRelu6Fp32) { 0, 0, 6, 0.28698101, 4.01059523, 0.53567243, 5.56195764, 0, 0, 0, 0, 0.71874648}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -1341,7 +1341,7 @@ TEST_F(TestArithmeticTestFp32, EqualFp32) { std::vector correct_out = {0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1}; auto correct_out_ptr = correct_out.data(); - CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct_out_ptr, 24, 0.00001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batch_to_space_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batch_to_space_fp32_test.cc index e43dfd6840..4e73ad62d8 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batch_to_space_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batch_to_space_fp32_test.cc @@ -39,7 +39,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest1) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_1) { @@ -57,7 +57,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_1) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest2) { @@ -76,7 +76,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_2) { @@ -95,7 +95,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest3) { @@ -118,7 +118,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest3) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_3) { @@ -139,7 +139,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_3) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest4) { @@ -164,7 +164,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest4) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_4) { @@ -187,7 +187,7 @@ TEST_F(BatchToSpaceTestFp32, BatchToSpaceTest_crop_4) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc index 267bb716a6..fe1c1bb30b 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc @@ -69,7 +69,7 @@ TEST_F(TestBatchnormFp32, BNTest) { std::cout << output[i] << " ,"; } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -125,7 +125,7 @@ TEST_F(TestBatchnormFp32, FusedBNTest) { std::cout << output[i] << " ,"; } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0.ElementsNum(), 0.001)); input0.set_data(nullptr); input1.set_data(nullptr); @@ -176,7 +176,7 @@ TEST_F(TestBatchnormFp32, easyTest) { std::cout << output[i] << " ,"; } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0.ElementsNum(), 0.001)); input0.set_data(nullptr); input1.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/constant_of_shape_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/constant_of_shape_fp32_test.cc index f0cb9504d4..407b97895e 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/constant_of_shape_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/constant_of_shape_fp32_test.cc @@ -63,7 +63,7 @@ TEST_F(TestConstantOfShapeFp32, Simple) { float *output = reinterpret_cast(outputs_[0]->MutableData()); for (int i = 0; i < 8; ++i) printf("%f ", output[i]); printf("\n"); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete op; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/conv1x1_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/conv1x1_fp32_tests.cc index 560c0b1815..f1e7b668f3 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/conv1x1_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/conv1x1_fp32_tests.cc @@ -27,7 +27,7 @@ using mindspore::lite::Tensor; class TestConv1x1Fp32 : public mindspore::CommonTest { public: - TestConv1x1Fp32() {} + TestConv1x1Fp32() = default; }; TEST_F(TestConv1x1Fp32, Input1x1PrePack1) { @@ -54,7 +54,7 @@ TEST_F(TestConv1x1Fp32, Input1x1PrePack1) { float out[20] = {0}; Conv1x1InputPack(in, out, conv_param, sizeof(float)); - EXPECT_EQ(0, lite::CompareOutputData(out, 20, correct, 20)); + EXPECT_EQ(0, CompareOutputData(out, correct, 20)); delete conv_param; } @@ -95,7 +95,7 @@ TEST_F(TestConv1x1Fp32, Input1x1PrePack2) { float out[28] = {0}; Conv1x1InputPack(in, out, conv_param, sizeof(float)); - CompareOutputData(out, correct, 28, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, correct, 28, 0.0001)); delete conv_param; } @@ -114,7 +114,7 @@ TEST_F(TestConv1x1Fp32, Input1x1PrePack3) { -5.052577, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0}; Conv1x1InputPack(in, out, conv_param, sizeof(float)); - EXPECT_EQ(0, lite::CompareOutputData(out, 18, correct, 18)); + EXPECT_EQ(0, CompareOutputData(out, correct, 18)); delete conv_param; } @@ -136,12 +136,12 @@ TEST_F(TestConv1x1Fp32, Input1x1PrePack4) { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0}; float out[54] = {0}; Conv1x1InputPack(in, out, conv_param, sizeof(float)); - EXPECT_EQ(0, lite::CompareOutputData(out, 54, correct, 54)); + EXPECT_EQ(0, CompareOutputData(out, correct, 54)); delete conv_param; } TEST_F(TestConv1x1Fp32, Conv1x1WeightTest1) { - ConvParameter *conv_param = new ConvParameter(); + auto *conv_param = new ConvParameter(); float in[] = {0.214637, 0.3815, 0.811557, 0.982146, 0.09123, 0.687198, 0.02742, 0.3360, 0.853275, 0.674123, 0.81337, 0.57188, 0.706416, 0.2740942, 0.9045, 0.07155, 0.130864, 0.037712, 0.5369175, 0.97283, 0.92133, 0.3588165, 0.7432479, 0.7886823, 0.870324, 0.230946, 0.343969, @@ -166,13 +166,13 @@ TEST_F(TestConv1x1Fp32, Conv1x1WeightTest1) { conv_param->output_channel_ = 7; float out[96] = {0}; Pack1x1WeightFp32(in, out, conv_param); - EXPECT_EQ(0, lite::CompareOutputData(out, 96, co, 96)); + EXPECT_EQ(0, CompareOutputData(out, co, 96)); delete conv_param; } int Conv1x1TestInit1(std::vector *inputs_, std::vector *outputs_, ConvParameter *conv_param, float **correct) { - lite::Tensor *in_t = new lite::Tensor(kNumberTypeFloat, {1, 2, 3, 4}, schema::Format_NHWC, lite::Tensor::VAR); + auto *in_t = new lite::Tensor(kNumberTypeFloat, {1, 2, 3, 4}, schema::Format_NHWC, lite::Tensor::VAR); in_t->MallocData(); float in[] = {12.216284, 3.3466918, 15.327419, 5.234958, 0.804376, 9.952188, 14.727955, -8.080715, 13.71383, 8.055829, 6.5845337, -9.25232, -4.24519, 11.550042, 9.262012, 1.2780352, @@ -180,21 +180,20 @@ int Conv1x1TestInit1(std::vector *inputs_, std::vectorMutableData(), in, sizeof(float) * 24); inputs_->push_back(in_t); - lite::Tensor *weight_t = - new lite::Tensor(kNumberTypeFloat, {3, 1, 1, 4}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); + auto *weight_t = new lite::Tensor(kNumberTypeFloat, {3, 1, 1, 4}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); weight_t->MallocData(); float weight[] = {-0.7308652, 0.5257509, -0.87825793, -1.123181, -1.2206168, 0.562695, 1.5382664, -0.5020635, 0.8591602, -0.26410004, 1.1262615, 0.073132955}; /* nhwc */ memcpy(weight_t->MutableData(), weight, sizeof(float) * 12); inputs_->push_back(weight_t); - lite::Tensor *bias_t = new lite::Tensor(kNumberTypeFloat, {3}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); + auto *bias_t = new lite::Tensor(kNumberTypeFloat, {3}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); bias_t->MallocData(); float bias[] = {2, 2, 2}; memcpy(bias_t->MutableData(), bias, sizeof(float) * 3); inputs_->push_back(bias_t); - lite::Tensor *out_t = new lite::Tensor(kNumberTypeFloat, {1, 2, 3, 3}, schema::Format_NHWC, lite::Tensor::VAR); + auto *out_t = new lite::Tensor(kNumberTypeFloat, {1, 2, 3, 3}, schema::Format_NHWC, lite::Tensor::VAR); out_t->MallocData(); outputs_->push_back(out_t); @@ -214,18 +213,18 @@ TEST_F(TestConv1x1Fp32, Conv1x1Test1) { std::vector inputs_; std::vector outputs_; auto conv_param = new ConvParameter(); - lite::InnerContext *ctx = new lite::InnerContext(); + auto *ctx = new lite::InnerContext(); ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); float *correct; int total_size = Conv1x1TestInit1(&inputs_, &outputs_, conv_param, &correct); - kernel::Convolution1x1CPUKernel *conv1x1 = + auto *conv1x1 = new kernel::Convolution1x1CPUKernel(reinterpret_cast(conv_param), inputs_, outputs_, ctx, nullptr); conv1x1->Init(); conv1x1->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete conv_param; delete conv1x1; for (auto t : inputs_) delete t; @@ -236,29 +235,28 @@ TEST_F(TestConv1x1Fp32, Conv1x1Test1) { int Conv1x1TestInit2(std::vector *inputs_, std::vector *outputs_, ConvParameter *conv_param, float **correct) { size_t buffer_size; - lite::Tensor *in_t = new lite::Tensor(kNumberTypeFloat, {1, 300, 300, 24}, schema::Format_NHWC, lite::Tensor::VAR); + auto *in_t = new lite::Tensor(kNumberTypeFloat, {1, 300, 300, 24}, schema::Format_NHWC, lite::Tensor::VAR); in_t->MallocData(); std::string input_path = "./conv/conv1x1fp32_input1_nhwc.bin"; auto in = reinterpret_cast(mindspore::lite::ReadFile(input_path.c_str(), &buffer_size)); memcpy(in_t->MutableData(), in, buffer_size); inputs_->push_back(in_t); - lite::Tensor *weight_t = - new lite::Tensor(kNumberTypeFloat, {40, 1, 1, 24}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); + auto *weight_t = new lite::Tensor(kNumberTypeFloat, {40, 1, 1, 24}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); weight_t->MallocData(); std::string weight_path = "./conv/conv1x1fp32_weight1_nhwc.bin"; auto weight = reinterpret_cast(mindspore::lite::ReadFile(weight_path.c_str(), &buffer_size)); memcpy(weight_t->MutableData(), weight, buffer_size); inputs_->push_back(weight_t); - lite::Tensor *bias_t = new lite::Tensor(kNumberTypeFloat, {40}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); + auto *bias_t = new lite::Tensor(kNumberTypeFloat, {40}, schema::Format_NHWC, lite::Tensor::CONST_TENSOR); bias_t->MallocData(); std::string bias_path = "./conv/conv1x1fp32_bias1_nhwc.bin"; auto bias = mindspore::lite::ReadFile(bias_path.c_str(), &buffer_size); memcpy(bias_t->MutableData(), bias, buffer_size); inputs_->push_back(bias_t); - lite::Tensor *out_t = new lite::Tensor(kNumberTypeFloat, {1, 300, 300, 40}, schema::Format_NHWC, lite::Tensor::VAR); + auto *out_t = new lite::Tensor(kNumberTypeFloat, {1, 300, 300, 40}, schema::Format_NHWC, lite::Tensor::VAR); out_t->MallocData(); outputs_->push_back(out_t); @@ -279,17 +277,17 @@ TEST_F(TestConv1x1Fp32, Conv1x1Test2) { std::vector inputs_; std::vector outputs_; auto conv_param = new ConvParameter(); - lite::InnerContext *ctx = new lite::InnerContext(); + auto *ctx = new lite::InnerContext(); ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); float *correct; int total_size = Conv1x1TestInit2(&inputs_, &outputs_, conv_param, &correct); - kernel::Convolution1x1CPUKernel *conv1x1 = + auto *conv1x1 = new kernel::Convolution1x1CPUKernel(reinterpret_cast(conv_param), inputs_, outputs_, ctx, nullptr); conv1x1->Init(); conv1x1->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); /* running warm up */ for (int i = 0; i < 0; i++) { diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/convolution_depthwise_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/convolution_depthwise_fp32_tests.cc index f2091a6c8c..779d363b3c 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/convolution_depthwise_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/convolution_depthwise_fp32_tests.cc @@ -135,14 +135,14 @@ TEST_F(TestConvolutionDwFp32, ConvDwFp32Accuracy) { auto correct_data = reinterpret_cast(mindspore::lite::ReadFile(output_path.c_str(), &output_size)); // compare - CompareOutputData(output_ptr, correct_data, outputs[0]->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_ptr, correct_data, outputs[0]->ElementsNum(), 0.0001)); delete conv_param; - for (unsigned int i = 0; i < inputs.size(); i++) { - delete inputs[i]; + for (auto &input : inputs) { + delete input; } - for (unsigned int i = 0; i < outputs.size(); i++) { - delete outputs[i]; + for (auto &output : outputs) { + delete output; } delete kernel; delete correct_data; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/crop_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/crop_fp32_test.cc index 4bf86f0129..ae58fbca4a 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/crop_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/crop_fp32_test.cc @@ -42,7 +42,7 @@ TEST_F(CropTestFp32, CropTest1) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest2) { @@ -65,7 +65,7 @@ TEST_F(CropTestFp32, CropTest2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest3) { @@ -85,7 +85,7 @@ TEST_F(CropTestFp32, CropTest3) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest4) { @@ -106,7 +106,7 @@ TEST_F(CropTestFp32, CropTest4) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest5) { @@ -127,7 +127,7 @@ TEST_F(CropTestFp32, CropTest5) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest6) { @@ -145,11 +145,11 @@ TEST_F(CropTestFp32, CropTest6) { crop_param.offset_[2] = 0; crop_param.offset_[3] = 0; Crop4DNoParallel(input, output, in_shape, out_shape, &crop_param); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest7) { @@ -164,11 +164,11 @@ TEST_F(CropTestFp32, CropTest7) { crop_param.axis_ = 3; crop_param.offset_[0] = 1; Crop4DNoParallel(input, output, in_shape, out_shape, &crop_param); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest8) { @@ -187,11 +187,11 @@ TEST_F(CropTestFp32, CropTest8) { crop_param.op_parameter_.thread_num_ = 2; Crop4D(input, output, in_shape, out_shape, &crop_param, 0); Crop4D(input, output, in_shape, out_shape, &crop_param, 1); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest9) { @@ -213,11 +213,11 @@ TEST_F(CropTestFp32, CropTest9) { crop_param.op_parameter_.thread_num_ = 2; Crop4D(input, output, in_shape, out_shape, &crop_param, 0); Crop4D(input, output, in_shape, out_shape, &crop_param, 1); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest10) { @@ -237,11 +237,11 @@ TEST_F(CropTestFp32, CropTest10) { crop_param.op_parameter_.thread_num_ = 2; Crop4D(input, output, in_shape, out_shape, &crop_param, 1); Crop4D(input, output, in_shape, out_shape, &crop_param, 0); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(CropTestFp32, CropTest11) { @@ -277,11 +277,11 @@ TEST_F(CropTestFp32, CropTest11) { kernel->Init(); kernel->Run(); - float *output = reinterpret_cast(outputs[0]->MutableData()); + auto *output = reinterpret_cast(outputs[0]->MutableData()); for (int i = 0; i < kOutSize; ++i) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/deconvolution_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/deconvolution_fp32_tests.cc index 3f4a5bce52..db620ac94b 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/deconvolution_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/deconvolution_fp32_tests.cc @@ -25,7 +25,7 @@ namespace mindspore { class TestDeConvolutionFp32 : public mindspore::CommonTest { public: - TestDeConvolutionFp32() {} + TestDeConvolutionFp32() = default; }; TEST_F(TestDeConvolutionFp32, DeConvWeightC4x4Pack1) { @@ -76,7 +76,7 @@ TEST_F(TestDeConvolutionFp32, DeConvWeightC4x4Pack1) { 0.000, 0.000, 0.000, 0.00}; float dst[256] = {0}; PackDeConvWeightFp32(in, dst, 5, 6, 2 * 2); - EXPECT_EQ(0, lite::CompareOutputData(dst, 256, co, 256)); + EXPECT_EQ(0, CompareOutputData(dst, co, 256)); } TEST_F(TestDeConvolutionFp32, DeConvWeightC4x4Pack2) { @@ -91,7 +91,7 @@ TEST_F(TestDeConvolutionFp32, DeConvWeightC4x4Pack2) { -0.293, 18.686, 0.0873, 0, 0, 0, 0, 0, 0, 0, 0, 0}; float dst[64] = {0}; PackDeConvWeightFp32(in, dst, 6, 3, 2 * 1); - EXPECT_EQ(0, lite::CompareOutputData(dst, 64, co, 64)); + EXPECT_EQ(0, CompareOutputData(dst, co, 64)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test1) { @@ -108,15 +108,15 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test1) { float no[] = {-8.646674, -4.7133026, -0.11849791, -4.530405, -5.419181, 14.387108, 2.8319538, -8.511095}; PostConvFuncFp32C8(in, out, bias, 1, 8, 1, ActType_No); - CompareOutputData(out, no, 8, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 8, 0.0001)); float relu[] = {0, 0, 0, 0, 0, 14.387108, 2.8319538, 0}; PostConvFuncFp32C8(in, out, bias, 1, 8, 1, ActType_Relu); - CompareOutputData(out, relu, 8, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, relu, 8, 0.0001)); float corr_relu6[] = {0, 0, 0, 0, 0, 6, 2.8319538, 0}; PostConvFuncFp32C8(in, out, bias, 1, 8, 1, ActType_Relu6); - CompareOutputData(out, corr_relu6, 8, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, corr_relu6, 8, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test2) { @@ -134,15 +134,15 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test2) { float no[] = {-8.646674, 0, -4.7133026, 0, -0.11849791, 0, -4.530405, 0, -5.419181, 0, 14.387108, 0, 2.8319538, 0, -8.511095, 0}; PostConvFuncFp32C8(in, out, bias, 1, 8, 2, ActType_No); - CompareOutputData(out, no, 16, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 16, 0.0001)); float relu[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14.387108, 0, 2.8319538, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 1, 8, 2, ActType_Relu); - CompareOutputData(out, relu, 16, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, relu, 16, 0.0001)); float corr_relu6[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 2.8319538, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 1, 8, 2, ActType_Relu6); - CompareOutputData(out, corr_relu6, 16, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, corr_relu6, 16, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test3) { @@ -161,7 +161,7 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test3) { 11.90631, -4.530405, -0.47735345, -3.7422307, -5.419181, -0.14518678, -8.15199, 14.387108, 8.693133, 8.080041, 2.8319538, 7.177942, -4.409286, -8.511095, -5.110127, -4.992582}; PostConvFuncFp32C8(in, out, bias, 3, 8, 3, ActType_No); - CompareOutputData(out, no, 24, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 24, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test4) { @@ -179,12 +179,12 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test4) { float co32[] = {0, 0, 0, 0, 0, 1.2270198, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14.387108, 8.693133, 0, 0, 2.8319538, 7.177942, 0, 0, 0, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 2, 8, 4, ActType_Relu); - CompareOutputData(out, co32, 32, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, co32, 32, 0.0001)); float co32_relu6[] = {0, 0, 6, 0, 0, 1.2270198, 6, 6, 0, 0, 6, 0.3088621, 0, 0, 0, 0, 0, 0, 0, 6, 6, 6, 6, 0, 2.8319538, 6, 0, 6, 0, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 4, 8, 4, ActType_Relu6); - CompareOutputData(out, co32_relu6, 32, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, co32_relu6, 32, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test5) { @@ -205,19 +205,19 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test5) { -8.334226, 14.387108, 8.693133, 8.080041, -0.30434704, -3.782834, 2.8319538, 7.177942, -4.409286, 12.194644, -7.0295477, -8.511095, -5.110127, -4.992582, -0.31387085, -2.7594402}; PostConvFuncFp32C8(in, out, bias, 5, 8, 5, ActType_No); - CompareOutputData(out, no, 40, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 40, 0.0001)); float relu[] = {0, 0, 8.56133, 0, 0, 0, 1.2270198, 17.954533, 11.086085, 0, 0, 0, 11.90631, 0.3088621, 11.196218, 0, 0, 0, 0, 0, 0, 0, 0, 9.464027, 0, 14.387108, 8.693133, 8.080041, 0, 0, 2.8319538, 7.177942, 0, 12.194644, 0, 0, 0, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 5, 8, 5, ActType_Relu); - CompareOutputData(out, relu, 40, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, relu, 40, 0.0001)); float corr_relu6[] = {0, 0, 6, 0, 0, 0, 1.2270198, 6, 6, 0, 0, 0, 6, 0.3088621, 6, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 6, 6, 6, 0, 0, 2.8319538, 6, 0, 6, 0, 0, 0, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 5, 8, 5, ActType_Relu6); - CompareOutputData(out, corr_relu6, 40, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, corr_relu6, 40, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test6) { @@ -231,13 +231,13 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test6) { float no_3[] = {-9.389655, -5.83877, 7.5724425, 0, 0, 0, -0.8614793, -4.404605, 10.917422, 0, 0, 0, -6.1621623, -0.6315082, -9.140878, 0, 0, 0, 2.0889723, 6.6916203, -5.3981733, 0, 0, 0}; PostConvFuncFp32C8(in, out, bias, 3, 4, 6, ActType_No); - CompareOutputData(out, no_3, 24, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no_3, 24, 0.0001)); float no_6[] = {-9.389655, -5.83877, 7.5724425, -1.4675674, -5.456284, 0.7406984, -0.8614793, -4.404605, 10.917422, 0.11158327, -5.2733865, -0.96367484, -6.1621623, -0.6315082, -9.140878, 9.266748, 13.644127, 8.206812, 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484}; PostConvFuncFp32C8(in, out, bias, 6, 4, 6, ActType_No); - CompareOutputData(out, no_6, 24, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no_6, 24, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test7) { @@ -253,7 +253,7 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test7) { -6.1621623, -0.6315082, -9.140878, 9.266748, 13.644127, 8.206812, 7.091153, 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484, -5.981469}; PostConvFuncFp32C8(in, out, bias, 7, 4, 7, ActType_No); - CompareOutputData(out, no, 28, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 28, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_2) { @@ -269,7 +269,7 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_2) { -0.8614793, -4.404605, 10.917422, 0.11158327, -5.2733865, -0.96367484, -4.731118, -7.576815, 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484, -5.981469, -0.51114964}; PostConvFuncFp32C8(in, out, bias, 16, 2, 16, ActType_No); - CompareOutputData(out, no, 28, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 28, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_4) { @@ -293,7 +293,7 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_4) { 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484, -5.981469, -0.51114964, 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484, -5.981469, -0.51114964}; PostConvFuncFp32C8(in, out, bias, 16, 4, 16, ActType_No); - CompareOutputData(out, no, 64, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 64, 0.0001)); } TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_8) { @@ -317,13 +317,13 @@ TEST_F(TestDeConvolutionFp32, PostConvFuncC8Test8_8) { -6.1621623, -0.6315082, -9.140878, 9.266748, 13.644127, 8.206812, 7.091153, -0.50162584, 2.0889723, 6.6916203, -5.3981733, 11.997365, -9.254076, -5.5964484, -5.981469, -0.51114964}; PostConvFuncFp32C8(in, out, bias, 8, 8, 8, ActType_No); - CompareOutputData(out, no, 64, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, no, 64, 0.0001)); } int DeConvTestInit1(std::vector *inputs_, std::vector *outputs_, ConvParameter *conv_param, float **correct) { std::vector in_dims_nhwc = {1, 5, 7, 2}; - lite::Tensor *in_t = + auto *in_t = new lite::Tensor(kNumberTypeFloat, in_dims_nhwc, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); float in_nchw[] = { @@ -339,7 +339,7 @@ int DeConvTestInit1(std::vector *inputs_, std::vectorpush_back(in_t); std::vector weight_dims_nhwc = {2, 3, 3, 6}; - lite::Tensor *weight_t = + auto *weight_t = new lite::Tensor(kNumberTypeFloat, weight_dims_nhwc, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); weight_t->MallocData(); float weight_nchw[] = { @@ -361,15 +361,14 @@ int DeConvTestInit1(std::vector *inputs_, std::vectorChannel()); inputs_->push_back(weight_t); - lite::Tensor *bias_t = - new lite::Tensor(kNumberTypeFloat, {6}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *bias_t = new lite::Tensor(kNumberTypeFloat, {6}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); bias_t->MallocData(); float bias[] = {-0.19064677, -0.0034778118, 0.63741624, -1.0311537, -1.0288948, 0.71384084}; memcpy(bias_t->MutableData(), bias, sizeof(float) * 6); inputs_->push_back(bias_t); std::vector output_nhwc_dims = {1, 9, 13, 6}; - lite::Tensor *out_t = + auto *out_t = new lite::Tensor(kNumberTypeFloat, output_nhwc_dims, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); out_t->MallocData(); outputs_->push_back(out_t); @@ -476,19 +475,19 @@ int DeConvTestInit1(std::vector *inputs_, std::vector inputs_; std::vector outputs_; - ConvParameter *deconv_param = new ConvParameter(); - lite::InnerContext *ctx = new lite::InnerContext; + auto *deconv_param = new ConvParameter(); + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); float *correct; int total_size = DeConvTestInit1(&inputs_, &outputs_, deconv_param, &correct); - kernel::DeConvolutionCPUKernel *deconv = + auto *deconv = new kernel::DeConvolutionCPUKernel(reinterpret_cast(deconv_param), inputs_, outputs_, ctx, nullptr); deconv->Init(); deconv->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete deconv_param; delete deconv; for (auto t : inputs_) delete t; @@ -547,15 +546,15 @@ TEST_F(TestDeConvolutionFp32, DeConvTest2) { auto deconv_param = new ConvParameter(); float *correct; int total_size = DeConvTestInit2(&inputs_, &outputs_, deconv_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::DeConvolutionCPUKernel *deconv = + auto *deconv = new kernel::DeConvolutionCPUKernel(reinterpret_cast(deconv_param), inputs_, outputs_, ctx, nullptr); deconv->Init(); deconv->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete deconv; for (auto t : inputs_) delete t; @@ -625,15 +624,15 @@ TEST_F(TestDeConvolutionFp32, DeConvTest3) { auto deconv_param = new ConvParameter(); float *correct; int total_size = DeConvTestInit3(&inputs_, &outputs_, deconv_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::DeConvolutionCPUKernel *deconv = + auto *deconv = new kernel::DeConvolutionCPUKernel(reinterpret_cast(deconv_param), inputs_, outputs_, ctx, nullptr); deconv->Init(); deconv->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete deconv; for (auto t : inputs_) delete t; @@ -694,15 +693,15 @@ TEST_F(TestDeConvolutionFp32, DeConvTest4) { auto deconv_param = new ConvParameter(); float *correct; int total_size = DeConvTestInit4(&inputs_, &outputs_, deconv_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::DeConvolutionCPUKernel *deconv = + auto *deconv = new kernel::DeConvolutionCPUKernel(reinterpret_cast(deconv_param), inputs_, outputs_, ctx, nullptr); deconv->Init(); deconv->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); /* running warm up */ for (int i = 0; i < 0; i++) { diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/depth_to_space_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/depth_to_space_fp32_test.cc index 9958bb5a93..e280b04a19 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/depth_to_space_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/depth_to_space_fp32_test.cc @@ -51,7 +51,7 @@ TEST_F(DepthToSpaceTestFp32, DepthToSpaceTest2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } TEST_F(DepthToSpaceTestFp32, DepthToSpaceTest3) { @@ -80,6 +80,6 @@ TEST_F(DepthToSpaceTestFp32, DepthToSpaceTest3) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/detection_post_process_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/detection_post_process_test.cc index 68b5a6eb7f..4e25d70f0f 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/detection_post_process_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/detection_post_process_test.cc @@ -129,33 +129,33 @@ TEST_F(TestDetectionPostProcessFp32, Fast) { op->Init(); op->Run(); - float *output_boxes = reinterpret_cast(outputs_[0]->MutableData()); + auto *output_boxes = reinterpret_cast(outputs_[0]->MutableData()); size_t output_boxes_size; std::string output_boxes_path = "./test_data/detectionPostProcess/output_0.bin"; auto correct_boxes = reinterpret_cast(mindspore::lite::ReadFile(output_boxes_path.c_str(), &output_boxes_size)); - CompareOutputData(output_boxes, correct_boxes, outputs_[0]->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_boxes, correct_boxes, outputs_[0]->ElementsNum(), 0.0001)); - float *output_classes = reinterpret_cast(outputs_[1]->MutableData()); + auto *output_classes = reinterpret_cast(outputs_[1]->MutableData()); size_t output_classes_size; std::string output_classes_path = "./test_data/detectionPostProcess/output_1.bin"; auto correct_classes = reinterpret_cast(mindspore::lite::ReadFile(output_classes_path.c_str(), &output_classes_size)); - CompareOutputData(output_classes, correct_classes, outputs_[1]->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_classes, correct_classes, outputs_[1]->ElementsNum(), 0.0001)); - float *output_scores = reinterpret_cast(outputs_[2]->MutableData()); + auto *output_scores = reinterpret_cast(outputs_[2]->MutableData()); size_t output_scores_size; std::string output_scores_path = "./test_data/detectionPostProcess/output_2.bin"; auto correct_scores = reinterpret_cast(mindspore::lite::ReadFile(output_scores_path.c_str(), &output_scores_size)); - CompareOutputData(output_scores, correct_scores, outputs_[2]->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_scores, correct_scores, outputs_[2]->ElementsNum(), 0.0001)); - float *output_num_det = reinterpret_cast(outputs_[3]->MutableData()); + auto *output_num_det = reinterpret_cast(outputs_[3]->MutableData()); size_t output_num_det_size; std::string output_num_det_path = "./test_data/detectionPostProcess/output_3.bin"; auto correct_num_det = reinterpret_cast(mindspore::lite::ReadFile(output_num_det_path.c_str(), &output_num_det_size)); - CompareOutputData(output_num_det, correct_num_det, outputs_[3]->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_num_det, correct_num_det, outputs_[3]->ElementsNum(), 0.0001)); delete op; for (auto t : inputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/fullconnection_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/fullconnection_fp32_tests.cc index 36705b3530..61dff107d8 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/fullconnection_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/fullconnection_fp32_tests.cc @@ -33,14 +33,14 @@ class TestFcFp32 : public mindspore::CommonTest { int FcTestInit1(std::vector *inputs_, std::vector *outputs_, MatMulParameter *matmal_param, float **correct) { - Tensor *in_t = new Tensor(kNumberTypeFloat, {2, 2, 2, 2}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *in_t = new Tensor(kNumberTypeFloat, {2, 2, 2, 2}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); float in[] = {-3.2366564, -4.7733846, -7.8329225, 16.146885, 5.060793, -6.1471, -1.7680453, -6.5721383, 17.87506, -5.1192183, 10.742863, 1.4536934, 19.693445, 19.45783, 5.063163, 0.5234792}; memcpy(in_t->MutableData(), in, sizeof(float) * in_t->ElementsNum()); inputs_->push_back(in_t); - Tensor *weight_t = new Tensor(kNumberTypeFloat, {3, 8}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *weight_t = new Tensor(kNumberTypeFloat, {3, 8}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); weight_t->MallocData(); float weight[] = {-0.0024438887, 0.0006738146, -0.008169129, 0.0021510671, -0.012470592, -0.0053063435, 0.006050155, 0.008656233, 0.012911413, -0.0028635843, -0.00034080597, -0.0010622552, @@ -49,13 +49,13 @@ int FcTestInit1(std::vector *inputs_, std::vectorMutableData(), weight, sizeof(float) * weight_t->ElementsNum()); inputs_->push_back(weight_t); - Tensor *bias_t = new Tensor(kNumberTypeFloat, {3}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *bias_t = new Tensor(kNumberTypeFloat, {3}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); bias_t->MallocData(); float bias[] = {1.6103756, -0.9872417, 0.546849}; memcpy(bias_t->MutableData(), bias, sizeof(float) * bias_t->ElementsNum()); inputs_->push_back(bias_t); - Tensor *out_t = new Tensor(kNumberTypeFloat, {2, 3}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *out_t = new Tensor(kNumberTypeFloat, {2, 3}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); out_t->MallocData(); outputs_->push_back(out_t); @@ -76,44 +76,43 @@ TEST_F(TestFcFp32, FcTest1) { auto matmul_param = new MatMulParameter(); float *correct; int total_size = FcTestInit1(&inputs_, &outputs_, matmul_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::FullconnectionCPUKernel *fc = + auto *fc = new kernel::FullconnectionCPUKernel(reinterpret_cast(matmul_param), inputs_, outputs_, ctx, nullptr); fc->Init(); fc->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); } int FcTestInit2(std::vector *inputs_, std::vector *outputs_, MatMulParameter *matmal_param, float **correct) { size_t buffer_size; - Tensor *in_t = - new Tensor(kNumberTypeFloat, {20, 4, 2, 10}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); + auto *in_t = new Tensor(kNumberTypeFloat, {20, 4, 2, 10}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); std::string in_path = "./matmul/FcFp32_input1.bin"; auto in_data = mindspore::lite::ReadFile(in_path.c_str(), &buffer_size); memcpy(in_t->MutableData(), in_data, buffer_size); inputs_->push_back(in_t); - Tensor *weight_t = new Tensor(kNumberTypeFloat, {30, 80}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); + auto *weight_t = new Tensor(kNumberTypeFloat, {30, 80}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); weight_t->MallocData(); std::string weight_path = "./matmul/FcFp32_weight1.bin"; auto w_data = mindspore::lite::ReadFile(weight_path.c_str(), &buffer_size); memcpy(weight_t->MutableData(), w_data, buffer_size); inputs_->push_back(weight_t); - Tensor *bias_t = new Tensor(kNumberTypeFloat, {30}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); + auto *bias_t = new Tensor(kNumberTypeFloat, {30}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); bias_t->MallocData(); std::string bias_path = "./matmul/FcFp32_bias1.bin"; auto bias_data = mindspore::lite::ReadFile(bias_path.c_str(), &buffer_size); memcpy(bias_t->MutableData(), bias_data, buffer_size); inputs_->push_back(bias_t); - Tensor *out_t = new Tensor(kNumberTypeFloat, {20, 30}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); + auto *out_t = new Tensor(kNumberTypeFloat, {20, 30}, schema::Format_NCHW, lite::Tensor::Category::CONST_TENSOR); out_t->MallocData(); outputs_->push_back(out_t); @@ -135,26 +134,26 @@ TEST_F(TestFcFp32, FcTest2) { auto matmul_param = new MatMulParameter(); float *correct; int total_size = FcTestInit2(&inputs_, &outputs_, matmul_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::FullconnectionCPUKernel *fc = + auto *fc = new kernel::FullconnectionCPUKernel(reinterpret_cast(matmul_param), inputs_, outputs_, ctx, nullptr); fc->Init(); fc->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); } void FcTestInit3(std::vector *inputs_, std::vector *outputs_, MatMulParameter *matmal_param, float **correct) { - Tensor *in_t = new Tensor(kNumberTypeFloat, {1, 1, 1, 20}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *in_t = new Tensor(kNumberTypeFloat, {1, 1, 1, 20}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); float in[] = {1, 0, 3, 0, 4, 5, 2, 5, 2, 5, 1, 5, 0, 1, 2, 0, 2, 1, 0, 5}; memcpy(in_t->MutableData(), in, sizeof(float) * in_t->ElementsNum()); inputs_->push_back(in_t); - Tensor *weight_t = new Tensor(kNumberTypeFloat, {16, 20}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *weight_t = new Tensor(kNumberTypeFloat, {16, 20}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); weight_t->MallocData(); float weight[] = {0, 5, 5, 3, 0, 5, 3, 1, 0, 1, 3, 0, 5, 5, 2, 4, 0, 1, 1, 2, 3, 0, 5, 5, 4, 4, 1, 4, 1, 1, 5, 3, 3, 1, 0, 3, 1, 2, 4, 5, 3, 4, 4, 0, 3, 5, 0, 3, 4, 1, 0, 1, 3, 4, 0, 5, 2, 5, 0, 4, 2, 2, 2, 2, @@ -169,7 +168,7 @@ void FcTestInit3(std::vector *inputs_, std::vectorMutableData(), weight, sizeof(float) * weight_t->ElementsNum()); inputs_->push_back(weight_t); - Tensor *out_t = new Tensor(kNumberTypeFloat, {1, 16}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *out_t = new Tensor(kNumberTypeFloat, {1, 16}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); out_t->MallocData(); outputs_->push_back(out_t); @@ -185,17 +184,17 @@ TEST_F(TestFcFp32, FcTest3) { auto matmul_param = new MatMulParameter(); float *correct; FcTestInit3(&inputs_, &outputs_, matmul_param, &correct); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::FullconnectionCPUKernel *fc = + auto *fc = new kernel::FullconnectionCPUKernel(reinterpret_cast(matmul_param), inputs_, outputs_, ctx, nullptr); fc->Init(); struct timeval start, end; - gettimeofday(&start, NULL); + gettimeofday(&start, nullptr); for (int i = 0; i < 100000; ++i) fc->Run(); - gettimeofday(&end, NULL); + gettimeofday(&end, nullptr); // printf("## elapsed: %llu\n", 1000000 * (end.tv_sec - start.tv_sec) + end.tv_usec - end.tv_usec); } diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/instance_norm_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/instance_norm_fp32_tests.cc index ae6745bed5..3e400cd7e6 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/instance_norm_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/instance_norm_fp32_tests.cc @@ -69,7 +69,7 @@ TEST_F(TestInstanceNormFp32, INTest1) { std::cout << output[i] << " ,"; } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -124,7 +124,7 @@ TEST_F(TestInstanceNormFp32, INTest2) { std::cout << output[i] << " ,"; } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/l2norm_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/l2norm_fp32_test.cc index fa989dc3ff..39546a0c10 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/l2norm_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/l2norm_fp32_test.cc @@ -92,7 +92,7 @@ TEST_F(TestL2NormFp32, Test1) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol_); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol_)); } // 2thread all axis relu @@ -113,7 +113,7 @@ TEST_F(TestL2NormFp32, Test2) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol_); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol_)); } // 4 thread trailing axis no activation @@ -134,7 +134,7 @@ TEST_F(TestL2NormFp32, Test3) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol_); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol_)); } // 1 thread trailing axis no activation @@ -155,7 +155,7 @@ TEST_F(TestL2NormFp32, Test4) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol_); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol_)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lsh_projection_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lsh_projection_fp32_tests.cc index 54fdc5bc1c..eb1c8d788c 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lsh_projection_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lsh_projection_fp32_tests.cc @@ -71,7 +71,7 @@ TEST_F(TestLshProjectionFp32, Dense1DInputs) { std::vector except_result = {0, 0, 0, 1, 0, 0}; PrintData("output data", output_data, 6); - CompareOutputData(output_data, except_result.data(), 6, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, except_result.data(), 6, 0.000001)); in_tensor0.set_data(nullptr); in_tensor1.set_data(nullptr); @@ -111,7 +111,7 @@ TEST_F(TestLshProjectionFp32, Sparse1DInputs) { std::vector except_result = {0, 5, 8}; PrintData("output data", output_data, 3); - CompareOutputData(output_data, except_result.data(), 3, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, except_result.data(), 3, 0.000001)); in_tensor0.set_data(nullptr); in_tensor1.set_data(nullptr); @@ -155,7 +155,7 @@ TEST_F(TestLshProjectionFp32, Sparse3DInputs) { std::vector except_result = {2, 5, 9}; PrintData("output data", output_data, 3); - CompareOutputData(output_data, except_result.data(), 3, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, except_result.data(), 3, 0.000001)); in_tensor0.set_data(nullptr); in_tensor1.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lstm_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lstm_fp32_tests.cc index cea7665582..472c70b88d 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lstm_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lstm_fp32_tests.cc @@ -23,7 +23,7 @@ namespace mindspore { class LstmFp32 : public mindspore::CommonTest { public: - LstmFp32() {} + LstmFp32() = default; }; void InitLstmParam(LstmParameter *lstm_param) { @@ -124,7 +124,7 @@ void InitLstmForwardCreator(std::vector *inputs, std::vectorpush_back(hidden_state); } -void CompareOutput(lite::Tensor *output, std::vector data) { +void CompareResult(lite::Tensor *output, std::vector data) { for (int i = 0; i < output->ElementsNum(); i++) { std::cout << reinterpret_cast(output->MutableData())[i] << ", "; } @@ -162,20 +162,20 @@ TEST_F(LstmFp32, LstmForwardFp32Accuracy) { std::cout << "==================output data=================" << std::endl; std::vector output0_data = {-0.0702, 0.1225, 0.0876, -0.0357, -0.0227, -0.2294, -0.0345, -0.0108, -0.2002, 0.0451, 0.0853, -0.1205}; - CompareOutput(outputs[0], output0_data); + CompareResult(outputs[0], output0_data); std::vector output1_data = {0.0451, 0.0853, -0.1205}; - CompareOutput(outputs[1], output1_data); + CompareResult(outputs[1], output1_data); std::vector output2_data = {0.0989, 0.2094, -0.4132}; - CompareOutput(outputs[2], output2_data); + CompareResult(outputs[2], output2_data); delete lstm_param; for (unsigned int i = 0; i < inputs.size() - 1; i++) { delete inputs[i]; } - for (unsigned int i = 0; i < outputs.size(); i++) { - delete outputs[i]; + for (auto &output : outputs) { + delete output; } delete kernel; MS_LOG(INFO) << "LstmFp32 forward accuracy passed"; @@ -312,20 +312,20 @@ TEST_F(LstmFp32, LstmBackwardFp32Accuracy) { std::vector output0_data = {-0.2922, -0.1416, 0.0077, -0.0422, -0.0585, 0.2061, -0.2385, -0.0146, -0.1796, -0.0554, -0.0973, 0.1013, -0.3062, -0.1516, -0.0310, 0.0459, -0.0784, 0.0949, 0.0249, -0.0653, -0.0869, -0.1113, -0.2155, -0.0500}; - CompareOutput(outputs[0], output0_data); + CompareResult(outputs[0], output0_data); std::vector output1_data = {0.0249, -0.0653, -0.0869, -0.0422, -0.0585, 0.2061}; - CompareOutput(outputs[1], output1_data); + CompareResult(outputs[1], output1_data); std::vector output2_data = {0.0373, -0.2322, -0.1477, -0.1621, -0.1808, 0.5146}; - CompareOutput(outputs[2], output2_data); + CompareResult(outputs[2], output2_data); delete lstm_param; for (unsigned int i = 0; i < inputs.size() - 1; i++) { delete inputs[i]; } - for (unsigned int i = 0; i < outputs.size(); i++) { - delete outputs[i]; + for (auto &output : outputs) { + delete output; } delete kernel; MS_LOG(INFO) << "LstmFp32 backward accuracy passed"; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/matmul_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/matmul_fp32_tests.cc index 3a1fa9cbe9..9b755531e8 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/matmul_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/matmul_fp32_tests.cc @@ -45,7 +45,7 @@ TEST_F(TestMatMulFp32, Row2Col8Test1) { 0.75, 0.24, 0, 0, 0, 0, 0, 0, 0.66, 0.52, 0, 0, 0, 0, 0, 0}; float out[144] = {0}; RowMajor2Col8Major(in, out, 10, 9); - CompareOutputData(out, co, 144, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, co, 144, 0.0001)); } TEST_F(TestMatMulFp32, Row2Col8Test2) { @@ -65,11 +65,11 @@ TEST_F(TestMatMulFp32, Row2Col8Test2) { 0.24, 0, 0, 0, 0, 0, 0, 0.92, 0.52, 0, 0, 0, 0, 0, 0}; float out[120] = {0}; RowMajor2Col8Major(in, out, 18, 5); - CompareOutputData(out, co, 120, 0.0001); + ASSERT_EQ(0, CompareOutputData(out, co, 120, 0.0001)); } int MMTestInit(std::vector *inputs_, std::vector *outputs_, float *a_ptr, float *b_ptr, - std::vector a_shape, std::vector b_shape, std::vector c_shape) { + const std::vector &a_shape, const std::vector &b_shape, const std::vector &c_shape) { auto in_t = new lite::Tensor(kNumberTypeFloat, a_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); memcpy(in_t->MutableData(), a_ptr, sizeof(float) * in_t->ElementsNum()); @@ -89,8 +89,8 @@ int MMTestInit(std::vector *inputs_, std::vector } int MMTestInit2(std::vector *inputs_, std::vector *outputs_, float *a_ptr, float *b_ptr, - float *bias_ptr, std::vector a_shape, std::vector b_shape, std::vector bias_shape, - std::vector c_shape) { + float *bias_ptr, const std::vector &a_shape, const std::vector &b_shape, + const std::vector &bias_shape, const std::vector &c_shape) { auto in_t = new lite::Tensor(kNumberTypeFloat, a_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); memcpy(in_t->MutableData(), a_ptr, sizeof(float) * in_t->ElementsNum()); @@ -140,7 +140,7 @@ TEST_F(TestMatMulFp32, simple) { mm->Run(); float correct[] = {-0.1256939023733139, -0.07744802534580231, 0.07410638779401779, -0.3049793541431427, -0.027687929570674896, -0.18109679222106934}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete mm; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; @@ -173,7 +173,7 @@ TEST_F(TestMatMulFp32, simple_bias) { mm->Run(); float correct[] = {-0.1256939023733139 + 1, -0.07744802534580231 + 2, 0.07410638779401779 + 3, -0.3049793541431427 + 1, -0.027687929570674896 + 2, -0.18109679222106934 + 3}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete mm; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; @@ -264,7 +264,7 @@ TEST_F(TestMatMulFp32, simple2) { 346, 486, 451, 451, 490, 475, 339, 319, 409, 315, 324, 367, 493, 286, 348, 185, 240, 287, 214, 312, 265, 237, 218, 261, 316, 279, 186, 377, 319, 279, 304, 281, 207, 261, 209, 287, 270, 415, 378, 312, 388, 423, 273, 230, 294, 239, 243, 319, 346}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete mm; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; @@ -294,7 +294,7 @@ TEST_F(TestMatMulFp32, simple_transb) { mm->Init(); mm->Run(); float correct[] = {0.00533547, 0.002545945, 0.062974121, -0.445441471, -0.246223617, -0.142070031}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete mm; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; @@ -348,7 +348,7 @@ TEST_F(TestMatMulFp32, batch) { -17.63555145263672, -8.490625381469727, 5.317771911621094, -14.561882019042969, -7.251564025878906, -2.508212089538574, 5.86458683013916, -3.466249465942383, 8.869029998779297, 25.034008026123047}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete mm; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/non_max_suppression_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/non_max_suppression_fp32_tests.cc index f24f42fadc..9ad141272c 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/non_max_suppression_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/non_max_suppression_fp32_tests.cc @@ -110,7 +110,8 @@ TEST_F(TestNMSFp32, TestCase1) { EXPECT_EQ(0, ret); std::vector expect{0, 0, 3, 0, 0, 0, 0, 0, 5}; - CompareOutputData(reinterpret_cast(out_tensor_.data_c()), expect.data(), output_size, err_tol_); + ASSERT_EQ(0, + CompareOutputData(reinterpret_cast(out_tensor_.data_c()), expect.data(), output_size, err_tol_)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/pad_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/pad_fp32_test.cc index 03c0e2a2ab..94ad358748 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/pad_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/pad_fp32_test.cc @@ -131,7 +131,7 @@ TEST_F(TestPadFp32, TestPad1) { 20.0, 21.0, 22.0, 23.0, 21.0, 22.0, 23.0, 18.0, 19.0, 20.0, 15.0, 16.0, 17.0, 12.0, 13.0, 14.0, 9.0, 10.0, 11.0, 6.0, 7.0, 8.0, 3.0, 4.0, 5.0, 0.0, 1.0, 2.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 9.0, 10.0, 11.0, 6.0, 7.0, 8.0, 3.0, 4.0, 5.0, 0.0, 1.0, 2.0}; - CompareOutputData(out_data, expect.data(), 432, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 432, err_tol)); } TEST_F(TestPadFp32, TestPad2) { @@ -166,7 +166,7 @@ TEST_F(TestPadFp32, TestPad2) { 16.0, 17.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 18.0, 19.0, 20.0, 15.0, 16.0, 17.0, 12.0, 13.0, 14.0, 9.0, 10.0, 11.0, 6.0, 7.0, 8.0, 3.0, 4.0, 5.