1 /**
2 * Copyright 2019 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/random_rotation_op.h"
19 #include "minddata/dataset/core/cv_tensor.h"
20 #include "minddata/dataset/kernels/data/to_float16_op.h"
21 #include "utils/log_adapter.h"
22
23 using namespace mindspore::dataset;
24 using mindspore::LogStream;
25 using mindspore::ExceptionType::NoExceptionType;
26 using mindspore::MsLogLevel::INFO;
27
28 class MindDataTestToFloat16Op : public UT::CVOP::CVOpCommon {
29 public:
MindDataTestToFloat16Op()30 MindDataTestToFloat16Op() : CVOpCommon() {}
31 };
32
TEST_F(MindDataTestToFloat16Op,TestOp)33 TEST_F(MindDataTestToFloat16Op, TestOp) {
34 MS_LOG(INFO) << "Doing TestRandomRotationOp::TestOp.";
35 std::shared_ptr<Tensor> output_tensor;
36 float s_degree = -180;
37 float e_degree = 180;
38 // use compute center to use for rotation
39 std::vector<float> center = {};
40 bool expand = false;
41 std::unique_ptr<RandomRotationOp> op(
42 new RandomRotationOp(s_degree, e_degree, InterpolationMode::kLinear, expand, center));
43 EXPECT_TRUE(op->OneToOne());
44 Status s = op->Compute(input_tensor_, &output_tensor);
45 EXPECT_TRUE(s.IsOk());
46 EXPECT_EQ(input_tensor_->shape()[0], output_tensor->shape()[0]);
47 EXPECT_EQ(input_tensor_->shape()[1], output_tensor->shape()[1]);
48
49 std::unique_ptr<ToFloat16Op> to_float_op(new ToFloat16Op());
50 std::shared_ptr<Tensor> output_tensor1;
51 s = op->Compute(output_tensor, &output_tensor1);
52 EXPECT_EQ(output_tensor->shape()[0], output_tensor1->shape()[0]);
53 EXPECT_EQ(output_tensor->shape()[1], output_tensor1->shape()[1]);
54 }
55