COMPMID-897 Merge batch normalization with bounded relu
Change-Id: I9a607fe620f795cdea1a99fdd3f5f8c2fc76f980
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119234
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/benchmark/CL/BatchNormalizationLayer.cpp b/tests/benchmark/CL/BatchNormalizationLayer.cpp
index 0fc8727..a61e7cc 100644
--- a/tests/benchmark/CL/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/CL/BatchNormalizationLayer.cpp
@@ -29,6 +29,7 @@
#include "tests/CL/CLAccessor.h"
#include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
@@ -47,24 +48,41 @@
TEST_SUITE(CL)
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
TEST_SUITE(NIGHTLY)
+
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", { 4, 8 })));
+
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
TEST_SUITE_END()
diff --git a/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
old mode 100755
new mode 100644
index 4464ea2..e615860
--- a/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -29,6 +29,7 @@
#include "tests/GLES_COMPUTE/GCAccessor.h"
#include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
@@ -47,24 +48,41 @@
TEST_SUITE(GC)
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), framework::dataset::make("ActivationInfo",
+ ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
TEST_SUITE(NIGHTLY)
+
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", { 4, 8 })));
+
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), framework::dataset::make("ActivationInfo",
+ ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
TEST_SUITE_END()
diff --git a/tests/benchmark/NEON/BatchNormalizationLayer.cpp b/tests/benchmark/NEON/BatchNormalizationLayer.cpp
index 3a7f2c6..2aae3a4 100644
--- a/tests/benchmark/NEON/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/NEON/BatchNormalizationLayer.cpp
@@ -33,6 +33,7 @@
#include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
namespace arm_compute
@@ -52,21 +53,39 @@
TEST_SUITE(NEON)
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), data_types),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+ data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(), data_types),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+ data_types),
framework::dataset::make("Batches", 1)));
TEST_SUITE(NIGHTLY)
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+ data_types),
+ framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), data_types),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+ data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(), data_types),
+ framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+ data_types),
framework::dataset::make("Batches", { 4, 8 })));
TEST_SUITE_END()
TEST_SUITE_END()
diff --git a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
index 38a3263..a031ec6 100644
--- a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
@@ -40,7 +40,7 @@
{
public:
template <typename...>
- void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, DataType data_type, int batches)
+ void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, ActivationLayerInfo act_info, DataType data_type, int batches)
{
// Set batched in source and destination shapes
const unsigned int fixed_point_position = 4;
@@ -55,7 +55,7 @@
gamma = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
// Create and configure function
- batch_norm_layer.configure(&src, &dst, &mean, &variance, &beta, &gamma, epsilon);
+ batch_norm_layer.configure(&src, &dst, &mean, &variance, &beta, &gamma, epsilon, act_info);
// Allocate tensors
src.allocator()->allocate();
diff --git a/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h b/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h
new file mode 100644
index 0000000..d09ff02
--- /dev/null
+++ b/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h
@@ -0,0 +1,68 @@
+/*
+ * Copyright (c) 2017-2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * 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.
+ */
+#ifndef ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET
+#define ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET
+
+#include "tests/datasets/BatchNormalizationLayerDataset.h"
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace datasets
+{
+class MobileNetBatchNormalizationLayerDataset final : public BatchNormalizationLayerDataset
+{
+public:
+ MobileNetBatchNormalizationLayerDataset()
+ {
+ // conv1_bn, dwc0_bn
+ add_config(TensorShape(112U, 112U, 32U), TensorShape(32U), 0.001f);
+ // pwc0_bn
+ add_config(TensorShape(112U, 112U, 64U), TensorShape(64U), 0.001f);
+ // dwc1_bn
+ add_config(TensorShape(56U, 56U, 64U), TensorShape(64U), 0.001f);
+ // dwc2_bn, pwc1_bn, pwc2_bn
+ add_config(TensorShape(56U, 56U, 128U), TensorShape(128U), 0.001f);
+ // dwc3_bn
+ add_config(TensorShape(28U, 28U, 128U), TensorShape(128U), 0.001f);
+ // dwc4_bn, pwc3_bn, pwc4_bn
+ add_config(TensorShape(28U, 28U, 256U), TensorShape(256U), 0.001f);
+ // dwc5_bn
+ add_config(TensorShape(14U, 14U, 256U), TensorShape(256U), 0.001f);
+ // dwc6_bn, dwc7_bn, dwc8_bn, dwc9_bn, dwc10_bn, pwc5_bn, pwc6_bn, pwc7_bn, pwc8_bn, pwc9_bn, pwc10_bn
+ add_config(TensorShape(14U, 14U, 512U), TensorShape(512U), 0.001f);
+ // dwc11_bn
+ add_config(TensorShape(7U, 7U, 512U), TensorShape(512U), 0.001f);
+ // dwc12_bn, pwc11_bn, pwc12_bn
