STT-tensorflow/tensorflow/lite/kernels/tile_test.cc
Karim Nosir 2a96849f47 Update source files with used includes.
PiperOrigin-RevId: 316589177
Change-Id: I0aba0ed1cf9ff478e7890fa53a7749bf844bd26d
2020-06-15 18:42:14 -07:00

251 lines
8.9 KiB
C++

/* Copyright 2017 The TensorFlow Authors. 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 <stdint.h>
#include <initializer_list>
#include <string>
#include <vector>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "tensorflow/lite/kernels/test_util.h"
#include "tensorflow/lite/schema/schema_generated.h"
#include "tensorflow/lite/string_type.h"
namespace tflite {
namespace {
using ::testing::ElementsAreArray;
class TileOpBaseModel : public SingleOpModel {
public:
template <typename T>
void SetInput(std::initializer_list<T> data) {
PopulateTensor<T>(input_, data);
}
template <typename T>
void SetMultipliers(std::initializer_list<T> data) {
PopulateTensor<T>(multipliers_, data);
}
template <typename T>
std::vector<T> GetOutput() {
return ExtractVector<T>(output_);
}
std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
protected:
int input_;
int multipliers_;
int output_;
};
template <typename T>
class TileOpConstModel : public TileOpBaseModel {
public:
TileOpConstModel(std::initializer_list<int> input_shape,
TensorType input_type, TensorType multiply_type,
std::initializer_list<T> multipliers_data) {
input_ = AddInput(input_type);
multipliers_ = AddConstInput(multiply_type, multipliers_data,
{static_cast<int>(multipliers_data.size())});
output_ = AddOutput(input_type);
SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
}
};
class TileOpDynamicModel : public TileOpBaseModel {
public:
TileOpDynamicModel(std::initializer_list<int> input_shape,
TensorType input_type, TensorType multiply_type) {
input_ = AddInput(input_type);
multipliers_ = AddInput(multiply_type);
output_ = AddOutput(input_type);
SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
}
};
enum class TestType {
kConst = 0,
kDynamic = 1,
};
template <typename InputType, typename MultipliersType = int32_t>
void Check(std::initializer_list<int> input_shape,
std::initializer_list<InputType> input_data,
std::initializer_list<MultipliersType> multipliers_data,
std::initializer_list<int> exp_output_shape,
std::initializer_list<InputType> exp_output_data,
TensorType input_type, TensorType multiply_type,
TestType test_type) {
switch (test_type) {
case TestType::kConst: {
TileOpConstModel<MultipliersType> m(input_shape, input_type,
multiply_type, multipliers_data);
m.SetInput(input_data);
m.Invoke();
EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(exp_output_shape));
EXPECT_THAT(m.template GetOutput<InputType>(),
ElementsAreArray(exp_output_data));
return;
}
case TestType::kDynamic: {
TileOpDynamicModel m(input_shape, input_type, multiply_type);
m.SetInput(input_data);
m.SetMultipliers(multipliers_data);
m.Invoke();
EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(exp_output_shape));
EXPECT_THAT(m.template GetOutput<InputType>(),
ElementsAreArray(exp_output_data));
return;
}
}
}
class TileTest : public ::testing::TestWithParam<TestType> {};
TEST_P(TileTest, Float32Vector) {
Check<float>(/*input_shape=*/{3},
/*input_data=*/{1.0, 2.0, 3.0},
/*multipliers_data=*/{2}, /*exp_output_shape=*/{6},
/*exp_output_data=*/{1.0, 2.0, 3.0, 1.0, 2.0, 3.0},
/*input_type=*/TensorType_FLOAT32,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Float32Matrix) {
Check<float>(
/*input_shape=*/{2, 3},
/*input_data=*/{11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/