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 6.0, 7.0, 8.0, 3.0, 4.0, 5.0, 0.0, 1.0, 2.0}; - CompareOutputData(out_data, expect.data(), 300, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 300, err_tol)); } TEST_F(TestPadFp32, TestPad3) { @@ -202,7 +202,7 @@ TEST_F(TestPadFp32, TestPad3) { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0}; - CompareOutputData(out_data, expect.data(), 300, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 300, err_tol)); } TEST_F(TestPadFp32, TestPad4) { @@ -238,7 +238,7 @@ TEST_F(TestPadFp32, TestPad4) { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0}; - CompareOutputData(out_data, expect.data(), 300, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 300, err_tol)); } TEST_F(TestPadFp32, TestPad5) { @@ -274,6 +274,6 @@ TEST_F(TestPadFp32, TestPad5) { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0}; - CompareOutputData(out_data, expect.data(), 300, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 300, err_tol)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/power_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/power_fp32_tests.cc index 4bfc59b87c..81aa537599 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/power_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/power_fp32_tests.cc @@ -26,7 +26,8 @@ class TestPowerFp32 : public mindspore::CommonTest { }; int PowerTestInit(std::vector *inputs_, std::vector *outputs_, float *a_ptr, - float *b_ptr, std::vector a_shape, std::vector b_shape, std::vector c_shape) { + float *b_ptr, const std::vector &a_shape, const std::vector &b_shape, + const std::vector &c_shape) { auto in_t = new lite::Tensor(kNumberTypeFloat, a_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); memcpy(in_t->MutableData(), a_ptr, sizeof(float) * in_t->ElementsNum()); @@ -46,7 +47,7 @@ int PowerTestInit(std::vector *inputs_, std::vector *inputs_, std::vector *outputs_, float *a_ptr, - std::vector a_shape, std::vector c_shape) { + const std::vector &a_shape, const std::vector &c_shape) { auto in_t = new lite::Tensor(kNumberTypeFloat, a_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); memcpy(in_t->MutableData(), a_ptr, sizeof(float) * in_t->ElementsNum()); @@ -74,12 +75,11 @@ TEST_F(TestPowerFp32, Simple) { auto ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::PowerCPUKernel *op = - new kernel::PowerCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); + auto *op = new kernel::PowerCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); op->Init(); op->Run(); float correct[] = {1, 64, 2187, 65536}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete op; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; @@ -99,12 +99,11 @@ TEST_F(TestPowerFp32, Broadcast) { auto ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::PowerCPUKernel *op = - new kernel::PowerCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); + auto *op = new kernel::PowerCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); op->Init(); op->Run(); float correct[] = {1, 4, 9, 16}; - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete op; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/reduce_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/reduce_fp32_tests.cc index 55fd7bc90e..ede2906c49 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/reduce_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/reduce_fp32_tests.cc @@ -116,7 +116,7 @@ TEST_F(TestReduceFp32, Mean1) { kernel_->Run(); int output_size = 24; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } // thread num 2 reduce_to_end @@ -143,7 +143,7 @@ TEST_F(TestReduceFp32, Mean2) { kernel_->Run(); int output_size = 2; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } // thread num 1 @@ -171,7 +171,7 @@ TEST_F(TestReduceFp32, Mean3) { kernel_->Run(); int output_size = 2; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, MeanAllAxis) { @@ -197,7 +197,7 @@ TEST_F(TestReduceFp32, MeanAllAxis) { kernel_->Run(); int output_size = 1; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, Sum) { @@ -224,7 +224,7 @@ TEST_F(TestReduceFp32, Sum) { kernel_->Run(); int output_size = 24; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } // sum reduce_to_end @@ -253,7 +253,7 @@ TEST_F(TestReduceFp32, Sum2) { kernel_->Run(); int output_size = 32; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, Sum3) { @@ -281,7 +281,7 @@ TEST_F(TestReduceFp32, Sum3) { kernel_->Run(); int output_size = 32; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, SumAllAxis) { @@ -306,7 +306,7 @@ TEST_F(TestReduceFp32, SumAllAxis) { kernel_->Run(); int output_size = 1; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, Max) { @@ -333,7 +333,7 @@ TEST_F(TestReduceFp32, Max) { kernel_->Run(); int output_size = 24; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, Min) { @@ -360,7 +360,7 @@ TEST_F(TestReduceFp32, Min) { kernel_->Run(); int output_size = 24; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, Prod) { @@ -388,7 +388,7 @@ TEST_F(TestReduceFp32, Prod) { kernel_->Run(); int output_size = 24; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, SumSquare) { @@ -414,7 +414,7 @@ TEST_F(TestReduceFp32, SumSquare) { kernel_->Run(); int output_size = 8; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, SumSquare2) { @@ -443,7 +443,7 @@ TEST_F(TestReduceFp32, SumSquare2) { kernel_->Run(); int output_size = 32; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } TEST_F(TestReduceFp32, ASum) { @@ -471,6 +471,6 @@ TEST_F(TestReduceFp32, ASum) { kernel_->Run(); int output_size = 32; - CompareOutputData(out, correct, output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(out, correct, output_size, err_tol)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_bilinear_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_bilinear_fp32_tests.cc index 9d78eca946..6a4458fd0c 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_bilinear_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_bilinear_fp32_tests.cc @@ -87,7 +87,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest1) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*1 @@ -104,7 +104,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest2) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*2 @@ -121,7 +121,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest3) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*1 @@ -138,7 +138,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest4) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*2 @@ -155,7 +155,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest5) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*4 @@ -172,7 +172,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest6) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*1 @@ -189,7 +189,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest7) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*4 @@ -206,7 +206,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest8) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*2 @@ -223,7 +223,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest9) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 3*3 @@ -240,7 +240,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest10) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*4 @@ -257,7 +257,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest11) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 @@ -285,7 +285,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest12) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 align corners @@ -320,7 +320,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest13) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 thread_num 2 @@ -349,7 +349,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest14) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 thread_num 4 @@ -379,7 +379,7 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest15) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 5*5 -> 2*2 @@ -405,6 +405,6 @@ TEST_F(TestResizeBilinearFp32, ResizeBilinearTest16) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_nearest_neighbor_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_nearest_neighbor_fp32_tests.cc index 81c6b3c4b4..d7e4a2eadc 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_nearest_neighbor_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_nearest_neighbor_fp32_tests.cc @@ -81,7 +81,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest1) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*1 @@ -98,7 +98,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest2) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*2 @@ -115,7 +115,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest3) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*1 @@ -132,7 +132,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest4) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*2 @@ -149,7 +149,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest5) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 1*4 @@ -166,7 +166,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest6) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*1 @@ -183,7 +183,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest7) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 2*4 @@ -200,7 +200,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest8) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*2 @@ -217,7 +217,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest9) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 3*3 @@ -234,7 +234,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest10) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2 -> 4*4 @@ -251,7 +251,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest11) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 @@ -279,7 +279,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest12) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 thread_num 2 @@ -307,7 +307,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest13) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*2*2*5 -> 2*4*4*5 thread_num 4 @@ -335,7 +335,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest14) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 4*4 -> 6*6 align_corners True @@ -354,7 +354,7 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest15) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } // 2*7*5*8 -> 2*14*10*8 align_corners True @@ -546,6 +546,6 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest16) { auto ret = kernel_->Run(); EXPECT_EQ(0, ret); - CompareOutputData(output_data, expect.data(), output_size, err_tol); + ASSERT_EQ(0, CompareOutputData(output_data, expect.data(), output_size, err_tol)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/roi_pooling_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/roi_pooling_fp32_tests.cc index 5feca86088..d018ec9818 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/roi_pooling_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/roi_pooling_fp32_tests.cc @@ -26,7 +26,8 @@ class TestROIPoolingFp32 : public mindspore::CommonTest { }; int ROIPoolingTestInit(std::vector *inputs_, std::vector *outputs_, float *a_ptr, - float *b_ptr, std::vector a_shape, std::vector b_shape, std::vector c_shape) { + float *b_ptr, const std::vector &a_shape, const std::vector &b_shape, + const std::vector &c_shape) { auto in_t = new lite::Tensor(kNumberTypeFloat, a_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR); in_t->MallocData(); memcpy(in_t->MutableData(), a_ptr, sizeof(float) * in_t->ElementsNum()); @@ -61,15 +62,14 @@ TEST_F(TestROIPoolingFp32, Simple) { auto ctx = new lite::InnerContext; ctx->thread_num_ = 3; ASSERT_EQ(lite::RET_OK, ctx->Init()); - kernel::ROIPoolingCPUKernel *op = - new kernel::ROIPoolingCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); + auto *op = new kernel::ROIPoolingCPUKernel(reinterpret_cast(param), inputs_, outputs_, ctx, nullptr); op->Init(); op->Run(); float correct[] = {25, 31, 34, 35, 25, 31, 34, 35}; float *output = reinterpret_cast(outputs_[0]->MutableData()); for (int i = 0; i < 8; ++i) printf("%f ", output[i]); printf("\n"); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0.0001)); delete op; for (auto t : inputs_) delete t; for (auto t : outputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/scale_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/scale_fp32_tests.cc index 08a9e93b0c..970ae8461f 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/scale_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/scale_fp32_tests.cc @@ -112,7 +112,7 @@ TEST_F(TestScaleFp32, ScaleNoAct) { std::vector expect{1.0, 3.0, 7.0, 4.0, 9.0, 16.0, 7.0, 15.0, 25.0, 10.0, 21.0, 34.0}; - CompareOutputData(out_data, expect.data(), 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 12, err_tol)); } TEST_F(TestScaleFp32, ScaleRelu) { @@ -134,7 +134,7 @@ TEST_F(TestScaleFp32, ScaleRelu) { std::vector expect{0.0, 0.0, 1.0, 0.0, 3.0, 10.0, 1.0, 9.0, 19.0, 4.0, 15.0, 28.0}; - CompareOutputData(out_data, expect.data(), 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 12, err_tol)); } TEST_F(TestScaleFp32, ScaleRelu6) { std::vector input_shape{1, 2, 2, 3}; @@ -155,6 +155,6 @@ TEST_F(TestScaleFp32, ScaleRelu6) { std::vector expect{0.0, 0.0, 1.0, 0.0, 3.0, 6.0, 1.0, 6.0, 6.0, 4.0, 6.0, 6.0}; - CompareOutputData(out_data, expect.data(), 12, err_tol); + ASSERT_EQ(0, CompareOutputData(out_data, expect.data(), 12, err_tol)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_batch_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_batch_fp32_tests.cc index 5f9bca0975..4d5c65c87a 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_batch_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_batch_fp32_tests.cc @@ -39,11 +39,11 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest4) { param.block_sizes_[0] = 2; param.block_sizes_[1] = 1; DoSpaceToBatchNHWC(input.data(), out, param.block_sizes_, in_shape.data(), out_shape.data()); - for (unsigned int i = 0; i < kOutSize; ++i) { - std::cout << out[i] << " "; + for (float i : out) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest5) { @@ -61,7 +61,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest5) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest6) { @@ -79,7 +79,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest6) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest7) { @@ -101,7 +101,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest7) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest8) { @@ -120,7 +120,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest8) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest9) { @@ -140,7 +140,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest9) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest10) { @@ -166,6 +166,6 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest10) { std::cout << out[i] << " "; } std::cout << "\n"; - CompareOutputData(out, expect_out.data(), kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, expect_out.data(), kOutSize, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_depth_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_depth_fp32_tests.cc index 309a39309b..8b29459961 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_depth_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_depth_fp32_tests.cc @@ -44,7 +44,7 @@ TEST_F(SpaceToDepthTestFp32, SpaceToDepthTest1) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, out_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, out_size, 0.000001)); } TEST_F(SpaceToDepthTestFp32, SpaceToDepthTest2) { @@ -89,7 +89,7 @@ TEST_F(SpaceToDepthTestFp32, SpaceToDepthTest2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output.data(), expect_out, out_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_out, out_size, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/sparse_to_dense_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/sparse_to_dense_fp32_tests.cc index ba96fc08d8..198a86e96e 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/sparse_to_dense_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/sparse_to_dense_fp32_tests.cc @@ -99,7 +99,7 @@ TEST_F(TestSparseToDenseFp32, SparseToDense_test1) { 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); @@ -183,7 +183,7 @@ TEST_F(TestSparseToDenseFp32, SparseToDense_test2) { 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); @@ -265,7 +265,7 @@ TEST_F(TestSparseToDenseFp32, SparseToDense_test3) { std::vector except_result = {0, 1, 0, 1, 1, 0, 0, 0, 0, 0}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); @@ -347,7 +347,7 @@ TEST_F(TestSparseToDenseFp32, SparseToDense_test4) { std::vector except_result = {0, 0, 0, 0, 0, 1, 0, 0, 0, 0}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); @@ -431,7 +431,7 @@ TEST_F(TestSparseToDenseFp32, SparseToDense_test5) { 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/stack_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/stack_fp32_test.cc index 7458f242d3..9780a75d1f 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/stack_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/stack_fp32_test.cc @@ -36,11 +36,11 @@ TEST_F(StackTestFp32, StackTest1) { float expect_out[kOutSize] = {1, 4, 7, 2, 5, 8, 3, 6, 9, 10, 40, 70, 20, 50, 80, 30, 60, 90}; float output[kOutSize]; DoStack(input, 3, shape.data(), shape.size(), axis, output); - for (int i = 0; i < kOutSize; ++i) { - std::cout << output[i] << " "; + for (float i : output) { + std::cout << i << " "; } std::cout << "\n"; - CompareOutputData(output, expect_out, kOutSize, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, expect_out, kOutSize, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/strided_slice_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/strided_slice_fp32_tests.cc index 8b3e2e65fd..728b207235 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/strided_slice_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/strided_slice_fp32_tests.cc @@ -85,7 +85,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice1) { std::cout << correct[0] << " , " << correct[1]; std::cout << std::endl; - CompareOutputData(output_data, correct, 2, 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 2, 0.00001)); delete strided_slice_param; MS_LOG(INFO) << "Teststrided_sliceFp32 passed"; @@ -111,7 +111,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice2) { // runtime part DoStridedSlice(input_data, output_data, strided_slice_param); - CompareOutputData(output_data, correct, 9, 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 9, 0.00001)); delete strided_slice_param; } @@ -162,7 +162,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice3) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 2, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 2, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -199,7 +199,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice4) { output_tensor.set_data_type(input_tensor.data_type()); output_tensor.set_shape(output_shape); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); strided_slice_param->op_parameter_.type_ = schema::PrimitiveType_StridedSlice; @@ -212,7 +212,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice4) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 4, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 4, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -256,7 +256,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice5) { output_tensor.set_data_type(input_tensor.data_type()); output_tensor.set_shape(output_shape); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); strided_slice_param->op_parameter_.type_ = schema::PrimitiveType_StridedSlice; @@ -269,7 +269,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice5) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 12, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 12, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -313,7 +313,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice6) { output_tensor.set_data_type(input_tensor.data_type()); output_tensor.set_shape(output_shape); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 2; ASSERT_EQ(lite::RET_OK, ctx->Init()); strided_slice_param->op_parameter_.type_ = schema::PrimitiveType_StridedSlice; @@ -326,7 +326,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice6) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 8, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 8, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -375,7 +375,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice7) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 1, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 1, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -432,7 +432,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice8) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 5, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 5, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } @@ -582,7 +582,7 @@ TEST_F(TestStridedSliceFp32, StridedSlice9) { kernel->Run(); delete ctx; - CompareOutputData(output_data, correct, 490, 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data, correct, 490, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/transpose_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/transpose_fp32_tests.cc index b04c057f1a..3f8d44d14e 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/transpose_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/transpose_fp32_tests.cc @@ -67,7 +67,7 @@ TEST_F(TestTransposeFp32, TransposeFp32_axes4) { auto ret = DoTransposeFp32(in, out, input_shape, output_shape, param, 0, 3, nullptr, nullptr); ASSERT_EQ(ret, 0); delete param; - CompareOutputData(out, correct, 24, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, correct, 24, 0.000001)); } TEST_F(TestTransposeFp32, TransposeFp32_axes3) { @@ -107,7 +107,7 @@ TEST_F(TestTransposeFp32, TransposeFp32_axes3) { auto ret = DoTransposeFp32(in, out, input_shape, output_shape, param, 0, 3, nullptr, nullptr); ASSERT_EQ(ret, 0); delete param; - CompareOutputData(out, correct, 24, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, correct, 24, 0.000001)); } TEST_F(TestTransposeFp32, TransposeFp32_axes2) { @@ -148,7 +148,7 @@ TEST_F(TestTransposeFp32, TransposeFp32_axes2) { auto ret = DoTransposeFp32(in, out, input_shape, output_shape, param, 0, 6, nullptr, nullptr); ASSERT_EQ(ret, 0); delete param; - CompareOutputData(out, correct, 24, 0.000001); + ASSERT_EQ(0, CompareOutputData(out, correct, 24, 0.000001)); } TEST_F(TestTransposeFp32, TransposeFp32_test5) { @@ -213,7 +213,7 @@ TEST_F(TestTransposeFp32, TransposeFp32_test5) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output.data(), correct, 24, 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), correct, 24, 0.000001)); input_tensor.set_data(nullptr); output_tensor.set_data(nullptr); } diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/activation_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/activation_grad_fp32_tests.cc index c7b7e0a212..f5863fffc7 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/activation_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/activation_grad_fp32_tests.cc @@ -21,7 +21,6 @@ #include "src/common/log_adapter.h" #include "common/common_test.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "mindspore/lite/src/kernel_registry.h" #include "mindspore/lite/src/tensor.h" #include "mindspore/lite/src/lite_kernel.h" @@ -71,7 +70,7 @@ TEST_F(TestActGradFp32, ReluGradFp32) { std::string output_path = "./test_data/activationGrad/relu_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); @@ -117,7 +116,7 @@ TEST_F(TestActGradFp32, Relu6GradFp32) { std::cout << std::endl; std::string output_path = "./test_data/activationGrad/relu6_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); @@ -163,7 +162,7 @@ TEST_F(TestActGradFp32, LReluGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/activationGrad/lrelu_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); @@ -209,10 +208,10 @@ TEST_F(TestActGradFp32, SigmoidGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/activationGrad/sigmoid_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); - // lite::CompareOutput(output_data, output_data_size, output_path); + // CompareOutput(output_data, output_data_size, output_path); delete[] input_data; delete[] output_data; @@ -256,7 +255,7 @@ TEST_F(TestActGradFp32, tanhGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/activationGrad/tanh_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); @@ -303,7 +302,7 @@ TEST_F(TestActGradFp32, hswishGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/activationGrad/hswish_out_50.bin"; - int res = lite::CompareRelativeOutput(output_data, output_path); + int res = CompareRelativeOutput(output_data, output_path); EXPECT_EQ(res, 0); @@ -312,5 +311,4 @@ TEST_F(TestActGradFp32, hswishGradFp32) { delete[] yt_data; MS_LOG(INFO) << "hswishGradFp32 passed"; } - } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/arithmetic_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/arithmetic_grad_fp32_tests.cc index 53455f9386..1b98f1db55 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/arithmetic_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/arithmetic_grad_fp32_tests.cc @@ -19,7 +19,6 @@ #include "src/common/log_adapter.h" #include "common/common_test.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "nnacl/fp32/reduce.h" #include "src/runtime/kernel/arm/fp32_grad/arithmetic_grad.h" #include "src/kernel_registry.h" @@ -129,10 +128,10 @@ TEST_F(TestArithmeticGradFp32, TestAddGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_1_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_1_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -167,10 +166,10 @@ TEST_F(TestArithmeticGradFp32, TestAddGrad2Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_1_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_1_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -207,10 +206,10 @@ TEST_F(TestArithmeticGradFp32, TestAddGrad3Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_8_dx2_5_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_8_dx1_5_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); @@ -248,10 +247,10 @@ TEST_F(TestArithmeticGradFp32, TestSubGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_2_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_2_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); @@ -289,10 +288,10 @@ TEST_F(TestArithmeticGradFp32, TestSubGrad2Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_3_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_3_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); @@ -338,10 +337,10 @@ TEST_F(TestArithmeticGradFp32, TestMulGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_4_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_4_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -377,10 +376,10 @@ TEST_F(TestArithmeticGradFp32, TestMulGrad2Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_4_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_4_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -417,10 +416,10 @@ TEST_F(TestArithmeticGradFp32, TestMulGrad3Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_9_dx1_5_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_9_dx2_5_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -457,10 +456,10 @@ TEST_F(TestArithmeticGradFp32, TestMulGrad4Fp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_9_dx1_5_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_9_dx2_5_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -497,10 +496,10 @@ TEST_F(TestArithmeticGradFp32, TestDivGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/operators/arithmetic_fp32_5_dx1_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), output_path)); std::string dx2_path = "./test_data/operators/arithmetic_fp32_5_dx2_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, dx2_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -537,10 +536,10 @@ TEST_F(TestArithmeticGradFp32, TestDivGrad2Fp32) { std::cout << std::endl; std::string dx2_path = "./test_data/operators/arithmetic_fp32_6_dx2_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), dx2_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[1]->MutableData()), dx2_path)); std::string output_path = "./test_data/operators/arithmetic_fp32_6_dx1_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, output_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, output_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); @@ -578,10 +577,10 @@ TEST_F(TestArithmeticGradFp32, TestDivGrad3Fp32) { std::cout << std::endl; std::string dx1_path = "./test_data/operators/arithmetic_fp32_10_dx1_5_4_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), dx1_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), dx1_path)); std::string output_path = "./test_data/operators/arithmetic_fp32_10_dx2_5_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, output_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, output_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); @@ -618,10 +617,10 @@ TEST_F(TestArithmeticGradFp32, Test3DDivGrad2Fp32) { std::cout << std::endl; std::string dx1_path = "./test_data/operators/arithmetic_fp32_7_dx1_4_5_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), dx1_path)); + EXPECT_EQ(0, CompareRelativeOutput(reinterpret_cast(outputs[0]->MutableData()), dx1_path)); std::string output_path = "./test_data/operators/arithmetic_fp32_7_dx2_1_1_6.bin"; - EXPECT_EQ(0, lite::CompareRelativeOutput(output_ptr, output_path)); + EXPECT_EQ(0, CompareRelativeOutput(output_ptr, output_path)); for (auto tensor : all_tensors) { delete[] reinterpret_cast(tensor->MutableData()); tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bias_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bias_grad_fp32_tests.cc index 155f20e44c..03659e39ee 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bias_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bias_grad_fp32_tests.cc @@ -61,7 +61,7 @@ TEST_F(TestBiasGradFp32, BiasGradFp32) { } std::cout << std::endl; std::string output_path = "./test_data/operators/biasgradfp32_1_db_7.bin"; - lite::CompareOutput(output_data, 7, output_path); + CompareOutput(output_data, 7, output_path); delete[] input_data; delete[] output_data; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bn_grad_fp32_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bn_grad_fp32_test.cc index c9c5601550..913d685725 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bn_grad_fp32_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/bn_grad_fp32_test.cc @@ -18,7 +18,6 @@ #include "src/common/log_adapter.h" #include "common/common_test.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "src/runtime/kernel/arm/fp32_grad/bn_grad.h" #include "nnacl/fp32_grad/batch_norm.h" #include "nnacl/fp32/batchnorm.h" @@ -93,18 +92,18 @@ TEST_F(TestBNGradFp32, BNGradFp32) { auto dx = reinterpret_cast(outputs[0]->MutableData()); for (int i = 0; i < 7; i++) std::cout << dx[i] << " "; std::cout << "\n"; - auto res = mindspore::lite::CompareRelativeOutput(dx, "./test_data/bngrad/output_dx_2_4_5_3.bin"); + auto res = CompareRelativeOutput(dx, "./test_data/bngrad/output_dx_2_4_5_3.bin"); std::cout << "\n=======dscale=======\n"; auto dscale = reinterpret_cast(outputs[1]->MutableData()); for (int i = 0; i < channels; i++) std::cout << dscale[i] << " "; std::cout << "\n"; - res = mindspore::lite::CompareRelativeOutput(dscale, "./test_data/bngrad/output_dscale_3.bin"); + res = CompareRelativeOutput(dscale, "./test_data/bngrad/output_dscale_3.bin"); EXPECT_EQ(res, 0); std::cout << "==========dbias==========\n"; auto dbias = reinterpret_cast(outputs[2]->MutableData()); for (int i = 0; i < 3; i++) std::cout << dbias[i] << " "; std::cout << "\n"; - res = mindspore::lite::CompareRelativeOutput(dbias, "./test_data/bngrad/output_dbias_3.bin"); + res = CompareRelativeOutput(dbias, "./test_data/bngrad/output_dbias_3.bin"); EXPECT_EQ(res, 0); for (auto v : inputs) { delete[] reinterpret_cast(v->MutableData()); @@ -192,9 +191,9 @@ TEST_F(TestBNGradFp32, BNTtrainFp32) { for (int i = 0; i < channels; i++) std::cout << save_var[i] << " "; std::cout << "\n"; delete[] reinterpret_cast(x_tensor->MutableData()); - auto res = mindspore::lite::CompareRelativeOutput(save_mean, "./test_data/bngrad/running_mean_3.bin"); + auto res = CompareRelativeOutput(save_mean, "./test_data/bngrad/running_mean_3.bin"); EXPECT_EQ(res, 0); - res = mindspore::lite::CompareRelativeOutput(save_var, "./test_data/bngrad/running_var_3.bin"); + res = CompareRelativeOutput(save_var, "./test_data/bngrad/running_var_3.bin"); EXPECT_EQ(res, 0); x_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/convolution_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/convolution_grad_fp32_tests.cc index 26894ad973..080cb1d17c 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/convolution_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/convolution_grad_fp32_tests.cc @@ -20,7 +20,6 @@ #include "src/common/log_adapter.h" #include "common/common_test.