- Add PreluTester class and unit test for XNNPACK-delegated Prelu operator - Relax restrictions on the number of input/output dimensions in delegated Prelu operators PiperOrigin-RevId: 317933686 Change-Id: Ie7bac6c8d6bd358ef8b5d79042d6ae1af07e1c49
584 lines
19 KiB
C++
584 lines
19 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/prelu_tester.h"
|
|
#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
|
|
|
|
namespace tflite {
|
|
namespace xnnpack {
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy4D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({batch, height, width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 4DBy4DBroadcastChannels) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({1, 1, 1, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy4DBroadcastWidth) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({1, 1, width, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy4DBroadcastHeight) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({1, height, 1, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy4DBroadcastBatch) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({batch, 1, 1, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy4DBroadcastHeightWidthChannels) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({1, height, width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy3D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({height, width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy2D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 4DBy1D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_4DBy0D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy3D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({batch, width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 3DBy3DBroadcastChannels) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({1, 1, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy3DBroadcastWidth) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({1, width, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy3DBroadcastBatch) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({batch, 1, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy3DBroadcastWidthChannels) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({1, width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy2D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({width, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 3DBy1D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_3DBy0D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, width, channels})
|
|
.SlopeShape({})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_2DBy2D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, channels})
|
|
.SlopeShape({batch, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 2DBy2DBroadcastChannels) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, channels})
|
|
.SlopeShape({1, channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_2DBy2DBroadcastBatch) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, channels})
|
|
.SlopeShape({batch, 1})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 2DBy1D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, channels})
|
|
.SlopeShape({channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_2DBy0D) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, channels})
|
|
.SlopeShape({})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 1DBy1D) {
|
|
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();
|
|
|
|
PreluTester().InputShape({batch}).SlopeShape({batch}).Test(
|
|
xnnpack_delegate.get());
|
|
}
|
|
|
|
// TODO(b/159727692)
|
|
TEST(Prelu, DISABLED_1DBy0D) {
|
|
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();
|
|
|
|
PreluTester().InputShape({batch}).SlopeShape({}).Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, FP16Weights) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({channels})
|
|
.FP16Weights()
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, SparseWeights) {
|
|
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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({channels})
|
|
.SparseWeights()
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
TEST(Prelu, 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();
|
|
|
|
PreluTester()
|
|
.InputShape({batch, height, width, channels})
|
|
.SlopeShape({channels})
|
|
.Test(xnnpack_delegate.get());
|
|
}
|
|
|
|
} // namespace xnnpack
|
|
} // namespace tflite
|