COMPMID-3293: Test Improvements for CLCol2ImKernel
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I086734a0c6d66cb782efb39ebd3e14a2809b3685
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3004
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/Col2Im.cpp b/tests/validation/CL/Col2Im.cpp
index 1fea5c1..aea21fb 100644
--- a/tests/validation/CL/Col2Im.cpp
+++ b/tests/validation/CL/Col2Im.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,10 +23,9 @@
*/
#include "arm_compute/core/CL/kernels/CLCol2ImKernel.h"
#include "arm_compute/core/Types.h"
-#include "tests/CL/Helper.h"
#include "tests/CL/CLAccessor.h"
-#include "tests/datasets/Col2ImLayerDataset.h"
+#include "tests/CL/Helper.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
@@ -44,83 +43,130 @@
using CLCol2Im = CLSynthetizeFunction<CLCol2ImKernel>;
-// *INDENT-OFF*
-// clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::S64), // Unsupported data type
- TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32), // Mismatching data type
- TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32), // Invalid output shape
- TensorInfo(TensorShape(3U, 12U, 4U, 2U), 1, DataType::F32),
- }),
- framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(3U, 4U, 10U, 2U), 1, DataType::F16),
- TensorInfo(TensorShape(3U, 4U, 10U, 2U), 1, DataType::F16),
- TensorInfo(TensorShape(3U, 3U, 10U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 4U, 12U, 2U), 1, DataType::F32),
- })),
- framework::dataset::make("ConvolvedWidth", { 3, 3, 3, 3 })),
- framework::dataset::make("ConvolvedHeight", { 4, 4, 4, 4 })),
- framework::dataset::make("NumGroups", { 1, 1, 1, 4 })),
- framework::dataset::make("Expected", { false, false, false, true })),
- input_info, output_info, convolved_width, convolved_height, num_groups, expected)
+/** Negative tests
+ *
+ * A series of validation tests on configurations which according to the API specification
+ * the function should fail against.
+ *
+ * Checks performed in order:
+ * - Pass unsupported data type for input
+ * - Pass NHWC as output data layout
+ * - Pass an invalid output shape
+ */
+TEST_CASE(Negative, framework::DatasetMode::PRECOMMIT)
{
- bool status = bool(CLCol2Im::validate(&input_info, &output_info, Size2D(convolved_width, convolved_height), num_groups));
- ARM_COMPUTE_EXPECT(status == expected, framework::LogLevel::ERRORS);
+ // Unsupported data type
+ {
+ const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::SIZET);
+ const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32);
+ const auto conv_size = Size2D(3, 4);
+ const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
+ ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+ }
+
+ // NHWC as output data layout
+ {
+ const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
+ const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32, DataLayout::NHWC);
+ const auto conv_size = Size2D(3, 4);
+ const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
+ ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+ }
+
+ // Invalid output size
+ {
+ const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
+ const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 2U, 2U), 1, DataType::F32);
+ const auto conv_size = Size2D(3, 4);
+ const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
+ ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+ }
}
-// clang-format on
-// *INDENT-ON*
template <typename T>
using CLCol2ImFixture = Col2ImValidationFixture<CLTensor, CLAccessor, CLCol2Im, T, true>;
-TEST_SUITE(Float)
-TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLCol2ImFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallGroupedCol2ImLayerDataset(), framework::dataset::make("DataType", DataType::F32)))
+/** Test kernel for single-precision floating point
+ *
+ * @note 8 elements processed per iteration
+ *
+ * Three main tests will be run:
+ * - Channels are multiple of elements processed
+ * - Channels larger and non multiple of elements used
+ * - Channels smaller and not multiple of elements used
+ *
+ * The above will be repeated with a different group size
+ *
+ * Kernel tested col2im
+ */
+FIXTURE_DATA_TEST_CASE(FP32,
+ CLCol2ImFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(
+ framework::dataset::make("InputShape", { TensorShape(8U, 16U, 3U, 1U), TensorShape(17U, 16U, 3U, 1U), TensorShape(7U, 16U, 3U, 1U) }),
+ framework::dataset::make("ConvolvedWidth", 4)),
+ framework::dataset::make("ConvolvedHeight", 4)),
+ framework::dataset::make("Groups", { 1, 3 })),
+ framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLCol2ImFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGroupedCol2ImLayerDataset(), framework::dataset::make("DataType", DataType::F32)))
-{
- // Validate output
- validate(CLAccessor(_target), _reference);
-}
-TEST_SUITE_END()
-
-TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLCol2ImFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallGroupedCol2ImLayerDataset(), framework::dataset::make("DataType", DataType::F16)))
+/** Test kernel for half-precision floating point
+ *
+ * @note 8 elements processed per iteration
+ *
+ * One main tests will be run:
+ * - Channels larger and non multiple of elements used
+ *
+ * We just need to test the difference in the data type size.
+ * Any other issues can be identified by the main FP32 tests
+ *
+ * Kernel tested col2im
+ */
+FIXTURE_DATA_TEST_CASE(F16,
+ CLCol2ImFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(
+ framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
+ framework::dataset::make("ConvolvedWidth", 4)),
+ framework::dataset::make("ConvolvedHeight", 4)),
+ framework::dataset::make("Groups", 3)),
+ framework::dataset::make("DataType", DataType::F16)))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLCol2ImFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGroupedCol2ImLayerDataset(), framework::dataset::make("DataType", DataType::F16)))
-{
- // Validate output
- validate(CLAccessor(_target), _reference);
-}
-TEST_SUITE_END()
-
-TEST_SUITE_END()
-
-TEST_SUITE(QASYMM8)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLCol2ImFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallGroupedCol2ImLayerDataset(), framework::dataset::make("DataType",
- DataType::QASYMM8)))
+/** Test kernel for unsigned asymmetric quantized type
+ *
+ * @note 8 elements processed per iteration
+ *
+ * One main tests will be run:
+ * - Channels larger and non multiple of elements used
+ *
+ * We just need to test the difference in the data type size.
+ * Any other issues can be identified by the main FP32 tests
+ *
+ * Kernel tested col2im
+ */
+FIXTURE_DATA_TEST_CASE(QASYMM8,
+ CLCol2ImFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(
+ framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
+ framework::dataset::make("ConvolvedWidth", 4)),
+ framework::dataset::make("ConvolvedHeight", 4)),
+ framework::dataset::make("Groups", 3)),
+ framework::dataset::make("DataType", DataType::QASYMM8)))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLCol2ImFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGroupedCol2ImLayerDataset(), framework::dataset::make("DataType",
- DataType::QASYMM8)))
-{
- // Validate output
- validate(CLAccessor(_target), _reference);
-}
-TEST_SUITE_END()
-
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // CL
+TEST_SUITE_END() // Col2Im
} // namespace validation
} // namespace test
} // namespace arm_compute