TIM-VX/src/tim/vx/ops/maxunpool2d_test.cc

117 lines
4.8 KiB
C++

/****************************************************************************
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* Copyright (c) 2021 Vivante Corporation
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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#include "tim/vx/context.h"
#include "tim/vx/graph.h"
#include "tim/vx/ops/maxunpool2d.h"
#include "gtest/gtest.h"
TEST(MaxUnpool2d, shape_2_2_1_fp32_kernel_2_stride_2) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType in_shape({2, 2, 1});
tim::vx::ShapeType out_shape({3, 3, 1});
tim::vx::TensorSpec values_spec(tim::vx::DataType::FLOAT32,
in_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec indices_spec(tim::vx::DataType::UINT8,
in_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
out_shape, tim::vx::TensorAttribute::OUTPUT);
auto values_tensor = graph->CreateTensor(values_spec);
auto indices_tensor = graph->CreateTensor(indices_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> values = {
5, 6,
8, 9 };
std::vector<uint8_t> indices = {
3, 2,
1, 0 };
std::vector<float> golden = {
0, 0, 0,
0, 5, 6,
0, 8, 9 };
EXPECT_TRUE(values_tensor->CopyDataToTensor(values.data(), values.size()*4));
EXPECT_TRUE(indices_tensor->CopyDataToTensor(indices.data(), indices.size()*4));
std::array<uint32_t, 2> ksize = {2, 2};
std::array<uint32_t, 2> stride = {2, 2};
auto op = graph->CreateOperation<tim::vx::ops::MaxUnpool2d>(ksize, stride);
(*op).BindInputs({values_tensor, indices_tensor}).BindOutputs({output_tensor});
EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());
std::vector<float> output(golden.size());
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}
TEST(MaxUnpool2d, shape_2_2_1_uint8_kernel_2_stride_2) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType in_shape({2, 2, 1});
tim::vx::ShapeType out_shape({4, 4, 1});
tim::vx::Quantization io_quant(tim::vx::QuantType::ASYMMETRIC, 1, 0);
tim::vx::TensorSpec values_spec(tim::vx::DataType::UINT8,
in_shape, tim::vx::TensorAttribute::INPUT, io_quant);
tim::vx::TensorSpec indices_spec(tim::vx::DataType::UINT8,
in_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::UINT8,
out_shape, tim::vx::TensorAttribute::OUTPUT, io_quant);
auto values_tensor = graph->CreateTensor(values_spec);
auto indices_tensor = graph->CreateTensor(indices_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<uint8_t> values = {
5, 6,
11, 12};
std::vector<uint8_t> indices = {
3, 2,
3, 2};
std::vector<uint8_t> golden = {
0, 0, 0, 0,
0, 5, 6, 0,
0, 0, 0, 0,
0, 11, 12, 0 };
EXPECT_TRUE(values_tensor->CopyDataToTensor(values.data(), values.size()));
EXPECT_TRUE(indices_tensor->CopyDataToTensor(indices.data(), indices.size()));
std::array<uint32_t, 2> ksize = {2, 2};
std::array<uint32_t, 2> stride = {2, 2};
auto op = graph->CreateOperation<tim::vx::ops::MaxUnpool2d>(ksize, stride);
(*op).BindInputs({values_tensor, indices_tensor}).BindOutputs({output_tensor});
EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());
std::vector<uint8_t> output(golden.size());
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}