Fix OpenCL direct convolution
- The ARM DOT macro was using wrong variables for performing the dot
product
- K0 could be a non power of 2 values when IFM was not a multiple of 16
- Refactor the test for direct convolution NHWC
Resolves COMPMID-4135, COMPMID-4155
Change-Id: I3a2dc89ef613ae20245cfc28e76ea36c55eaf81d
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4962
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: TeresaARM <teresa.charlinreyes@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index ae2f22d..3a6cacc 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -161,14 +161,178 @@
bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
-// clang-format on
-// *INDENT-ON*
template <typename T>
using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
template <typename T>
using CLDirectConvolutionValidationWithTensorShapesFixture = DirectConvolutionValidationWithTensorShapesFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
+template <typename T>
+using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
+template <typename T>
+using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
+TEST_SUITE(NHWC)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
+ TensorShape(9U, 5U, 6U, 4U),
+ TensorShape(3U, 5U, 7U, 2U),
+ TensorShape(32U, 37U, 3U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::IDENTITY) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num);
+}
+
+TEST_SUITE_END() // FP16
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
+ TensorShape(9U, 5U, 6U, 4U),
+ TensorShape(3U, 5U, 7U, 2U),
+ TensorShape(32U, 37U, 3U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_fp32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::IDENTITY) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_fp32);
+}
+
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
+ TensorShape(9U, 5U, 6U, 4U),
+ TensorShape(3U, 5U, 7U, 2U),
+ TensorShape(32U, 37U, 3U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(1.1f / 255, 10))),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+
+TEST_SUITE_END() // QASYMM8
+//
+TEST_SUITE(QASYMM8_SIGNED)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
+ TensorShape(9U, 5U, 6U, 4U),
+ TensorShape(3U, 5U, 7U, 2U),
+ TensorShape(32U, 37U, 3U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END() // QASYMM8_SIGNED
+TEST_SUITE_END() // Quantized
+TEST_SUITE_END() // NHWC
+
+// clang-format on
+// *INDENT-ON*
+TEST_SUITE(NCHW)
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", DataType::F16)),
@@ -185,59 +349,22 @@
// Validate output
validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num);
}
-FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType",
- DataType::F16)),
- ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NHWC })))
-{
- validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num);
-}
-FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType",
- DataType::F16)),
- ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NHWC })))
-{
- validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num);
-}
TEST_SUITE_END() // FP16
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType",
DataType::F32)),
ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
validate(CLAccessor(_target), _reference, tolerance_fp32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", DataType::F32)),
ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
validate(CLAccessor(_target), _reference, tolerance_fp32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType",
- DataType::F32)),
- ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NHWC })))
-{
- validate(CLAccessor(_target), _reference, tolerance_fp32);
-}
-FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType",
- DataType::F32)),
- ActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NHWC })))
-{
- validate(CLAccessor(_target), _reference, tolerance_fp32);
-}
-
-FIXTURE_DATA_TEST_CASE(RunLargeUsecase, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_usecase, framework::dataset::make("DataType",
- DataType::F32)),
- framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })),
- framework::dataset::make("DataLayout", { DataLayout::NHWC })))
-{
- // Validate output
- validate(CLAccessor(_target), _reference, tolerance_fp32, 0.f, tolerance_fp32_abs);
-}
TEST_SUITE_END() // FP32
TEST_SUITE(FP32_CustomDataset)
@@ -251,11 +378,6 @@
TEST_SUITE_END() // FP32_CustomDataset
TEST_SUITE_END() // Float
-template <typename T>
-using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
-template <typename T>
-using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
-
const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
{
ActivationLayerInfo(),
@@ -269,7 +391,7 @@
DataType::QASYMM8)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })),
QuantizedActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -279,7 +401,7 @@
DataType::QASYMM8)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(3.f / 255, 10), QuantizationInfo(1.1f, 10) })),
QuantizedActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -288,7 +410,7 @@
DataType::QASYMM8)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })),
QuantizedActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -312,7 +434,7 @@
framework::dataset::make("DataType", DataType::QASYMM8)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127), QuantizationInfo(1.1f, 10) })),
QuantizedActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -347,18 +469,18 @@
framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127), QuantizationInfo(1.1f, 10) })),
QuantizedActivationFunctionsDataset),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
TEST_SUITE_END() // QASYMM8_SIGNED
-
TEST_SUITE_END() // Quantized
-
+TEST_SUITE_END() // NCHW
TEST_SUITE_END() // DirectConvolutionLayer
-TEST_SUITE_END() // Float
+TEST_SUITE_END() // CL
+
} // namespace validation
} // namespace test
} // namespace arm_compute