+ add_config(TensorShape(7U, 7U, 1024U), TensorShape(1024U), 0.001f);
+ }
+};
+} // namespace datasets
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET */
diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp
index 30dd70a..ef53515 100644
--- a/tests/validation/CL/BatchNormalizationLayer.cpp
+++ b/tests/validation/CL/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,6 +47,12 @@
constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto act_infos = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
} // namespace
TEST_SUITE(CL)
@@ -80,13 +86,16 @@
// *INDENT-OFF*
// clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Unsupported fused activation
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
}),
@@ -96,6 +105,9 @@
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
TensorInfo(),
})),
@@ -106,16 +118,31 @@
TensorInfo(TensorShape(5U), 1, DataType::F32),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+ TensorInfo(TensorShape(2U), 1, DataType::F32),
+ TensorInfo(TensorShape(2U), 1, DataType::F32),
+ TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
})),
- framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
- input_info, output_info, mvbg_info, expected)
+ framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ })),
+ framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, false, true, true})),
+ input_info, output_info, mvbg_info, act_info, expected)
{
const auto &mean_info = mvbg_info;
const auto &var_info = mvbg_info;
const auto &beta_info = mvbg_info;
const auto &gamma_info = mvbg_info;
- bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+ bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
}
// clang-format on
@@ -123,7 +150,8 @@
TEST_SUITE(Float)
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ act_infos),
framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
@@ -132,7 +160,8 @@
TEST_SUITE_END()
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
framework::dataset::make("DataType", DataType::F16)))
{
// Validate output
@@ -146,7 +175,8 @@
using CLBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLBatchNormalizationLayer, T>;
TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", DataType::QS8)),
framework::dataset::make("FractionalBits", 1, 6)))
{
@@ -156,7 +186,8 @@
TEST_SUITE_END()
TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", DataType::QS16)),
framework::dataset::make("FractionalBits", 1, 14)))
{
diff --git a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
index a82149b..d817fc0 100644
--- a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -45,6 +45,12 @@
{
constexpr AbsoluteTolerance<float> tolerance_f(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+const auto act_infos = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
} // namespace
TEST_SUITE(GC)
@@ -78,7 +84,8 @@
TEST_SUITE(Float)
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ act_infos),
framework::dataset::make("DataType", DataType::F16)))
{
// Validate output
@@ -87,7 +94,8 @@
TEST_SUITE_END()
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ act_infos),
framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp
index dfa32bb..3501c35 100644
--- a/tests/validation/NEON/BatchNormalizationLayer.cpp
+++ b/tests/validation/NEON/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -49,6 +49,12 @@
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto act_infos = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
} // namespace
TEST_SUITE(NEON)
@@ -82,13 +88,15 @@
// *INDENT-OFF*
// clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
}),
@@ -98,6 +106,8 @@
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
TensorInfo(),
})),
@@ -108,10 +118,23 @@
TensorInfo(TensorShape(5U), 1, DataType::F32),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+ TensorInfo(TensorShape(2U), 1, DataType::F32),
+ TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
})),
- framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
- input_info, output_info, mvbg_info, expected)
+ framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ })),
+ framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, true, true})),
+ input_info, output_info, mvbg_info, act_info, expected)
{
const auto &mean_info = mvbg_info;
const auto &var_info = mvbg_info;
@@ -120,14 +143,15 @@
bool has_error = bool(NEBatchNormalizationLayer::validate(
&input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr,
&mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false),
- &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+ &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
TEST_SUITE(Float)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ act_infos),
framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
@@ -137,7 +161,8 @@
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(Float16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ act_infos),
framework::dataset::make("DataType", DataType::F16)))
{
// Validate output
@@ -151,7 +176,8 @@
using NEBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", DataType::QS8)),
framework::dataset::make("FractionalBits", 1, 6)))
{
@@ -161,7 +187,8 @@
TEST_SUITE_END()
TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", DataType::QS16)),
framework::dataset::make("FractionalBits", 1, 14)))
{
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
index 298c9ca..e02c619 100644
