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-rw-r--r--tests/validation/CL/ConvolutionLayer.cpp2
-rw-r--r--tests/validation/CL/FFT.cpp119
-rw-r--r--tests/validation/CL/ReductionOperation.cpp2
3 files changed, 113 insertions, 10 deletions
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 41d2b7bb5e..f1f9b59330 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -46,7 +46,7 @@ namespace validation
namespace
{
constexpr AbsoluteTolerance<float> absolute_tolerance_float(0.0001f); /**< Absolute Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-RelativeTolerance<float> tolerance_f32(0.05f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+RelativeTolerance<float> tolerance_f32(0.1f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
constexpr AbsoluteTolerance<float> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
constexpr float tolerance_num = 0.07f; /**< Tolerance number */
diff --git a/tests/validation/CL/FFT.cpp b/tests/validation/CL/FFT.cpp
index 0d29532c29..9fdd85b604 100644
--- a/tests/validation/CL/FFT.cpp
+++ b/tests/validation/CL/FFT.cpp
@@ -24,7 +24,10 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/functions/CLFFT1D.h"
+#include "arm_compute/runtime/CL/functions/CLFFT2D.h"
+#include "arm_compute/runtime/CL/functions/CLFFTConvolutionLayer.h"
#include "tests/CL/CLAccessor.h"
+#include "tests/datasets/SmallConvolutionLayerDataset.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
@@ -40,7 +43,7 @@ namespace validation
namespace
{
const auto data_types = framework::dataset::make("DataType", { DataType::F32 });
-const auto shapes = framework::dataset::make("TensorShape", { TensorShape(2U, 2U, 3U), TensorShape(3U, 2U, 3U),
+const auto shapes_1d = framework::dataset::make("TensorShape", { TensorShape(2U, 2U, 3U), TensorShape(3U, 2U, 3U),
TensorShape(4U, 2U, 3U), TensorShape(5U, 2U, 3U),
TensorShape(7U, 2U, 3U), TensorShape(8U, 2U, 3U),
TensorShape(9U, 2U, 3U), TensorShape(25U, 2U, 3U),
@@ -48,11 +51,27 @@ const auto shapes = framework::dataset::make("TensorShape", { TensorShape(2U
TensorShape(16U, 2U, 3U), TensorShape(32U, 2U, 3U),
TensorShape(96U, 2U, 2U)
});
+const auto shapes_2d = framework::dataset::make("TensorShape", { TensorShape(2U, 2U, 3U), TensorShape(3U, 6U, 3U),
+ TensorShape(4U, 5U, 3U), TensorShape(5U, 7U, 3U),
+ TensorShape(7U, 25U, 3U), TensorShape(8U, 2U, 3U),
+ TensorShape(9U, 16U, 3U), TensorShape(25U, 32U, 3U),
+ TensorShape(192U, 128U, 2U)
+ });
+
+const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f)
+});
+
+RelativeTolerance<float> tolerance_f32(0.1f); /**< Relative tolerance value for FP32 */
+constexpr float tolerance_num = 0.07f; /**< Tolerance number */
+
} // namespace
TEST_SUITE(CL)
TEST_SUITE(FFT1D)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(shapes, data_types),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(shapes_1d, data_types),
shape, data_type)
{
// Create tensors
@@ -81,19 +100,19 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(shapes, data_
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32), // Mismatching shapes
- TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid channels
+ TensorInfo(TensorShape(32U, 13U, 2U), 3, DataType::F32), // Invalid channels
TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32), // Unsupported axis
TensorInfo(TensorShape(11U, 13U, 2U), 2, DataType::F32), // Undecomposable FFT
TensorInfo(TensorShape(25U, 13U, 2U), 2, DataType::F32),
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F16),
TensorInfo(TensorShape(16U, 13U, 2U), 2, DataType::F32),
- TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32),
TensorInfo(TensorShape(11U, 13U, 2U), 2, DataType::F32),
TensorInfo(TensorShape(25U, 13U, 2U), 2, DataType::F32),
})),
- framework::dataset::make("Axis", { 0, 0, 0, 1, 0, 0 })),
+ framework::dataset::make("Axis", { 0, 0, 0, 2, 0, 0 })),
framework::dataset::make("Expected", { false, false, false, false, false, true })),
input_info, output_info, axis, expected)
{
@@ -106,19 +125,103 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
