/** * 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/strided_slice.h" #include "ir/dtype/type.h" #include "ir/value.h" #include "abstract/dshape.h" #include "utils/tensor_construct_utils.h" namespace mindspore { namespace ops { namespace { template void SetTensorData(void *data, std::vector num) { MS_EXCEPTION_IF_NULL(data); auto tensor_data = reinterpret_cast(data); MS_EXCEPTION_IF_NULL(tensor_data); for (size_t index = 0; index < num.size(); ++index) { *tensor_data = num[index]; } } } // namespace class TestStridedSlice : public UT::Common { public: TestStridedSlice() {} void SetUp() {} void TearDown() {} }; TEST_F(TestStridedSlice, test_ops_stridedslice1) { auto stridedslice = std::make_shared(); stridedslice->Init(0, 0, 0, 0, 0); EXPECT_EQ(stridedslice->get_begin_mask(), 0); EXPECT_EQ(stridedslice->get_end_mask(), 0); EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector{3, 3, 3}); auto begin = MakeValue(std::vector{1, 0, 0}); auto end = MakeValue(std::vector{2, 1, 3}); auto strides = MakeValue(std::vector{1, 1, 1}); MS_EXCEPTION_IF_NULL(tensor_x); MS_EXCEPTION_IF_NULL(begin); MS_EXCEPTION_IF_NULL(end); MS_EXCEPTION_IF_NULL(strides); auto abstract = stridedslice->Infer({tensor_x->ToAbstract(), begin->ToAbstract(), end->ToAbstract(), strides->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(), 3); EXPECT_EQ(shape_vec[0], 1); EXPECT_EQ(shape_vec[1], 1); EXPECT_EQ(shape_vec[2], 3); } /* TEST_F(TestStridedSlice, test_ops_stridedslice2) { auto stridedslice = std::make_shared(); stridedslice->Init(0, 0, 0, 0, 0); EXPECT_EQ(stridedslice->get_begin_mask(), 0); EXPECT_EQ(stridedslice->get_end_mask(), 0); EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector{3,3,3}); auto begin = MakeValue(std::vector{1,0,0}); auto end = MakeValue(std::vector{2,2,3}); auto strides =MakeValue(std::vector{1,1,1}); MS_EXCEPTION_IF_NULL(tensor_x); MS_EXCEPTION_IF_NULL(begin); MS_EXCEPTION_IF_NULL(end); MS_EXCEPTION_IF_NULL(strides); auto abstract = stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->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(), 3); EXPECT_EQ(shape_vec[0], 1); EXPECT_EQ(shape_vec[1], 2); EXPECT_EQ(shape_vec[2], 3); } TEST_F(TestStridedSlice, test_ops_stridedslice3) { auto stridedslice = std::make_shared(); stridedslice->Init(0, 0, 0, 0, 0); EXPECT_EQ(stridedslice->get_begin_mask(), 0); EXPECT_EQ(stridedslice->get_end_mask(), 0); EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector{3,3,3}); auto begin = MakeValue(std::vector{1,0,0}); auto end = MakeValue(std::vector{2,-3,3}); auto strides =MakeValue(std::vector{1,-1,1}); MS_EXCEPTION_IF_NULL(tensor_x); MS_EXCEPTION_IF_NULL(begin); MS_EXCEPTION_IF_NULL(end); MS_EXCEPTION_IF_NULL(strides); auto abstract = stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->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(), 3); EXPECT_EQ(shape_vec[0], 1); EXPECT_EQ(shape_vec[1], 2); EXPECT_EQ(shape_vec[2], 3); } TEST_F(TestStridedSlice, test_ops_stridedslice4) { auto stridedslice = std::make_shared(); stridedslice->Init(0, 0, 0, 0, 0); EXPECT_EQ(stridedslice->get_begin_mask(), 0); EXPECT_EQ(stridedslice->get_end_mask(), 0); EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector{5}); auto begin = MakeValue(std::vector{1}); auto end = MakeValue(std::vector{-2}); auto strides =MakeValue(std::vector{1}); MS_EXCEPTION_IF_NULL(tensor_x); MS_EXCEPTION_IF_NULL(begin); MS_EXCEPTION_IF_NULL(end); MS_EXCEPTION_IF_NULL(strides); auto abstract = stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->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], 2); }*/ } // namespace ops } // namespace mindspore