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "mindspore/lite/src/runtime/kernel/arm/fp32_grad/convolution.h" #include "mindspore/lite/src/runtime/kernel/arm/fp32_grad/convolution_grad_filter.h" #include "mindspore/lite/src/runtime/kernel/arm/fp32_grad/convolution_grad_input.h" @@ -131,7 +130,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dw_32_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -205,7 +204,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32InputGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dx_1_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(dx_data, output_path); + auto res = CompareRelativeOutput(dx_data, output_path); EXPECT_EQ(res, 0); delete[] dx_data; delete[] w_data; @@ -276,7 +275,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32GroupFilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dw_g3_18_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -348,7 +347,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32GroupInputGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dx_g3_1_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(dx_data, output_path); + auto res = CompareRelativeOutput(dx_data, output_path); EXPECT_EQ(res, 0); delete[] dx_data; delete[] w_data; @@ -421,7 +420,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32GroupDilationFilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dw_g3_d2_18_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; delete[] dy_data; @@ -488,7 +487,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32GroupDilationInputGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dx_g3_d2_1_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(dx_data, output_path); + auto res = CompareRelativeOutput(dx_data, output_path); EXPECT_EQ(res, 0); delete[] dx_data; delete[] w_data; @@ -563,7 +562,7 @@ TEST_F(TestConvolutionGradFp32, ConvGroupDilation) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_y_g3_d2_1_26_26_18.bin"; - auto res = lite::CompareRelativeOutput(y_data, output_path); + auto res = CompareRelativeOutput(y_data, output_path); EXPECT_EQ(res, 0); delete[] y_data; @@ -661,7 +660,7 @@ TEST_F(TestConvolutionGradFp32, ConvFp32Dilation2Group2Stride2FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_dw_d2_g2_s2_12_2_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -761,7 +760,7 @@ TEST_F(TestConvolutionGradFp32, ConvGroup2Dilation2Stride2) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/conv/convfp32_inputdx_d2_g2_s2_2_4_32_32.bin"; - auto res = lite::CompareRelativeOutput(dx_data, output_path); + auto res = CompareRelativeOutput(dx_data, output_path); EXPECT_EQ(res, 0); delete[] dx_data; delete[] w_data; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/deconvolution_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/deconvolution_grad_fp32_tests.cc index 35d298e338..571ffa81f8 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/deconvolution_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/deconvolution_grad_fp32_tests.cc @@ -17,10 +17,8 @@ #include #include #include -// #include "utils/log_adapter.h" #include "common/common_test.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "mindspore/lite/src/runtime/kernel/arm/fp32_grad/deconvolution_grad_filter.h" #include "mindspore/lite/nnacl/conv_parameter.h" #include "mindspore/lite/src/kernel_registry.h" @@ -114,7 +112,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_9_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -213,7 +211,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32Dilation2FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_d2_9_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -312,7 +310,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32Dilation2Group3FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_d2_g3_3_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -411,7 +409,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32Dilation2Group3Stride1FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_d2_g3_s1_3_3_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -510,7 +508,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32Dilation2Group2Stride2FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_d2_g2_s2_6_4_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); @@ -609,7 +607,7 @@ TEST_F(TestDeConvolutionGradFp32, DeConvFp32Dilation2Group12Stride2FilterGrad) { printf("single thread running time : %f ms\n", time_avg / 1000.0f); std::string output_path = "./test_data/deconv/deconvfp32_dw_d2_g12_s2_12_1_3_3.bin"; - auto res = lite::CompareRelativeOutput(dw_data, output_path); + auto res = CompareRelativeOutput(dw_data, output_path); EXPECT_EQ(res, 0); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/network_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/network_test.cc index 7cb310e0aa..0e1275cbdf 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/network_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/network_test.cc @@ -30,7 +30,6 @@ #include "include/errorcode.h" #include "src/common/log_adapter.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "src/kernel_registry.h" #include "src/runtime/kernel/arm/fp32_grad/convolution.h" @@ -418,7 +417,7 @@ TEST_F(NetworkTest, tuning_layer) { } std::cout << std::endl; std::string output_path = "./test_data/train/train_output_32_10.bin"; - auto error = lite::RelativeOutputError(outData, output_path); + auto error = RelativeOutputError(outData, output_path); EXPECT_LT(error, 2e-3); ret = session->RunGraph(); @@ -433,7 +432,7 @@ TEST_F(NetworkTest, tuning_layer) { std::cout << outData[i] << ", "; } std::cout << std::endl; - error = lite::RelativeOutputError(outData, output_path); + error = RelativeOutputError(outData, output_path); EXPECT_LT(error, 2e-3); session->Train(); @@ -449,7 +448,7 @@ TEST_F(NetworkTest, tuning_layer) { std::cout << outData[i] << ", "; } std::cout << std::endl; - error = lite::RelativeOutputError(outData, output_path); + error = RelativeOutputError(outData, output_path); EXPECT_LT(error, 2e-3); delete session; @@ -502,7 +501,7 @@ int32_t runNet(mindspore::session::LiteSession *session, const std::string &in, } std::cout << std::endl; } - return mindspore::lite::CompareRelativeOutput(output_data, out); + return CommonTest::CompareRelativeOutput(output_data, out); } return lite::RET_ERROR; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/pooling_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/pooling_grad_fp32_tests.cc index 7ba5b2e4ba..ae7d061f47 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/pooling_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/pooling_grad_fp32_tests.cc @@ -22,7 +22,6 @@ #include "common/common_test.h" #include "src/common/utils.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "nnacl/fp32_grad/pooling_grad.h" #include "src/runtime/kernel/arm/fp32_grad/pooling_grad.h" #include "mindspore/lite/src/kernel_registry.h" @@ -97,7 +96,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolingGradFp32) { } std::cout << std::endl; std::string output_path = "./test_data/pooling/avgpoolgradfp32_1_dx_1_28_28_3.bin"; - auto res = lite::CompareOutput(output_data, output_data_size, output_path); + auto res = CompareOutput(output_data, output_data_size, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -156,7 +155,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolingKernelGradFp32) { } std::cout << std::endl; std::string output_path = "./test_data/pooling/avgpoolgradfp32_1_dx_1_28_28_3.bin"; - auto res = lite::CompareOutput(output_data, output_data_size, output_path); + auto res = CompareOutput(output_data, output_data_size, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -221,7 +220,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolingBatchGradFp32) { std::cout << std::endl; std::string output_path = "./test_data/pooling/avgpoolgradfp32_1_dx_3_28_28_3.bin"; size_t output_data_size = dx_tensor.ElementsNum(); - auto res = lite::CompareOutput(output_data, output_data_size, output_path); + auto res = CompareOutput(output_data, output_data_size, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -279,7 +278,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolGradStride2Fp32) { kernel->Run(); std::string output_path = "./test_data/pooling/avgpoolgradfp32_s2_dx_3_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] x_data; @@ -340,7 +339,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolGradStride3Fp32) { kernel->Run(); std::string output_path = "./test_data/pooling/avgpoolgradfp32_s3_dx_3_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); @@ -398,7 +397,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolingGradFp32) { } std::cout << std::endl; std::string output_path = "./test_data/pooling/maxpoolgradfp32_1_xgrad_1_28_28_3.bin"; - auto res = lite::CompareOutput(output_data, output_data_size, output_path); + auto res = CompareOutput(output_data, output_data_size, output_path); EXPECT_EQ(res, 0); free(pooling_param); @@ -458,7 +457,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradBatchFp32) { kernel->Run(); std::string output_path = "./test_data/pooling/maxpoolgradfp32_1_xgrad_3_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); @@ -529,7 +528,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradStride2Fp32) { kernel->Run(); std::string output_path = "./test_data/pooling/maxpoolgradfp32_s2_xgrad_3_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); @@ -600,7 +599,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradStride3Fp32) { kernel->Run(); std::string output_path = "./test_data/pooling/maxpoolgradfp32_s3_xgrad_3_28_28_3.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_crossentropy_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_crossentropy_fp32_tests.cc index ae059f756a..9988320431 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_crossentropy_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_crossentropy_fp32_tests.cc @@ -76,7 +76,7 @@ TEST_F(TestSoftmaxCrossEntropyFp32, SoftmaxCrossEntropyFp32) { printf("==================Testing Grad===============\n"); std::string output_path = "./test_data/operators/sce_fp32_1_loss_1.bin"; - lite::CompareOutput(loss, 1, output_path); + CompareOutput(loss, 1, output_path); ((mindspore::kernel::SparseSoftmaxCrossEntropyWithLogitsCPUKernel *)kernel_obj)->train(); kernel_obj->Run(); @@ -87,7 +87,7 @@ TEST_F(TestSoftmaxCrossEntropyFp32, SoftmaxCrossEntropyFp32) { } std::cout << std::endl; std::string grad_path = "./test_data/operators/sce_fp32_1_dy_6_4.bin"; - lite::CompareOutput(grad, 24, grad_path); + CompareOutput(grad, 24, grad_path); delete[] ll_labels; delete[] labels; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_grad_fp32_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_grad_fp32_tests.cc index b8164b2af7..6c61cd1e7f 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_grad_fp32_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/softmax_grad_fp32_tests.cc @@ -23,7 +23,6 @@ #include "common/common_test.h" #include "src/common/utils.h" #include "src/common/file_utils.h" -#include "src/common/file_utils_ext.h" #include "mindspore/lite/src/runtime/kernel/arm/fp32_grad/softmax_grad.h" #include "mindspore/lite/nnacl/fp32_grad/softmax_grad.h" #include "mindspore/lite/src/kernel_registry.h" @@ -97,7 +96,7 @@ TEST_F(TestSoftmaxGradFp32, SoftmaxGradAxis0) { std::string output_path = "./test_data/softmax/softmaxgrad_out.bin"; - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -156,7 +155,7 @@ TEST_F(TestSoftmaxGradFp32, SoftmaxGradAxis1) { std::string output_path = "./test_data/softmax/softmaxgrad_1_out.bin"; // auto output_data = reinterpret_cast(mindspore::lite::ReadFile(input_path.c_str(), &input_size)); - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -215,7 +214,7 @@ TEST_F(TestSoftmaxGradFp32, SoftmaxGradAxis2) { std::string output_path = "./test_data/softmax/softmaxgrad_2_out.bin"; // auto output_data = reinterpret_cast(mindspore::lite::ReadFile(input_path.c_str(), &input_size)); - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -274,7 +273,7 @@ TEST_F(TestSoftmaxGradFp32, SoftmaxGradAxis3) { std::string output_path = "./test_data/softmax/softmaxgrad_3_out.bin"; // auto output_data = reinterpret_cast(mindspore::lite::ReadFile(input_path.c_str(), &input_size)); - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; @@ -333,7 +332,7 @@ TEST_F(TestSoftmaxGradFp32, SoftmaxGradAxisMinus1) { std::string output_path = "./test_data/softmax/softmaxgrad_-1_out.bin"; // auto output_data = reinterpret_cast(mindspore::lite::ReadFile(input_path.c_str(), &input_size)); - auto res = lite::CompareRelativeOutput(out_data, output_path); + auto res = CompareRelativeOutput(out_data, output_path); EXPECT_EQ(res, 0); delete[] input_data; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/arithmetic_self_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/arithmetic_self_int8_tests.cc index 192f3c5d2c..7112a34320 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/arithmetic_self_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/arithmetic_self_int8_tests.cc @@ -80,7 +80,7 @@ TEST_F(TestArithmeticSelfInt8, floor_quant0_thread2) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -140,7 +140,7 @@ TEST_F(TestArithmeticSelfInt8, floor_quant1_thread2) { std::vector except_result = {0, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -200,7 +200,7 @@ TEST_F(TestArithmeticSelfInt8, round_quant0_thread2) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -260,7 +260,7 @@ TEST_F(TestArithmeticSelfInt8, round_quant1_thread2) { std::vector except_result = {1, 1, 1, 2, 3, 3, 4, 4, 5, 5, 6, 7}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -320,7 +320,7 @@ TEST_F(TestArithmeticSelfInt8, ceil_quant0_thread2) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -380,7 +380,7 @@ TEST_F(TestArithmeticSelfInt8, ceil_quant1_thread2) { std::vector except_result = {1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 7}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -440,7 +440,7 @@ TEST_F(TestArithmeticSelfInt8, abs_quant0_thread0) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -500,7 +500,7 @@ TEST_F(TestArithmeticSelfInt8, abs_quant1_thread2) { std::vector except_result = {1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -560,7 +560,7 @@ TEST_F(TestArithmeticSelfInt8, sin_quant0_thread2) { std::vector except_result = {1, 1, 0, -1}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -620,7 +620,7 @@ TEST_F(TestArithmeticSelfInt8, cos_quant0_thread2) { std::vector except_result = {1, 0, -1, -1}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -680,7 +680,7 @@ TEST_F(TestArithmeticSelfInt8, log_quant0_thread2) { std::vector except_result = {0, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -740,7 +740,7 @@ TEST_F(TestArithmeticSelfInt8, sqrt_quant0_thread2) { std::vector except_result = {1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -800,7 +800,7 @@ TEST_F(TestArithmeticSelfInt8, rsqrt_quant0_thread2) { std::vector except_result = {1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -860,7 +860,7 @@ TEST_F(TestArithmeticSelfInt8, square_quant0_thread2) { std::vector except_result = {1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 127}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -920,7 +920,7 @@ TEST_F(TestArithmeticSelfInt8, square_quant1_thread2) { std::vector except_result = {1, 2, 4, 7, 11, 16, 21, 28, 35, 43, 52, 62}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -980,7 +980,7 @@ TEST_F(TestArithmeticSelfInt8, logical_not_quant0_thread2) { std::vector except_result = {0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/batchnorm_int8_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/batchnorm_int8_test.cc index c5322be70e..ee567e4aea 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/batchnorm_int8_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/batchnorm_int8_test.cc @@ -116,7 +116,7 @@ TEST_F(TestBatchnormInt8, FusedTest) { printf("%d, ", output[i]); } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); @@ -197,7 +197,7 @@ TEST_F(TestBatchnormInt8, BNTest) { printf("%d, ", output[i]); } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/concat_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/concat_int8_tests.cc index b354f43b92..312867cf21 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/concat_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/concat_int8_tests.cc @@ -92,7 +92,7 @@ TEST_F(TestConcatInt8, Concat1_axis0) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}; PrintData("output data", output, input1.size() + input2.size()); - CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -164,7 +164,7 @@ TEST_F(TestConcatInt8, Concat1_axis1_thread2) { std::vector except_result = {10, 11, 12, 13, 14, 15, 30, 31, 20, 21, 22, 23, 24, 25, 32, 33}; PrintData("output data", output, input1.size() + input2.size()); - CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); @@ -237,7 +237,7 @@ TEST_F(TestConcatInt8, Concat1_axis1_thread2_quant1) { std::vector except_result = {5, 6, 6, 7, 7, 8, 15, 16, 10, 11, 11, 12, 12, 13, 16, 17}; PrintData("output data", output, input1.size() + input2.size()); - CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size() + input2.