{11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
/*input_type=*/TensorType_FLOAT32,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Float32HighDimension) {
Check<float>(
/*input_shape=*/{1, 2, 3},
/*input_data=*/{11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
/*multipliers_data=*/{2, 3, 1}, /*exp_output_shape=*/{2, 6, 3},
/*exp_output_data=*/{11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f,
13.f, 21.f, 22.f, 23.f, 11.f, 12.f, 13.f, 21.f,
22.f, 23.f, 11.f, 12.f, 13.f, 21.f, 22.f, 23.f,
11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f,
13.f, 21.f, 22.f, 23.f},
/*input_type=*/TensorType_FLOAT32,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Uint8Matrix) {
Check<uint8_t>(
/*input_shape=*/{2, 3},
/*input_data=*/{11, 12, 13, 21, 22, 23},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
/*input_type=*/TensorType_UINT8,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Int32Matrix) {
Check<int32_t>(
/*input_shape=*/{2, 3},
/*input_data=*/{11, 12, 13, 21, 22, 23},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
/*input_type=*/TensorType_INT32,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, BooleanMatrix) {
Check<bool>(
/*input_shape=*/{2, 3},
/*input_data=*/{true, false, false, true, true, false},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/
{true, false, false, true, true, false, true, false, false, true, true,
false},
/*input_type=*/TensorType_BOOL,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Int64Matrix) {
Check<int64_t>(
/*input_shape=*/{2, 3},
/*input_data=*/{11, 12, 13, 21, 22, 23},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
/*input_type=*/TensorType_INT64,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, Int64Matrix64Multipliers) {
Check<int64_t, int64_t>(
/*input_shape=*/{2, 3},
/*input_data=*/{11, 12, 13, 21, 22, 23},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
/*input_type=*/TensorType_INT64,
/*multiply_type=*/TensorType_INT64, GetParam());
}
TEST_P(TileTest, StringMatrix) {
Check<std::string>(
/*input_shape=*/{2, 3},
/*input_data=*/{"AA", "AB", "AC", "BA", "BB", "BC"},
/*multipliers_data=*/{1, 2}, /*exp_output_shape=*/{2, 6},
/*exp_output_data=*/
{"AA", "AB", "AC", "AA", "AB", "AC", "BA", "BB", "BC", "BA", "BB", "BC"},
/*input_type=*/TensorType_STRING,
/*multiply_type=*/TensorType_INT32, GetParam());
}
TEST_P(TileTest, StringMatrix64Multipliers) {
Check<std::string, int64_t>(
/*input_shape=*/{2, 3},
/*input_data=*/{"AA", "AB", "AC", "BA", "BB", "BC"},
/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
/*exp_output_data=*/
{"AA", "AB", "AC", "BA", "BB", "BC", "AA", "AB", "AC", "BA", "BB", "BC"},
/*input_type=*/TensorType_STRING,
/*multiply_type=*/TensorType_INT64, GetParam());
}
TEST_P(TileTest, StringMatrix2) {
Check<std::string>(
/*input_shape=*/{3, 2, 1},
/*input_data=*/{"AA", "AB", "AC", "BA", "BB", "BC"},
/*multipliers_data=*/{2, 2, 2}, /*exp_output_shape=*/{6, 4, 2},
/*exp_output_data=*/
{"AA", "AA", "AB", "AB", "AA", "AA", "AB", "AB", "AC", "AC", "BA", "BA",
"AC", "AC", "BA", "BA", "BB", "BB", "BC", "BC", "BB", "BB", "BC", "BC",
"AA", "AA", "AB", "AB", "AA", "AA", "AB", "AB", "AC", "AC", "BA", "BA",
"AC", "AC", "BA", "BA", "BB", "BB", "BC", "BC", "BB", "BB", "BC", "BC"},
/*input_type=*/TensorType_STRING,
/*multiply_type=*/TensorType_INT32, GetParam());
}
INSTANTIATE_TEST_SUITE_P(TileTest, TileTest,
::testing::Values(TestType::kConst,
TestType::kDynamic));
} // namespace
} // namespace tflite