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/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)))
{