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1 /**
2  * Copyright 2020 Huawei Technologies Co., Ltd
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 #include "common/common.h"
17 #include "common/cvop_common.h"
18 #include "minddata/dataset/kernels/image/cutmix_batch_op.h"
19 #include "utils/log_adapter.h"
20 
21 using namespace mindspore::dataset;
22 using mindspore::LogStream;
23 using mindspore::ExceptionType::NoExceptionType;
24 using mindspore::MsLogLevel::INFO;
25 
26 class MindDataTestCutMixBatchOp : public UT::CVOP::CVOpCommon {
27  protected:
MindDataTestCutMixBatchOp()28   MindDataTestCutMixBatchOp() : CVOpCommon() {}
29 };
30 
TEST_F(MindDataTestCutMixBatchOp,TestSuccess1)31 TEST_F(MindDataTestCutMixBatchOp, TestSuccess1) {
32   MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp success1 case";
33   std::shared_ptr<Tensor> input_tensor_resized;
34   std::shared_ptr<Tensor> batched_tensor;
35   std::shared_ptr<Tensor> batched_labels;
36   Resize(input_tensor_, &input_tensor_resized, 227, 403);
37 
38   Tensor::CreateEmpty(TensorShape({2, input_tensor_resized->shape()[0], input_tensor_resized->shape()[1],
39                       input_tensor_resized->shape()[2]}), input_tensor_resized->type(), &batched_tensor);
40   for (int i = 0; i < 2; i++) {
41     batched_tensor->InsertTensor({i}, input_tensor_resized);
42   }
43   Tensor::CreateFromVector(std::vector<uint32_t>({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels);
44   std::shared_ptr<CutMixBatchOp> op = std::make_shared<CutMixBatchOp>(ImageBatchFormat::kNHWC, 1.0, 1.0);
45   TensorRow in;
46   in.push_back(batched_tensor);
47   in.push_back(batched_labels);
48   TensorRow out;
49   ASSERT_TRUE(op->Compute(in, &out).IsOk());
50 
51   EXPECT_EQ(in.at(0)->shape()[0], out.at(0)->shape()[0]);
52   EXPECT_EQ(in.at(0)->shape()[1], out.at(0)->shape()[1]);
53   EXPECT_EQ(in.at(0)->shape()[2], out.at(0)->shape()[2]);
54   EXPECT_EQ(in.at(0)->shape()[3], out.at(0)->shape()[3]);
55 
56   EXPECT_EQ(in.at(1)->shape()[0], out.at(1)->shape()[0]);
57   EXPECT_EQ(in.at(1)->shape()[1], out.at(1)->shape()[1]);
58 }
59 
TEST_F(MindDataTestCutMixBatchOp,TestSuccess2)60 TEST_F(MindDataTestCutMixBatchOp, TestSuccess2) {
61   MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp success2 case";
62   std::shared_ptr<Tensor> input_tensor_resized;
63   std::shared_ptr<Tensor> batched_tensor;
64   std::shared_ptr<Tensor> batched_labels;
65   std::shared_ptr<Tensor> chw_tensor;
66   Resize(input_tensor_, &input_tensor_resized, 227, 403);
67 
68   ASSERT_TRUE(HwcToChw(input_tensor_resized, &chw_tensor).IsOk());
69   Tensor::CreateEmpty(TensorShape({2, chw_tensor->shape()[0], chw_tensor->shape()[1], chw_tensor->shape()[2]}),
70                       chw_tensor->type(), &batched_tensor);
71   for (int i = 0; i < 2; i++) {
72     batched_tensor->InsertTensor({i}, chw_tensor);
73   }
74   Tensor::CreateFromVector(std::vector<uint32_t>({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels);
75   std::shared_ptr<CutMixBatchOp> op = std::make_shared<CutMixBatchOp>(ImageBatchFormat::kNCHW, 1.0, 0.5);
76   TensorRow in;
77   in.push_back(batched_tensor);
78   in.push_back(batched_labels);
79   TensorRow out;
80   ASSERT_TRUE(op->Compute(in, &out).IsOk());
81 
82   EXPECT_EQ(in.at(0)->shape()[0], out.at(0)->shape()[0]);
83   EXPECT_EQ(in.at(0)->shape()[1], out.at(0)->shape()[1]);
84   EXPECT_EQ(in.at(0)->shape()[2], out.at(0)->shape()[2]);
85   EXPECT_EQ(in.at(0)->shape()[3], out.at(0)->shape()[3]);
86 
87   EXPECT_EQ(in.at(1)->shape()[0], out.at(1)->shape()[0]);
88   EXPECT_EQ(in.at(1)->shape()[1], out.at(1)->shape()[1]);
89 }
90 
TEST_F(MindDataTestCutMixBatchOp,TestFail1)91 TEST_F(MindDataTestCutMixBatchOp, TestFail1) {
92   // This is a fail case because our labels are not batched and are 1-dimensional
93   MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp fail1 case";
94   std::shared_ptr<Tensor> labels;
95   Tensor::CreateFromVector(std::vector<uint32_t>({0, 1, 1, 0}), TensorShape({4}), &labels);
96   std::shared_ptr<CutMixBatchOp> op = std::make_shared<CutMixBatchOp>(ImageBatchFormat::kNHWC, 1.0, 1.0);
97   TensorRow in;
98   in.push_back(input_tensor_);
99   in.push_back(labels);
100   TensorRow out;
101   ASSERT_FALSE(op->Compute(in, &out).IsOk());
102 }
103 
TEST_F(MindDataTestCutMixBatchOp,TestFail2)104 TEST_F(MindDataTestCutMixBatchOp, TestFail2) {
105   // This should fail because the image_batch_format provided is not the same as the actual format of the images
106   MS_LOG(INFO) << "Doing MindDataTestCutMixBatchOp fail2 case";
107   std::shared_ptr<Tensor> batched_tensor;
108   std::shared_ptr<Tensor> batched_labels;
109   Tensor::CreateEmpty(TensorShape({2, input_tensor_->shape()[0], input_tensor_->shape()[1], input_tensor_->shape()[2]}),
110                       input_tensor_->type(), &batched_tensor);
111   for (int i = 0; i < 2; i++) {
112     batched_tensor->InsertTensor({i}, input_tensor_);
113   }
114   Tensor::CreateFromVector(std::vector<uint32_t>({0, 1, 1, 0}), TensorShape({2, 2}), &batched_labels);
115   std::shared_ptr<CutMixBatchOp> op = std::make_shared<CutMixBatchOp>(ImageBatchFormat::kNCHW, 1.0, 1.0);
116   TensorRow in;
117   in.push_back(batched_tensor);
118   in.push_back(batched_labels);
119   TensorRow out;
120   ASSERT_FALSE(op->Compute(in, &out).IsOk());
121 }
122