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/*
* Copyright (c) 2020 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 "kernels/Concatenation.h"
#include "kernels/TestUtils.h"
#include "luci_interpreter/TestMemoryManager.h"
namespace luci_interpreter
{
namespace kernels
{
namespace
{
using namespace testing;
class ConcatenationTest : public ::testing::Test
{
protected:
void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
std::unique_ptr<IMemoryManager> _memory_manager;
};
TEST_F(ConcatenationTest, Float)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
// Try different 'axis' and expect different results.
{
params.axis = 0;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
kernel.configure();
for (auto t : kernel.getOutputTensors())
{
_memory_manager->allocate_memory(*t);
}
kernel.execute();
EXPECT_THAT(extractTensorData<float>(output_tensor),
FloatArrayNear({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}));
}
{
params.axis = -2; // Same as '0'.
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
kernel.configure();
_memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<float>(output_tensor),
FloatArrayNear({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}));
}
{
params.axis = 1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
kernel.configure();
_memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<float>(output_tensor),
FloatArrayNear({1, 2, 3, 7, 8, 9, 4, 5, 6, 10, 11, 12}));
}
{
params.axis = -1; // Same as '1'.
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
kernel.configure();
_memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<float>(output_tensor),
FloatArrayNear({1, 2, 3, 7, 8, 9, 4, 5, 6, 10, 11, 12}));
}
}
TEST_F(ConcatenationTest, Input_Number_Check_NEG)
{
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Invalid_Axis_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = -3;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Mismatching_Input_Type_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<uint8_t> input2_data{7, 8, 9, 10, 11, 12};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor = makeInputTensor<DataType::U8>({2, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Mismatching_Input_Dimension_Num_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::FLOAT32>({1, 2, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Mismatching_Input_Dimension_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12, 13, 14, 15};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::FLOAT32>({3, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Int8_Mismatching_Input_Type_NEG)
{
std::vector<uint8_t> input1_data{1, 2, 3, 4};
std::vector<int8_t> input2_data{5, 6, 7, 8};
Tensor input1_tensor = makeInputTensor<DataType::U8>({2, 2}, input1_data, _memory_manager.get());
Tensor input2_tensor = makeInputTensor<DataType::S8>({2, 2}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::S8);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Int8_Mismatching_Input_Output_Quant_Params_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12};
int quantized_dimension = 3;
std::vector<float> scales{0.1, 0.2, 0.3};
std::vector<int32_t> zero_points{1, -1, 1};
Tensor input1_tensor = makeInputTensor<DataType::S8>(
{1, 1, 2, 3}, scales, zero_points, quantized_dimension, input1_data, _memory_manager.get());
Tensor input2_tensor = makeInputTensor<DataType::S8>(
{1, 1, 2, 3}, scales, zero_points, quantized_dimension, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::S8, scales.at(0), zero_points.at(0));
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
TEST_F(ConcatenationTest, Int8_Mismatching_Zero_Point_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4};
std::vector<float> input2_data{5, 6, 7, 8};
float scale = 0.1;
int32_t zero_point_1 = 1;
int32_t zero_point_2 = -1;
Tensor input1_tensor =
makeInputTensor<DataType::S8>({2, 2}, scale, zero_point_1, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::S8>({2, 2}, scale, zero_point_2, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::S8, scale, zero_point_1);
ConcatenationParams params{};
params.axis = -1;
params.activation = luci::FusedActFunc::NONE;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
// TODO: Remove this test when concat w/ fused_activation is supported
TEST_F(ConcatenationTest, With_Fused_Activation_NEG)
{
std::vector<float> input1_data{1, 2, 3, 4, 5, 6};
std::vector<float> input2_data{7, 8, 9, 10, 11, 12};
Tensor input1_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input1_data, _memory_manager.get());
Tensor input2_tensor =
makeInputTensor<DataType::FLOAT32>({2, 3}, input2_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
ConcatenationParams params{};
params.axis = 1;
params.activation = luci::FusedActFunc::RELU;
Concatenation kernel({&input1_tensor, &input2_tensor}, &output_tensor, params);
EXPECT_ANY_THROW(kernel.configure());
}
} // namespace
} // namespace kernels
} // namespace luci_interpreter
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