/** * 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 "common/common_test.h" #include "ops/crop.h" #include "ir/dtype/type.h" #include "ir/value.h" #include "abstract/dshape.h" #include "utils/tensor_construct_utils.h" namespace mindspore { namespace ops { class TestCrop : public UT::Common { public: TestCrop() {} void SetUp() {} void TearDown() {} }; TEST_F(TestCrop, test_ops_crop1) { auto crop = std::make_shared(); crop->Init(1, std::vector{1, 1, 1, 1}); std::vector ret = crop->get_offsets(); EXPECT_EQ(crop->get_axis(), 1); for (auto item : ret) { EXPECT_EQ(item, 1); } auto tensor_x1 = std::make_shared(kNumberTypeFloat32, std::vector{2, 2}); auto tensor_x2 = std::make_shared(kNumberTypeInt32, std::vector{1}); MS_EXCEPTION_IF_NULL(tensor_x1); MS_EXCEPTION_IF_NULL(tensor_x2); auto tensor_x1_data = reinterpret_cast(tensor_x1->data_c()); *tensor_x1_data = 1.0; tensor_x1_data++; *tensor_x1_data = 2.0; tensor_x1_data++; *tensor_x1_data = 3.0; tensor_x1_data++; *tensor_x1_data = 4.0; tensor_x1_data++; auto tensor_x2_data = reinterpret_cast(tensor_x2->data_c()); *tensor_x2_data = 1; auto abstract = crop->Infer({tensor_x1->ToAbstract(), tensor_x2->ToAbstract()}); MS_EXCEPTION_IF_NULL(abstract); EXPECT_EQ(abstract->isa(), true); auto shape_ptr = abstract->BuildShape(); MS_EXCEPTION_IF_NULL(shape_ptr); EXPECT_EQ(shape_ptr->isa(), true); auto shape = shape_ptr->cast(); MS_EXCEPTION_IF_NULL(shape); auto shape_vec = shape->shape(); auto type = abstract->BuildType(); MS_EXCEPTION_IF_NULL(type); EXPECT_EQ(type->isa(), true); auto tensor_type = type->cast(); MS_EXCEPTION_IF_NULL(tensor_type); auto data_type = tensor_type->element(); MS_EXCEPTION_IF_NULL(data_type); EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); EXPECT_EQ(shape_vec.size(), 1); EXPECT_EQ(shape_vec[0], 1); } } // namespace ops } // namespace mindspore