// *INDENT-ON*
template <typename T>
-using CLFFT1DFixture = FFTValidationFixture<CLTensor, CLAccessor, CLFFT1D, T>;
+using CLFFT1DFixture = FFTValidationFixture<CLTensor, CLAccessor, CLFFT1D, FFT1DInfo, T>;
TEST_SUITE(Float)
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLFFT1DFixture<float>, framework::DatasetMode::ALL, combine(shapes, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLFFT1DFixture<float>, framework::DatasetMode::ALL, combine(shapes_1d, framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
- validate(CLAccessor(_target), _reference, RelativeTolerance<float>(0.1f), 0.05f);
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
}
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
TEST_SUITE_END() // FFT1D
+
+TEST_SUITE(FFT2D)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(shapes_2d, data_types),
+ shape, data_type)
+{
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(shape, data_type, 2);
+ CLTensor dst = create_tensor<CLTensor>(shape, data_type, 2);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ CLFFT2D fft2d;
+ fft2d.configure(&src, &dst, FFT2DInfo());
+
+ // Validate valid region
+ const ValidRegion valid_region = shape_to_valid_region(shape);
+ validate(src.info()->valid_region(), valid_region);
+ validate(dst.info()->valid_region(), valid_region);
+
+ // Validate padding
+ validate(src.info()->padding(), PaddingSize());
+ validate(dst.info()->padding(), PaddingSize());
+}
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32), // Mismatching data types
+ TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32), // Mismatching shapes
+ TensorInfo(TensorShape(32U, 25U, 2U), 3, DataType::F32), // Invalid channels
+ TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32), // Undecomposable FFT
+ TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32),
+ }),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F16),
+ TensorInfo(TensorShape(16U, 25U, 2U), 2, DataType::F32),
+ TensorInfo(TensorShape(32U, 25U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32),
+ TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32),
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, true })),
+ input_info, output_info, expected)
+{
+ const Status s = CLFFT2D::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), FFT2DInfo());
+ ARM_COMPUTE_EXPECT(bool(s) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using CLFFT2DFixture = FFTValidationFixture<CLTensor, CLAccessor, CLFFT2D, FFT2DInfo, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLFFT2DFixture<float>, framework::DatasetMode::ALL, combine(shapes_2d, framework::dataset::make("DataType", DataType::F32)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // FFT2D
+
+TEST_SUITE(FFTConvolutionLayer)
+
+template <typename T>
+using CLFFTConvolutionLayerFixture = FFTConvolutionValidationFixture<CLTensor, CLAccessor, CLFFTConvolutionLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLFFTConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFFTConvolutionLayerDataset(),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ ActivationFunctionsSmallDataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // FFTConvolutionLayer
+
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
diff --git a/tests/validation/CL/ReductionOperation.cpp b/tests/validation/CL/ReductionOperation.cpp
index c8474e97e6..79308c8229 100644
--- a/tests/validation/CL/ReductionOperation.cpp
+++ b/tests/validation/CL/ReductionOperation.cpp
@@ -63,7 +63,7 @@ TEST_SUITE(ReductionOperation)
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching data type input/output
- TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
+ TensorInfo(TensorShape(128U, 64U), 3, DataType::F32), // Number of Input channels != 1
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != QASYMM8/F16/F32
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
TensorInfo(TensorShape(128U, 64U), 1, DataType::QASYMM8), // Axis == 0 and SUM_SQUARE and QASYMM8
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-23 22:09:14 +0000