--- a/tests/validation/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -45,12 +45,12 @@
{
public:
template <typename...>
- void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt, int fractional_bits)
+ void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fractional_bits)
{
_fractional_bits = fractional_bits;
_data_type = dt;
- _target = compute_target(shape0, shape1, epsilon, dt, fractional_bits);
- _reference = compute_reference(shape0, shape1, epsilon, dt, fractional_bits);
+ _target = compute_target(shape0, shape1, epsilon, act_info, dt, fractional_bits);
+ _reference = compute_reference(shape0, shape1, epsilon, act_info, dt, fractional_bits);
}
protected:
@@ -85,7 +85,7 @@
}
}
- TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+ TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
{
// Create tensors
TensorType src = create_tensor<TensorType>(shape0, dt, 1, fixed_point_position);
@@ -97,7 +97,7 @@
// Create and configure function
FunctionType norm;
- norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon);
+ norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon, act_info);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -130,7 +130,7 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+ SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
{
// Create reference
SimpleTensor<T> ref_src{ shape0, dt, 1, fixed_point_position };
@@ -142,7 +142,7 @@
// Fill reference
fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma);
- return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position);
+ return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info, fixed_point_position);
}
TensorType _target{};
@@ -156,9 +156,9 @@
{
public:
template <typename...>
- void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt)
+ void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt)
{
- BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, dt, 0);
+ BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, act_info, dt, 0);
}
};
} // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.cpp b/tests/validation/reference/BatchNormalizationLayer.cpp
index e4446d1..a9d9f03 100644
--- a/tests/validation/reference/BatchNormalizationLayer.cpp
+++ b/tests/validation/reference/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,6 +23,8 @@
*/
#include "BatchNormalizationLayer.h"
+#include "ActivationLayer.h"
+
#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
@@ -37,8 +39,9 @@
// Batch Normalization Layer for fixed point type
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type *>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- int fixed_point_position)
+ ActivationLayerInfo act_info, int fixed_point_position)
{
+ ARM_COMPUTE_UNUSED(act_info);
SimpleTensor<T> result(src.shape(), src.data_type());
const auto cols = static_cast<int>(src.shape()[0]);
@@ -79,7 +82,7 @@
// Batch Normalization Layer for floating point type
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- int fixed_point_position)
+ ActivationLayerInfo act_info, int fixed_point_position)
{
ARM_COMPUTE_UNUSED(fixed_point_position);
@@ -103,21 +106,28 @@
const float numerator = src[pos] - mean[i];
const float x_bar = numerator / denominator;
result[pos] = beta[i] + x_bar * gamma[i];
+ ;
}
}
}
}
+
+ if(act_info.enabled())
+ {
+ result = activation_layer(result, act_info);
+ }
+
return result;
}
template SimpleTensor<float> batch_normalization_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &var, const SimpleTensor<float> &beta,
- const SimpleTensor<float> &gamma, float epsilon, int fixed_point_position);
+ const SimpleTensor<float> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
template SimpleTensor<int8_t> batch_normalization_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &mean, const SimpleTensor<int8_t> &var, const SimpleTensor<int8_t> &beta,
- const SimpleTensor<int8_t> &gamma, float epsilon, int fixed_point_position);
+ const SimpleTensor<int8_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
template SimpleTensor<int16_t> batch_normalization_layer(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &mean, const SimpleTensor<int16_t> &var, const SimpleTensor<int16_t> &beta,
- const SimpleTensor<int16_t> &gamma, float epsilon, int fixed_point_position);
+ const SimpleTensor<int16_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
template SimpleTensor<half> batch_normalization_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &var,
const SimpleTensor<half> &beta,
- const SimpleTensor<half> &gamma, float epsilon, int fixed_point_position);
+ const SimpleTensor<half> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
} // namespace reference
} // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.h b/tests/validation/reference/BatchNormalizationLayer.h
index 1a554ad..329909d 100644
--- a/tests/validation/reference/BatchNormalizationLayer.h
+++ b/tests/validation/reference/BatchNormalizationLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -37,11 +37,13 @@
{
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- int fixed_point_position);
+ ActivationLayerInfo act_info,
+ int fixed_point_position);
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- int fixed_point_position);
+ ActivationLayerInfo act_info,
+ int fixed_point_position);
} // namespace reference
} // namespace validation
} // namespace test