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/conv_1x1_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/conv_1x1_int8_tests.cc index 2d75af9f92..bea6ae291a 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/conv_1x1_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/conv_1x1_int8_tests.cc @@ -42,7 +42,7 @@ TEST_F(TestConv1x1Int8, Input1x1PrePack1) { 1, -1, 41, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; int8_t out[54] = {0}; Conv1x1InputPack(in, out, conv_param, sizeof(int8_t)); - CompareOutputData(out, correct, 54, 0); + ASSERT_EQ(0, CompareOutputData(out, correct, 54, 0)); delete conv_param; } @@ -65,7 +65,7 @@ TEST_F(TestConv1x1Int8, Input1x1PrePack2) { int8_t out[20] = {0}; Conv1x1InputPack(in, out, conv_param, sizeof(int8_t)); - CompareOutputData(out, correct, 20, 0); + ASSERT_EQ(0, CompareOutputData(out, correct, 20, 0)); delete conv_param; } @@ -130,7 +130,7 @@ TEST_F(TestConv1x1Int8, Conv1x1TestPerChannel) { conv1x1->Init(); conv1x1->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 70); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 70)); delete conv1x1; for (auto t : inputs_) delete t; @@ -199,7 +199,7 @@ TEST_F(TestConv1x1Int8, Conv1x1Int8Test1) { conv1x1->Init(); conv1x1->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 2); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 2)); delete conv1x1; for (auto t : inputs_) delete t; @@ -271,12 +271,12 @@ TEST_F(TestConv1x1Int8, Conv1x1Int8Test2) { ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); int total_size = Conv1x1Int8TestInit2(&inputs_, &outputs_, conv_param, &correct); - kernel::Convolution1x1Int8CPUKernel *conv1x1 = new kernel::Convolution1x1Int8CPUKernel( - reinterpret_cast(conv_param), inputs_, outputs_, ctx, nullptr); + auto *conv1x1 = new kernel::Convolution1x1Int8CPUKernel(reinterpret_cast(conv_param), inputs_, + outputs_, ctx, nullptr); conv1x1->Init(); conv1x1->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 2); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 2)); delete conv1x1; for (auto t : inputs_) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/crop_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/crop_int8_tests.cc index 40ef98d6be..73a33292c2 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/crop_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/crop_int8_tests.cc @@ -85,7 +85,7 @@ TEST_F(TestCropInt8, crop_1d_axis0_offset0_quant0_thread2) { std::vector except_result = {2, 3, 4, 5, 6, 7, 8}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -149,7 +149,7 @@ TEST_F(TestCropInt8, crop_2d_axis1_offset0_quant0_thread2) { std::vector except_result = {2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -213,7 +213,7 @@ TEST_F(TestCropInt8, crop_3d_axis1_offset0_quant0_thread0) { std::vector except_result = {4, 8}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -278,7 +278,7 @@ TEST_F(TestCropInt8, crop_3d_axis1_offset0_quant0_thread2) { std::vector except_result = {4, 6, 8, 10, 12, 14, 16, 20, 22, 24, 26, 28, 30, 32}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -342,7 +342,7 @@ TEST_F(TestCropInt8, crop_4d_axis0_offset0_quant0_thread0) { std::vector except_result = {16}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -406,7 +406,7 @@ TEST_F(TestCropInt8, crop_4d_axis1_offset0_quant0_thread0) { std::vector except_result = {8, 16}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -473,7 +473,7 @@ TEST_F(TestCropInt8, crop_4d_axis1_offset1_quant0_thread0) { std::vector except_result = {13, 14, 15, 16}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -540,7 +540,7 @@ TEST_F(TestCropInt8, crop_4d_axis1_offset1_quant1_thread0) { std::vector except_result = {7, 7, 8, 8}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -606,7 +606,7 @@ TEST_F(TestCropInt8, crop_4d_axis0_offset0_quant0_thread2) { std::vector except_result = {40, 44, 48, 52, 56, 60, 64}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -672,7 +672,7 @@ TEST_F(TestCropInt8, crop_4d_axis0_offset0_quant0_thread3) { std::vector except_result = {40, 44, 48, 52, 56, 60, 64}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/deconv_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/deconv_int8_tests.cc index bcb078f30d..3de3a098c7 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/deconv_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/deconv_int8_tests.cc @@ -48,7 +48,7 @@ TEST_F(TestDeconvInt8, PackWeight1) { int8_t dst[80] = {0}; /*5*1*2*6 nhwc*/ PackNHWCToC8HWN8Int8(in, dst, 5, 2, 6); - CompareOutputData(dst, co, 80, 1); + ASSERT_EQ(0, CompareOutputData(dst, co, 80, 1)); } TEST_F(TestDeconvInt8, PackWeight2) { @@ -105,7 +105,7 @@ TEST_F(TestDeconvInt8, PackWeight2) { 46, 121, 66, 92, 0, 0, 0, 0}; int8_t dst[528] = {0}; PackNHWCToC8HWN8Int8(in, dst, 22, 1, 20); - CompareOutputData(dst, co, 528, 1); + ASSERT_EQ(0, CompareOutputData(dst, co, 528, 1)); } TEST_F(TestDeconvInt8, PackInputTest1) { @@ -131,7 +131,7 @@ TEST_F(TestDeconvInt8, PackInputTest1) { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; int8_t dst[8 * 32] = {0}; RowMajor2Row16x4MajorInt8(in, dst, 6, 20); - CompareOutputData(dst, co, 8 * 32, 1); + ASSERT_EQ(0, CompareOutputData(dst, co, 8 * 32, 1)); } TEST_F(TestDeconvInt8, InputSumTest1) { @@ -150,12 +150,12 @@ TEST_F(TestDeconvInt8, InputSumTest1) { int32_t input_sum[12] = {0}; int32_t correct_input_sum[] = {-7100, -4780, 580, -4880, -9460, -1420, -3120, -3260, -1840, -6960, -4800, -4800}; DeConvPackInputSum(packed_a, input_sum, filter_zp, 12, 16, true); - CompareOutputData(input_sum, correct_input_sum, 12, 0); + ASSERT_EQ(0, CompareOutputData(input_sum, correct_input_sum, 12, 0)); int32_t input_sum_4[4] = {0}; int32_t correct_input_sum_4[] = {-18400, -13160, -7340, -12940}; DeConvPackInputSum(packed_a, input_sum_4, filter_zp, 4, 16 * 3, true); - CompareOutputData(input_sum_4, correct_input_sum_4, 4, 0); + ASSERT_EQ(0, CompareOutputData(input_sum_4, correct_input_sum_4, 4, 0)); } TEST_F(TestDeconvInt8, MatMulOptTest1) { @@ -196,7 +196,7 @@ TEST_F(TestDeconvInt8, MatMulOptTest1) { 55, 10, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15}; RowMajor2Row16x4MajorInt8(a_src_ptr, packed_a, 10, 12); - CompareOutputData(packed_a, correct_packed_a, 16 * 12, 0); + ASSERT_EQ(0, CompareOutputData(packed_a, correct_packed_a, 16 * 12, 0)); /* * ---------------------- pack weight ------------------------- */ @@ -224,14 +224,14 @@ TEST_F(TestDeconvInt8, MatMulOptTest1) { -20, -20, -20, -20, -20, -20}; DeConvWeightTransInt8(b_src_ptr, packed_b, 12, 6, 3, true); /* kernel : 12x1x3x6 nhwc */ - CompareOutputData(packed_b, correct_packed_b, 16 * 3 * 8, 0); + ASSERT_EQ(0, CompareOutputData(packed_b, correct_packed_b, 16 * 3 * 8, 0)); /* * ---------------------- calculate input_sum ------------------------- */ int32_t input_sum[12] = {0}; int32_t correct_input_sum[] = {-7100, -4780, 580, -4880, -9460, -1420, -3120, -3260, -1840, -6960, -4800, -4800}; DeConvPackInputSum(packed_a, input_sum, filter_zp, 12, 16, true); - CompareOutputData(input_sum, correct_input_sum, 12, 0); + ASSERT_EQ(0, CompareOutputData(input_sum, correct_input_sum, 12, 0)); /* * ---------------------- calculate weight_sum ------------------------- */ @@ -239,7 +239,7 @@ TEST_F(TestDeconvInt8, MatMulOptTest1) { int32_t correct_weight_sum[] = {-7395, -8265, -3090, -435, -5655, -1035, 0, 0, 1695, -4770, -6630, 300, -765, -2835, 0, 0, -7395, 4665, -2475, -4170, -2880, -1110, 0, 0}; DeConvPackWeightSum(packed_b, weight_sum, input_zp, filter_zp, 16, 24, true); - CompareOutputData(weight_sum, correct_weight_sum, 3 * 8, 0); + ASSERT_EQ(0, CompareOutputData(weight_sum, correct_weight_sum, 3 * 8, 0)); /* * ---------------------- do matmul ------------------------- */ @@ -268,36 +268,36 @@ TEST_F(TestDeconvInt8, MatMulOptTest1) { 0, 0, 0, 0, 0, 0, 0, 0}; MatMulInt8_16x4(packed_a, packed_b, tmp_output, 12, 24, 16, input_sum, weight_sum); - CompareOutputData(tmp_output, correct_tmp_output, 12 * 3 * 8, 0); + ASSERT_EQ(0, CompareOutputData(tmp_output, correct_tmp_output, 12 * 3 * 8, 0)); } int DeConvInt8TestInit1(std::vector *inputs_, std::vector *outputs_, ConvParameter *conv_param, int8_t **correct) { /* float data from deconv fp32 testcase : DeConvTestInit2 */ /* vq = (vi - zp) * s vi = vq / s + zp */ - Tensor *in_t = new Tensor(kNumberTypeInt8, {1, 4, 2, 3}, Format_NHWC, lite::Tensor::Category::VAR); + auto *in_t = new Tensor(kNumberTypeInt8, {1, 4, 2, 3}, Format_NHWC, lite::Tensor::Category::VAR); in_t->MallocData(); int8_t in[] = {6, 43, 38, 24, -8, 12, 41, -24, -20, 41, -19, -6, -26, -6, 23, -31, 34, 45, 8, 45, -39, -27, -48, 12}; memcpy(in_t->MutableData(), in, sizeof(int8_t) * in_t->ElementsNum()); - QuantArg *in_quant_arg = new QuantArg(); + auto *in_quant_arg = new QuantArg(); in_quant_arg->zeroPoint = -19, in_quant_arg->scale = 0.31228156; in_t->AddQuantParam(*in_quant_arg); inputs_->push_back(in_t); - Tensor *weight_t = new Tensor(kNumberTypeInt8, {3, 3, 3, 2}, Format_NHWC, lite::Tensor::Category::CONST_TENSOR); + auto *weight_t = new Tensor(kNumberTypeInt8, {3, 3, 3, 2}, Format_NHWC, lite::Tensor::Category::CONST_TENSOR); weight_t->MallocData(); int8_t weight[] = {66, 89, 98, 74, 95, 86, 125, 95, 105, 83, 116, 94, 90, 80, 86, 59, 72, 92, 64, 76, 92, 80, 90, 87, 106, 55, 105, 60, 75, 53, 81, 81, 98, 81, 86, 59, 74, 82, 97, 105, 71, 67, 79, 87, 72, 79, 80, 76, 96, 80, 83, 71, 61, 79}; memcpy(weight_t->MutableData(), weight, sizeof(int8_t) * weight_t->ElementsNum()); - QuantArg *w_quant_arg = new QuantArg(); + auto *w_quant_arg = new QuantArg(); w_quant_arg->zeroPoint = 83, w_quant_arg->scale = 0.023649725490196; weight_t->AddQuantParam(*w_quant_arg); inputs_->push_back(weight_t); - Tensor *out_t = new Tensor(kNumberTypeInt8, {1, 7, 3, 2}, Format_NHWC, lite::Tensor::Category::VAR); + auto *out_t = new Tensor(kNumberTypeInt8, {1, 7, 3, 2}, Format_NHWC, lite::Tensor::Category::VAR); out_t->MallocData(); - QuantArg *out_quant_arg = new QuantArg(); + auto *out_quant_arg = new QuantArg(); out_quant_arg->zeroPoint = 31, out_quant_arg->scale = 0.3439215686275; out_t->AddQuantParam(*out_quant_arg); outputs_->push_back(out_t); @@ -318,17 +318,17 @@ TEST_F(TestDeconvInt8, DeConvInt8Test1) { std::vector inputs_; std::vector outputs_; auto deconv_param = new ConvParameter(); - lite::InnerContext *ctx = new lite::InnerContext; + auto *ctx = new lite::InnerContext; ctx->thread_num_ = 1; ASSERT_EQ(lite::RET_OK, ctx->Init()); int8_t *correct; int total_size = DeConvInt8TestInit1(&inputs_, &outputs_, deconv_param, &correct); - mindspore::kernel::DeConvInt8CPUKernel *deconv = new mindspore::kernel::DeConvInt8CPUKernel( - reinterpret_cast(deconv_param), inputs_, outputs_, ctx, nullptr); + auto *deconv = new mindspore::kernel::DeConvInt8CPUKernel(reinterpret_cast(deconv_param), inputs_, + outputs_, ctx, nullptr); deconv->Init(); deconv->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 3); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 3)); delete deconv_param; delete deconv; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/fullconnection_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/fullconnection_int8_tests.cc index 4dc18b145e..72c4ee2c12 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/fullconnection_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/fullconnection_int8_tests.cc @@ -147,7 +147,7 @@ TEST_F(TestFcInt8, fctest1) { QuantProcess(correct, out_params.len, out_params.min, out_params.max, &out_scale, &out_zp, nullptr); float *out = new float[out_params.len]; Dequantize(reinterpret_cast(outputs[0]->MutableData()), outputs[0]->ElementsNum(), out_scale, out_zp, out); - CompareOutputData(out, correct, 6, 0.3); + ASSERT_EQ(0, CompareOutputData(out, correct, 6, 0.3)); delete fc; for (auto t : inputs) delete t; for (auto t : outputs) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gatherNd_int8_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gatherNd_int8_test.cc index 361cead544..aa64abcd44 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gatherNd_int8_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gatherNd_int8_test.cc @@ -92,7 +92,7 @@ TEST_F(TestGatherNdInt8, GatherNdTest) { printf("%d, ", output[i]); } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gather_int8_test.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gather_int8_test.cc index 1cedf1241d..4190b723ba 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gather_int8_test.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/gather_int8_test.cc @@ -90,7 +90,7 @@ TEST_F(TestGatherInt8, GatherTest) { printf("%d, ", output[i]); } std::cout << std::endl; - CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001); + ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0_tensor.ElementsNum(), 0.001)); input0_tensor.set_data(nullptr); input1_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/matmul_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/matmul_int8_tests.cc index b24b5893c6..e28f2b2e1b 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/matmul_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/matmul_int8_tests.cc @@ -126,7 +126,7 @@ TEST_F(TestMatmulInt8, simple) { MatMulInt8_16x4_r(a_r4x16, b_c16x4, output, ROW, COL, DEPTH16, COL, a_sums, bias, &ls, &rs, &multiplier, 0, INT8_MIN, INT8_MAX, false); #endif - CompareOutputData(output, correct, ROW * COL, 0.1); + ASSERT_EQ(0, CompareOutputData(output, correct, ROW * COL, 0.1)); delete[] a_r4x16; delete[] b_c16x4; } @@ -187,7 +187,7 @@ TEST_F(TestMatmulInt8, mmtest1) { QuantProcess(correct, out_params.len, out_params.min, out_params.max, &out_scale, &out_zp, nullptr); float *out = new float[out_params.len]; Dequantize(reinterpret_cast(outputs[0]->MutableData()), outputs[0]->ElementsNum(), out_scale, out_zp, out); - CompareOutputData(out, correct, 6, 0.3); + ASSERT_EQ(0, CompareOutputData(out, correct, 6, 0.3)); delete mm; for (auto t : inputs) delete t; for (auto t : outputs) delete t; @@ -304,7 +304,7 @@ TEST_F(TestMatmulInt8, mmtest2) { QuantProcess(correct, out_params.len, out_params.min, out_params.max, &out_scale, &out_zp, nullptr); float *out = new float[out_params.len]; Dequantize(reinterpret_cast(outputs[0]->MutableData()), outputs[0]->ElementsNum(), out_scale, out_zp, out); - CompareOutputData(out, correct, 6, 0.6); + ASSERT_EQ(0, CompareOutputData(out, correct, 6, 0.6)); delete mm; for (auto t : inputs) delete t; for (auto t : outputs) delete t; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/mul_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/mul_int8_tests.cc index 95a3ecc602..4465782e31 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/mul_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/mul_int8_tests.cc @@ -91,7 +91,7 @@ TEST_F(TestMulInt8, Mul_quant0) { std::vector except_result = {1, 4, 3, 8, 5, 12, 21, 32, 27, 40, 33, 48}; PrintData("output data", output, input1.