STT-tensorflow/tensorflow/lite/delegates/xnnpack/mean_test.cc
Marat Dukhan ffc7592c82 Support Global Average Pooling in XNNPACK delegate
- MEAN over spatial dimensions is converted as a Global Average Pooling

PiperOrigin-RevId: 316031672
Change-Id: Icbecf2ccf2920c701ee2f6b04b6dcf9972b9ce0b
2020-06-11 20:25:14 -07:00

266 lines
9.0 KiB
C++

/* Copyright 2020 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 <cstdint>
#include <functional>
#include <memory>
#include <random>
#include <gtest/gtest.h>
#include "tensorflow/lite/delegates/xnnpack/reduce_tester.h"
#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
namespace tflite {
namespace xnnpack {
TEST(Mean, DISABLED_4DReduceBatch) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({0})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_4DReduceHeight) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({1})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_4DReduceWidth) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({2})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, 4DReduceHeightWidth) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({1, 2})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({2, 1})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_4DReduceChannels) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({3})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_3DReduceBatch) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, width, channels})
.Axes({0})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_3DReduceWidth) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, width, channels})
.Axes({1})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_3DReduceChannels) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, width, channels})
.Axes({2})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_2DReduceBatch) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, channels})
.Axes({0})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_2DReduceChannels) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, channels})
.Axes({1})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
TEST(Mean, DISABLED_1D) {
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(nullptr),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
ReduceTester().InputShape({batch}).Axes({0}).Test(BuiltinOperator_MEAN,
xnnpack_delegate.get());
}
TEST(Mean, MultiThreading) {
TfLiteXNNPackDelegateOptions delegate_options =
TfLiteXNNPackDelegateOptionsDefault();
delegate_options.num_threads = 2;
std::unique_ptr<TfLiteDelegate, decltype(&TfLiteXNNPackDelegateDelete)>
xnnpack_delegate(TfLiteXNNPackDelegateCreate(&delegate_options),
TfLiteXNNPackDelegateDelete);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto shape_rng =
std::bind(std::uniform_int_distribution<int32_t>(2, 5), std::ref(rng));
const auto batch = shape_rng();
const auto height = shape_rng();
const auto width = shape_rng();
const auto channels = shape_rng();
ReduceTester()
.InputShape({batch, height, width, channels})
.Axes({1, 2})
.Test(BuiltinOperator_MEAN, xnnpack_delegate.get());
}
} // namespace xnnpack
} // namespace tflite