colin
/
TIM-VX
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add softmax unit test (#274) 

https://github.com/VeriSilicon/TIM-VX/issues/266

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>

Co-authored-by: Chen Xin <jack.chen@verisilicon.com>
This commit is contained in:
chxin66 2022-01-19 14:54:39 +08:00 committed by GitHub
parent a02900d135
commit 32308f62c5
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 279 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

279
src/tim/vx/ops/softmax_test.cc Normal file
View File

@ -0,0 +1,279 @@
/****************************************************************************
*
* 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/softmax.h"
#include "test_utils.h"
#include "gtest/gtest.h"
TEST(Softmax, shape_3_1_float_axis_0) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 1});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
-1, 0, 1,
};
std::vector<float> golden = {
0.09003057, 0.24472848, 0.66524094
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
(*op).BindInputs({input_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_TRUE(ArraysMatch(golden, output, 1e-5f));
}
TEST(Softmax, shape_3_4_float_axis_0) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 4});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
1, 2, 3,
1, 2, 3,
1, 2, 3,
1, 2, 3,
};
std::vector<float> golden = {
0.09003057, 0.24472848, 0.66524094,
0.09003057, 0.24472848, 0.66524094,
0.09003057, 0.24472848, 0.66524094,
0.09003057, 0.24472848, 0.66524094,
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
(*op).BindInputs({input_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);
// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}
TEST(Softmax, shape_3_4_float_axis_1) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 4});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
1, 2, 3,
1, 2, 3,
1, 2, 3,
1, 2, 3,
};
std::vector<float> golden = {
0.25, 0.25, 0.25,
0.25, 0.25, 0.25,
0.25, 0.25, 0.25,
0.25, 0.25, 0.25,
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,1);
(*op).BindInputs({input_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);
// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}
TEST(Softmax, shape_3_3_2_float_axis_0) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 3, 2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
1, 2, 3,
1, 2, 3,
1, 2, 3,
2, 3, 5,
2, 3, 5,
2, 3, 5,
};
std::vector<float> golden = {
0.09003057, 0.24472848, 0.66524094,
0.09003057, 0.24472848, 0.66524094,
0.09003057, 0.24472848, 0.66524094,
0.04201007, 0.11419519, 0.8437947,
0.04201007, 0.11419519, 0.8437947,
0.04201007, 0.11419519, 0.8437947,
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
(*op).BindInputs({input_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);
// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}
TEST(Softmax, shape_3_3_2_float_axis_1) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 3, 2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
1, 2, 3,
1, 2, 3,
1, 2, 3,
2, 3, 5,
2, 3, 5,
2, 3, 5,
};
std::vector<float> golden = {
0.33333334, 0.33333334, 0.33333334,
0.33333334, 0.33333334, 0.33333334,
0.33333334, 0.33333334, 0.33333334,
0.33333334, 0.33333334, 0.33333334,
0.33333334, 0.33333334, 0.33333334,
0.33333334, 0.33333334, 0.33333334,
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,1);
(*op).BindInputs({input_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);
// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}
TEST(Softmax, shape_3_3_2_float_axis_2) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({3, 3, 2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {
1, 2, 3,
1, 2, 3,
1, 2, 3,
2, 3, 5,
2, 3, 5,
2, 3, 5,
};
std::vector<float> golden = {
0.26894143, 0.26894143, 0.11920291,
0.26894143, 0.26894143, 0.11920291,
0.26894143, 0.26894143, 0.11920291,
0.7310586 , 0.7310586 , 0.880797,
0.7310586 , 0.7310586 , 0.880797,
0.7310586 , 0.7310586 , 0.880797,
};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,2);
(*op).BindInputs({input_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);
// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}