From 1167487ea8e54a76d0a3625e0aa84e2ad9ffd317 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Wed, 7 Feb 2018 15:38:12 +0000 Subject: COMPMID-897 Merge batch normalization with bounded relu Change-Id: I9a607fe620f795cdea1a99fdd3f5f8c2fc76f980 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119234 Tested-by: Jenkins Reviewed-by: Gian Marco Iodice Reviewed-by: Georgios Pinitas --- tests/validation/CL/BatchNormalizationLayer.cpp | 49 ++++++++++++++++++++----- 1 file changed, 40 insertions(+), 9 deletions(-) (limited to 'tests/validation/CL') diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp index 30dd70a66a..ef535153f2 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 tolerance_f32(0.00001f); /**< Tolerance value constexpr AbsoluteTolerance tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ constexpr AbsoluteTolerance tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */ constexpr AbsoluteTolerance 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 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran // *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 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( 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 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( 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("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, true, true})), - input_info, output_info, mvbg_info, expected) + 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 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( TEST_SUITE(Float) TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), + act_infos), framework::dataset::make("DataType", DataType::F32))) { // Validate output @@ -132,7 +160,8 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, framewor TEST_SUITE_END() TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, 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 @@ template using CLBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture; TEST_SUITE(QS8) -FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, 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 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, 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))) { -- cgit v1.2.1