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -162,7 +162,7 @@ TEST_F(TestMulInt8, Mul_quant0_thread0) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18}; PrintData("output data", output, input1.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -233,7 +233,7 @@ TEST_F(TestMulInt8, Mul_quant1) { std::vector except_result = {1, 2, 2, 4, 3, 6, 11, 16, 14, 20, 17, 24}; PrintData("output data", output, input1.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -304,7 +304,7 @@ TEST_F(TestMulInt8, Mul_quant1_thread1) { std::vector except_result = {1, 2, 2, 4, 3, 6, 11, 16, 14, 20, 17, 24}; PrintData("output data", output, input1.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -375,7 +375,7 @@ TEST_F(TestMulInt8, test) { std::vector except_result = {1, 4, 9, 16, 25, 36, 7, 16, 27, 40, 55, 72}; PrintData("output data", output, input1.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); input_tensor2->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/pad_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/pad_int8_tests.cc index 2ea9242673..25d642fd7e 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/pad_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/pad_int8_tests.cc @@ -74,7 +74,7 @@ TEST_F(TestPadInt8, PadInt8Test1) { pad->Init(); pad->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0)); delete pad_param; delete pad; @@ -127,7 +127,7 @@ TEST_F(TestPadInt8, PadInt8Test2) { pad->Init(); pad->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0)); delete pad_param; delete pad; @@ -195,7 +195,7 @@ TEST_F(TestPadInt8, PadInt8TestInit4) { pad->Init(); pad->Run(); - CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0); + ASSERT_EQ(0, CompareOutputData(reinterpret_cast(outputs_[0]->MutableData()), correct, total_size, 0)); delete pad_param; delete pad; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/power_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/power_int8_tests.cc index c207ac73a4..264e54d467 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/power_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/power_int8_tests.cc @@ -79,7 +79,7 @@ TEST_F(TestPowerInt8, PowerInt8) { kernel->Run(); std::vector except_result = {-112, -65, 15, 127}; - CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); @@ -148,7 +148,7 @@ TEST_F(TestPowerInt8, normal) { kernel->Run(); std::vector except_result = {-99, 95, 124, -14}; - CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/prelu_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/prelu_int8_tests.cc index 556c33956a..52169d0c4d 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/prelu_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/prelu_int8_tests.cc @@ -85,7 +85,7 @@ TEST_F(TestPreluInt8, prelu_1) { std::vector except_result = {1, -1, 3, 4, 5, 6, 7, -2}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/quant_dtype_cast_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/quant_dtype_cast_tests.cc index dc2c68297c..080307b917 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/quant_dtype_cast_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/quant_dtype_cast_tests.cc @@ -77,7 +77,7 @@ TEST_F(QuantDTypeCastTestFp32, QuantDTypeCastTest1) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output.data(), expect_out, out_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_out, out_size, 0.000001)); } TEST_F(QuantDTypeCastTestFp32, QuantDTypeCastTest2) { @@ -124,6 +124,6 @@ TEST_F(QuantDTypeCastTestFp32, QuantDTypeCastTest2) { std::cout << output[i] << " "; } std::cout << "\n"; - CompareOutputData(output.data(), expect_out, out_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), expect_out, out_size, 0.000001)); } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/reshape_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/reshape_int8_tests.cc index 90f000485e..25ca86ceae 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/reshape_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/reshape_int8_tests.cc @@ -81,7 +81,7 @@ TEST_F(TestReshapeInt8, reshape_quant0) { std::vector except_result = {10, 11, 12, 13, 14, 15, 20, 21, 22, 23, 24, 25}; PrintData("output data", output, input1.size()); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); @@ -141,7 +141,7 @@ TEST_F(TestReshapeInt8, reshape_quant1_thread2) { std::vector except_result = {6, 7, 7, 8, 8, 9, 11, 12, 12, 13, 13, 14}; PrintData("output data", output, input1.size()); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), input1.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), input1.size(), 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/softmax_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/softmax_int8_tests.cc index 57937d8ca1..5d8c181945 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/softmax_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/softmax_int8_tests.cc @@ -84,7 +84,7 @@ TEST_F(TestSoftmaxInt8, SoftmaxInt8) { std::vector except_result = {-126, -126, -124, -124, -123, -124, -116, -116, 122, 122, 112, 112, -127, -127, -127, -127, -59, -59, -61, -59, 58, 58, 59, 58}; - CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output.data(), except_result.data(), input.size(), 0.000001)); input0_tensor.set_data(nullptr); output0_tensor.set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/split_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/split_int8_tests.cc index 2f0d84084b..1d882bdf3a 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/split_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/split_int8_tests.cc @@ -100,8 +100,8 @@ TEST_F(TestSplitInt8, Split_quant0_thread2) { PrintData("output data shape", output1_tensor_shape.data(), output1_tensor_shape.size()); PrintData("output data", output2, output2_size); PrintData("output data shape", output2_tensor_shape.data(), output2_tensor_shape.size()); - CompareOutputData(output1, except_result1.data(), output1_size, 0.000001); - CompareOutputData(output2, except_result2.data(), output2_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output1, except_result1.data(), output1_size, 0.000001)); + ASSERT_EQ(0, CompareOutputData(output2, except_result2.data(), output2_size, 0.000001)); input_tensor1->set_data(nullptr); output1_tensor->set_data(nullptr); @@ -194,9 +194,9 @@ TEST_F(TestSplitInt8, Split_quant0_thread2_num) { PrintData("output data shape", output2_tensor_shape.data(), output2_tensor_shape.size()); PrintData("output data", output3, output3_size); PrintData("output data shape", output3_tensor_shape.data(), output3_tensor_shape.size()); - CompareOutputData(output1, except_result1.data(), output1_size, 0.000001); - CompareOutputData(output2, except_result2.data(), output2_size, 0.000001); - CompareOutputData(output3, except_result3.data(), output3_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output1, except_result1.data(), output1_size, 0.000001)); + ASSERT_EQ(0, CompareOutputData(output2, except_result2.data(), output2_size, 0.000001)); + ASSERT_EQ(0, CompareOutputData(output3, except_result3.data(), output3_size, 0.000001)); input_tensor1->set_data(nullptr); output1_tensor->set_data(nullptr); @@ -291,9 +291,9 @@ TEST_F(TestSplitInt8, Split_quant1_thread2_num) { PrintData("output data shape", output2_tensor_shape.data(), output2_tensor_shape.size()); PrintData("output data", output3, output3_size); PrintData("output data shape", output3_tensor_shape.data(), output3_tensor_shape.size()); - CompareOutputData(output1, except_result1.data(), output1_size, 0.000001); - CompareOutputData(output2, except_result2.data(), output2_size, 0.000001); - CompareOutputData(output3, except_result3.data(), output3_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output1, except_result1.data(), output1_size, 0.000001)); + ASSERT_EQ(0, CompareOutputData(output2, except_result2.data(), output2_size, 0.000001)); + ASSERT_EQ(0, CompareOutputData(output3, except_result3.data(), output3_size, 0.000001)); input_tensor1->set_data(nullptr); output1_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/squeeze_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/squeeze_int8_tests.cc index a30f3552f2..053946e7e7 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/squeeze_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/squeeze_int8_tests.cc @@ -85,7 +85,7 @@ TEST_F(TestSqueezeInt8, Squeeze_1d_axis0_offset0_quant0_thread2) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/unsqueeze_int8_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/unsqueeze_int8_tests.cc index f1f8d74edc..30f7126ad0 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/unsqueeze_int8_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/arm/int8/unsqueeze_int8_tests.cc @@ -84,7 +84,7 @@ TEST_F(TestUnsqueezeInt8, Unsqueeze_1) { std::vector except_result = {1, 2, 3, 4, 5, 6, 7, 8}; PrintData("output data", output, output_size); PrintData("output data shape", output_tensor_shape.data(), output_tensor_shape.size()); - CompareOutputData(output, except_result.data(), output_size, 0.000001); + ASSERT_EQ(0, CompareOutputData(output, except_result.data(), output_size, 0.000001)); input_tensor1->set_data(nullptr); output0_tensor->set_data(nullptr); diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/batchnorm_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/batchnorm_tests.cc index de7a306dba..644380e851 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/batchnorm_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/batchnorm_tests.cc @@ -141,7 +141,7 @@ TEST_F(TestBatchnormOpenCLCI, Batchnormfp32CI) { sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -260,7 +260,7 @@ TEST_F(TestBatchnormOpenCLfp16, Batchnormfp16input_dim4) { sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.01); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.01)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -378,7 +378,7 @@ TEST_F(TestBatchnormOpenCLfp32, Batchnormfp32input_dim4) { sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc index 68738ba866..b2337d7dea 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc @@ -124,7 +124,7 @@ TEST_F(TestConcatOpenCLCI, ConcatFp32_2inputforCI) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -252,7 +252,7 @@ TEST_F(TestConcatOpenCLfp16, ConcatFp16_4input_dim4_axis1) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -371,7 +371,7 @@ TEST_F(TestConcatOpenCLfp32, ConcatFp32_3input_dim4_axis1) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -510,7 +510,7 @@ TEST_F(TestConcatOpenCLfp16, ConcatFp16_6input_dim4_axis1) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->MutableData()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/fill_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/fill_tests.cc index c93603e90f..c2ce6719b6 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/fill_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/fill_tests.cc @@ -83,7 +83,7 @@ TEST_F(TestFillOpenCLCI, Fp32testfill) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -139,7 +139,7 @@ TEST_F(TestFillOpenCLCI, Fp32testshape) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/hswish_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/hswish_tests.cc index aab2821ddb..830bc36804 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/hswish_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/hswish_tests.cc @@ -94,7 +94,7 @@ TEST_F(TestSwishOpenCLCI, Fp32CI) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } } // namespace mindspore diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/pad_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/pad_tests.cc index 91c52ba4e8..cae15c12f3 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/pad_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/pad_tests.cc @@ -69,8 +69,8 @@ void TEST_MAIN(PadParameter *param, Format input_format, Format output_format, F sub_graph->Init(); memcpy(input.data_c(), input_data, input.Size()); sub_graph->Run(); - if (lite::CompareOutputData(reinterpret_cast(output.data_c()), output.ElementsNum(), - const_cast(expect_data), output.ElementsNum())) { + if (CommonTest::CompareOutputData(reinterpret_cast(output.data_c()), const_cast(expect_data), + static_cast(output.ElementsNum()))) { FAIL(); } else { std::cout << "COMPARE SUCCESS!\n"; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/sparse_to_dense_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/sparse_to_dense_tests.cc index 87c9d2d88a..7fa050810b 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/sparse_to_dense_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/sparse_to_dense_tests.cc @@ -96,7 +96,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim2Scalar) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -168,7 +168,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim2Vector) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -239,7 +239,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim2Shape1Vector) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -310,7 +310,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim2Shape1Scalar) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -381,7 +381,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim1Scalar) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } @@ -452,7 +452,7 @@ TEST_F(TestSparseToDenseOpenCLCI, Fp32Dim1Vector) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor.data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor.ElementsNum(), 0.0001)); delete sub_graph; } diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/stack_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/stack_tests.cc index 6434505599..9df29e386f 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/stack_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/stack_tests.cc @@ -135,7 +135,7 @@ TEST_F(TestStackOpenCLCI, StackFp32_8inputforCI) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->data_c()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; @@ -268,7 +268,7 @@ TEST_F(TestStackOpenCLfp16, StackFp32_8inputaxis1) { std::cout << "==================output data================" << std::endl; sub_graph->Run(); auto *output_data_gpu = reinterpret_cast(output_tensor->MutableData()); - CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001); + ASSERT_EQ(0, CompareOutputData(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001)); for (auto tensor : inputs) { tensor->set_data(nullptr); delete tensor; diff --git a/mindspore/lite/test/ut/src/runtime/kernel/opencl/to_format_tests.cc b/mindspore/lite/test/ut/src/runtime/kernel/opencl/to_format_tests.cc index 11280707de..f5f3259860 100644 --- a/mindspore/lite/test/ut/src/runtime/kernel/opencl/to_format_tests.cc +++ b/mindspore/lite/test/ut/src/runtime/kernel/opencl/to_format_tests.cc @@ -100,7 +100,7 @@ TEST_F(TestToFormatOpenCL, ToFormatNHWC2NCHW) { std::cout << std::endl; // compare - CompareOutputData(output_data, correct_data, h * w * c, 0.00001); + ASSERT_EQ(0, CompareOutputData(output_data, correct_data, h * w * c, 0.00001)); MS_LOG(INFO) << "Test TransposeFp32 passed"; } } // namespace mindspore