/** * 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/range.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 TestRange : public UT::Common { public: TestRange() {} void SetUp() {} void TearDown() {} }; TEST_F(TestRange, test_ops_range1) { auto range = std::make_shared(); range->Init(1, 3, 34, 4); EXPECT_EQ(range->get_d_type(), 1); EXPECT_EQ(range->get_start(), 3); EXPECT_EQ(range->get_limit(), 34); EXPECT_EQ(range->get_delta(), 4); range->set_d_type(1); range->set_start(3); range->set_limit(34); range->set_delta(4); auto abstract = range->Infer({}); 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(), kNumberTypeInt32); EXPECT_EQ(shape_vec.size(), 1); EXPECT_EQ(shape_vec[0], 8); EXPECT_EQ(range->get_d_type(), 1); EXPECT_EQ(range->get_start(), 3); EXPECT_EQ(range->get_limit(), 34); EXPECT_EQ(range->get_delta(), 4); } TEST_F(TestRange, test_ops_range2) { auto range = std::make_shared(); range->Init(1, 1, 1, 1); EXPECT_EQ(range->get_d_type(), 1); EXPECT_EQ(range->get_start(), 1); EXPECT_EQ(range->get_limit(), 1); EXPECT_EQ(range->get_delta(), 1); range->set_d_type(1); range->set_start(1); range->set_limit(1); range->set_delta(1); auto tensor_x1 = std::make_shared(kNumberTypeFloat32, std::vector{1}); auto tensor_x2 = std::make_shared(kNumberTypeFloat32, std::vector{1}); auto tensor_x3 = std::make_shared(kNumberTypeFloat32, std::vector{1}); MS_EXCEPTION_IF_NULL(tensor_x1); MS_EXCEPTION_IF_NULL(tensor_x2); MS_EXCEPTION_IF_NULL(tensor_x3); auto data_x1 = tensor_x1->data_c(); MS_EXCEPTION_IF_NULL(data_x1); auto val_x1 = reinterpret_cast(data_x1); *val_x1 = 1.0; auto data_x2 = tensor_x2->data_c(); MS_EXCEPTION_IF_NULL(data_x2); auto val_x2 = reinterpret_cast(data_x2); *val_x2 = 42.0; auto data_x3 = tensor_x3->data_c(); MS_EXCEPTION_IF_NULL(data_x3); auto val_x3 = reinterpret_cast(data_x3); *val_x3 = 3.0; auto abstract = range->Infer({tensor_x1->ToAbstract(), tensor_x2->ToAbstract(), tensor_x3->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], 14); EXPECT_EQ(range->get_d_type(), 1); EXPECT_EQ(range->get_start(), 1); EXPECT_EQ(range->get_limit(), 1); EXPECT_EQ(range->get_delta(), 1); } } // namespace ops } // namespace mindspore