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Added two reduce layout infer unittest 

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>
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Chen Xin 2022-09-26 14:40:17 +08:00 committed by Sven
parent 72f2c5b69e
commit 4c6299e7fd
1 changed files with 114 additions and 0 deletions
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src/tim/transform/reduce_layout_inference_test.cc Normal file
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/****************************************************************************
*
* Copyright (c) 2022 Vivante Corporation
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
*****************************************************************************/
#include "tim/vx/context.h"
#include "tim/vx/graph.h"
#include "tim/vx/ops.h"
#include "test_utils.h"
#include "gtest/gtest.h"
#include "tim/transform/layout_inference.h"
#include "permute_vector.h"
TEST(Reduce_Min, notalign_1_2_0) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType input_shape({3,1,2}); //input_pv={1,2,0}
tim::vx::ShapeType output_shape({2, 1});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape,
tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec reduce_sum_spec(tim::vx::DataType::FLOAT32, output_shape,
tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto reduce_sum_out = graph->CreateTensor(reduce_sum_spec);
std::vector<int32_t> axis = {1};
auto reduce_sum =
graph->CreateOperation<tim::vx::ops::ReduceMin>(axis, false);
(*reduce_sum).BindInputs({input_tensor}).BindOutputs({reduce_sum_out});
std::vector<float> in_data = {0.4, 0.2, 0.3, 0.4, 0.5, 0.6};
std::vector<float> golden = {
0.2, 0.4
};
std::map<std::shared_ptr<tim::vx::Tensor>,
std::shared_ptr<tim::transform::IPermuteVector>>
tensor_pv_map;
std::shared_ptr<tim::transform::IPermuteVector> pv =
std::make_shared<tim::transform::PermuteVector<3>>(
std::initializer_list<uint32_t>({1,2,0}));
tensor_pv_map.insert({input_tensor, pv});
auto transform = tim::transform::LayoutInference(graph, ctx, tensor_pv_map);
auto infer_graph = transform.first;
EXPECT_TRUE(infer_graph->Compile());
auto graph_io_map = transform.second;
auto infer_input = graph_io_map[graph->InputsTensor()[0]];
auto infer_output = graph_io_map[graph->OutputsTensor()[0]];
EXPECT_TRUE(infer_input->CopyDataToTensor(in_data.data(), in_data.size()));
EXPECT_TRUE(infer_graph->Run());
std::vector<float> output(golden.size());
EXPECT_TRUE(infer_output->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}
TEST(Reduce_Min, notalign_1_0_2) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType input_shape({3,2,1}); //input_pv={1,0,2}
tim::vx::ShapeType output_shape({2, 1});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape,
tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec reduce_sum_spec(tim::vx::DataType::FLOAT32, output_shape,
tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto reduce_sum_out = graph->CreateTensor(reduce_sum_spec);
std::vector<int32_t> axis = {1};
auto reduce_sum =
graph->CreateOperation<tim::vx::ops::ReduceMin>(axis, false);
(*reduce_sum).BindInputs({input_tensor}).BindOutputs({reduce_sum_out});
std::vector<float> in_data = {0.4, 0.2, 0.3, 0.4, 0.5, 0.6};
std::vector<float> golden = {
0.2, 0.4
};
std::map<std::shared_ptr<tim::vx::Tensor>,
std::shared_ptr<tim::transform::IPermuteVector>>
tensor_pv_map;
std::shared_ptr<tim::transform::IPermuteVector> pv =
std::make_shared<tim::transform::PermuteVector<3>>(
std::initializer_list<uint32_t>({1,0,2}));
tensor_pv_map.insert({input_tensor, pv});
auto transform = tim::transform::LayoutInference(graph, ctx, tensor_pv_map);
auto infer_graph = transform.first;
EXPECT_TRUE(infer_graph->Compile());
auto graph_io_map = transform.second;
auto infer_input = graph_io_map[graph->InputsTensor()[0]];
auto infer_output = graph_io_map[graph->OutputsTensor()[0]];
EXPECT_TRUE(infer_input->CopyDataToTensor(in_data.data(), in_data.size()));
EXPECT_TRUE(infer_graph->Run());
std::vector<float> output(golden.size());
EXPECT_TRUE(infer_output->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}