/** * 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 "common/common.h" #include "common/cvop_common.h" #include "minddata/dataset/kernels/image/cutmix_batch_op.h" #include "utils/log_adapter.h" using namespace mindspore::dataset; using mindspore::LogStream; using mindspore::ExceptionType::NoExceptionType; using mindspore::MsLogLevel::INFO; class MindDataTestCutMixBatchOp : public UT::CVOP::CVOpCommon { protected: MindDataTestCutMixBatchOp() : CVOpCommon() {} }; TEST_F(MindDataTestCutMixBatchOp, TestSuccess1) { MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp success1 case"; std::shared_ptr batched_tensor; std::shared_ptr batched_labels; Tensor::CreateEmpty(TensorShape({2, input_tensor_->shape()[0], input_tensor_->shape()[1], input_tensor_->shape()[2]}), input_tensor_->type(), &batched_tensor); for (int i = 0; i < 2; i++) { batched_tensor->InsertTensor({i}, input_tensor_); } Tensor::CreateFromVector(std::vector({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels); std::shared_ptr op = std::make_shared(ImageBatchFormat::kNHWC, 1.0, 1.0); TensorRow in; in.push_back(batched_tensor); in.push_back(batched_labels); TensorRow out; ASSERT_TRUE(op->Compute(in, &out).IsOk()); EXPECT_EQ(in.at(0)->shape()[0], out.at(0)->shape()[0]); EXPECT_EQ(in.at(0)->shape()[1], out.at(0)->shape()[1]); EXPECT_EQ(in.at(0)->shape()[2], out.at(0)->shape()[2]); EXPECT_EQ(in.at(0)->shape()[3], out.at(0)->shape()[3]); EXPECT_EQ(in.at(1)->shape()[0], out.at(1)->shape()[0]); EXPECT_EQ(in.at(1)->shape()[1], out.at(1)->shape()[1]); } TEST_F(MindDataTestCutMixBatchOp, TestSuccess2) { MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp success2 case"; std::shared_ptr batched_tensor; std::shared_ptr batched_labels; std::shared_ptr chw_tensor; ASSERT_TRUE(HwcToChw(input_tensor_, &chw_tensor).IsOk()); Tensor::CreateEmpty(TensorShape({2, chw_tensor->shape()[0], chw_tensor->shape()[1], chw_tensor->shape()[2]}), chw_tensor->type(), &batched_tensor); for (int i = 0; i < 2; i++) { batched_tensor->InsertTensor({i}, chw_tensor); } Tensor::CreateFromVector(std::vector({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels); std::shared_ptr op = std::make_shared(ImageBatchFormat::kNCHW, 1.0, 0.5); TensorRow in; in.push_back(batched_tensor); in.push_back(batched_labels); TensorRow out; ASSERT_TRUE(op->Compute(in, &out).IsOk()); EXPECT_EQ(in.at(0)->shape()[0], out.at(0)->shape()[0]); EXPECT_EQ(in.at(0)->shape()[1], out.at(0)->shape()[1]); EXPECT_EQ(in.at(0)->shape()[2], out.at(0)->shape()[2]); EXPECT_EQ(in.at(0)->shape()[3], out.at(0)->shape()[3]); EXPECT_EQ(in.at(1)->shape()[0], out.at(1)->shape()[0]); EXPECT_EQ(in.at(1)->shape()[1], out.at(1)->shape()[1]); } TEST_F(MindDataTestCutMixBatchOp, TestFail1) { // This is a fail case because our labels are not batched and are 1-dimensional MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp fail1 case"; std::shared_ptr labels; Tensor::CreateFromVector(std::vector({0, 1, 1, 0}), TensorShape({4}), &labels); std::shared_ptr op = std::make_shared(ImageBatchFormat::kNHWC, 1.0, 1.0); TensorRow in; in.push_back(input_tensor_); in.push_back(labels); TensorRow out; ASSERT_FALSE(op->Compute(in, &out).IsOk()); } TEST_F(MindDataTestCutMixBatchOp, TestFail2) { // This should fail because the image_batch_format provided is not the same as the actual format of the images MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp fail2 case"; std::shared_ptr batched_tensor; std::shared_ptr batched_labels; Tensor::CreateEmpty(TensorShape({2, input_tensor_->shape()[0], input_tensor_->shape()[1], input_tensor_->shape()[2]}), input_tensor_->type(), &batched_tensor); for (int i = 0; i < 2; i++) { batched_tensor->InsertTensor({i}, input_tensor_); } Tensor::CreateFromVector(std::vector({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels); std::shared_ptr op = std::make_shared(ImageBatchFormat::kNCHW, 1.0, 1.0); TensorRow in; in.push_back(batched_tensor); in.push_back(batched_labels); TensorRow out; ASSERT_FALSE(op->Compute(in, &out).IsOk()); }