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Diffstat (limited to 'compiler/locomotiv/src/Node/TensorReduce.test.cpp')
| -rw-r--r-- | compiler/locomotiv/src/Node/TensorReduce.test.cpp | 104 |
1 files changed, 104 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/TensorReduce.test.cpp b/compiler/locomotiv/src/Node/TensorReduce.test.cpp new file mode 100644 index 000000000..68398cacd --- /dev/null +++ b/compiler/locomotiv/src/Node/TensorReduce.test.cpp @@ -0,0 +1,104 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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 "NodeExecution.h" + +#include "locomotiv/NodeData.h" +#include "NodeDataImpl.h" +#include "NodeDomain.h" + +#include <nncc/core/ADT/tensor/Index.h> +#include <nncc/core/ADT/tensor/Shape.h> +#include <nncc/core/ADT/tensor/Buffer.h> +#include <nncc/core/ADT/tensor/LexicalLayout.h> + +#include <gtest/gtest.h> + +using nncc::core::ADT::tensor::Index; +using nncc::core::ADT::tensor::Shape; +using nncc::core::ADT::tensor::LexicalLayout; +using nncc::core::ADT::tensor::make_buffer; + +TEST(NodeExecution_Fixed_Reduce_Mean, f32_0) +{ + // Make pull-TensorReduce(Mean) graph + auto g = loco::make_graph(); + auto pull_input = g->nodes()->create<loco::Pull>(); + pull_input->dtype(loco::DataType::FLOAT32); + pull_input->shape({1, 2, 2}); + auto reduce_node = g->nodes()->create<loco::TensorReduce>(); + reduce_node->input(pull_input); + reduce_node->axes()->insert(0); + reduce_node->axes()->insert(1); + reduce_node->func(loco::ReduceFunc::Mean); + + // Make and assign data to pull node + auto pull_input_buf = make_buffer<float, LexicalLayout>({1, 2, 2}); + pull_input_buf.at(Index{0, 0, 0}) = 1.1f; + pull_input_buf.at(Index{0, 0, 1}) = 2.2f; + pull_input_buf.at(Index{0, 1, 0}) = 5.5f; + pull_input_buf.at(Index{0, 1, 1}) = 6.6f; + auto pull_input_data = locomotiv::make_data(pull_input_buf); + locomotiv::annot_data(pull_input, std::move(pull_input_data)); + locomotiv::annot_domain(pull_input, loco::Domain::Tensor); + + locomotiv::NodeExecution::get().run(reduce_node); + + auto kShape = Shape{1, 1, 2}; + auto reduce_data = locomotiv::annot_data(reduce_node); + ASSERT_NE(reduce_data, nullptr); + ASSERT_EQ(reduce_data->dtype(), loco::DataType::FLOAT32); + ASSERT_EQ(*(reduce_data->shape()), kShape); + ASSERT_FLOAT_EQ(reduce_data->as_f32_bufptr()->at(Index{0, 0, 0}), 3.3f); + ASSERT_FLOAT_EQ(reduce_data->as_f32_bufptr()->at(Index{0, 0, 1}), 4.4f); + + ASSERT_EQ(locomotiv::annot_domain(reduce_node), loco::Domain::Tensor); +} + +TEST(NodeExecution_Fixed_Reduce_Mean, f32_1) +{ + // Make pull-TensorReduce(Mean) graph + auto g = loco::make_graph(); + auto pull_input = g->nodes()->create<loco::Pull>(); + pull_input->dtype(loco::DataType::FLOAT32); + pull_input->shape({1, 2, 2}); + auto reduce_node = g->nodes()->create<loco::TensorReduce>(); + reduce_node->input(pull_input); + reduce_node->axes()->insert(1); + reduce_node->axes()->insert(2); + reduce_node->func(loco::ReduceFunc::Mean); + + // Make and assign data to pull node + auto pull_input_buf = make_buffer<float, LexicalLayout>({1, 2, 2}); + pull_input_buf.at(Index{0, 0, 0}) = 1.1f; + pull_input_buf.at(Index{0, 0, 1}) = 2.2f; + pull_input_buf.at(Index{0, 1, 0}) = 5.5f; + pull_input_buf.at(Index{0, 1, 1}) = 6.6f; + auto pull_input_data = locomotiv::make_data(pull_input_buf); + locomotiv::annot_data(pull_input, std::move(pull_input_data)); + locomotiv::annot_domain(pull_input, loco::Domain::Tensor); + + locomotiv::NodeExecution::get().run(reduce_node); + + auto kShape = Shape{1, 1, 1}; + auto reduce_data = locomotiv::annot_data(reduce_node); + ASSERT_NE(reduce_data, nullptr); + ASSERT_EQ(reduce_data->dtype(), loco::DataType::FLOAT32); + ASSERT_EQ(*(reduce_data->shape()), kShape); + ASSERT_FLOAT_EQ(reduce_data->as_f32_bufptr()->at(Index{0, 0, 0}), 3.85f); + + ASSERT_EQ(locomotiv::annot_domain(reduce_node), loco::Domain::Tensor); +} |