arm_compute v18.08
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index ec729b3..2cb704f 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -48,7 +48,6 @@
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<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_fixed(1.0f); /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
constexpr float tolerance_num = 0.07f; /**< Tolerance number */
@@ -57,10 +56,16 @@
{
DataType::F16,
DataType::F32,
- DataType::QS8,
- DataType::QS16,
DataType::QASYMM8,
});
+
+/** Grouped CNN data types */
+const auto GroupedCNNDataTypes = framework::dataset::make("DataType",
+{
+ DataType::F16,
+ DataType::F32
+});
+
const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
{
ActivationLayerInfo(),
@@ -74,32 +79,32 @@
TEST_SUITE(ConvolutionLayer)
DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0)
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32),
+ TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32)
}),
- framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 31U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0),
- TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0)
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 31U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16),
+ TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32)
})),
- framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0)
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32)
})),
framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1),
PadStrideInfo(1, 2, 1, 1),
@@ -156,16 +161,13 @@
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -207,7 +209,7 @@
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F16)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
ActivationFunctionsDataset))
{
// Validate output
@@ -218,13 +220,13 @@
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F16)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // FP16
TEST_SUITE(FP32)
@@ -232,7 +234,7 @@
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F32)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
ActivationFunctionsDataset))
{
// Validate output
@@ -243,69 +245,14 @@
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F32)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, absolute_tolerance_float);
}
-TEST_SUITE_END()
-TEST_SUITE_END()
-
-template <typename T>
-using CLGEMMConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
-
-TEST_SUITE(FixedPoint)
-TEST_SUITE(QS8)
-// We test for fixed point precision [4,6]
-FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::QS8)),
- framework::dataset::make("FractionalBits", 4, 7)),
- ActivationFunctionsDataset))
-{
- // Validate output
- validate(CLAccessor(_target), _reference, tolerance_fixed);
-}
-
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::QS8)),
- framework::dataset::make("FractionalBits", 4, 7)),
- ActivationFunctionsDataset))
-{
- // Validate output
- validate(CLAccessor(_target), _reference, tolerance_fixed);
-}
-TEST_SUITE_END()
-
-TEST_SUITE(QS16)
-// Testing for fixed point position [1,14)
-FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::QS16)),
- framework::dataset::make("FractionalBits", 1, 14)),
- ActivationFunctionsDataset))
-{
- // Validate output
- validate(CLAccessor(_target), _reference, tolerance_fixed);
-}
-
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::QS16)),
- framework::dataset::make("FractionalBits", 1, 14)),
- ActivationFunctionsDataset))
-{
- // Validate output
- validate(CLAccessor(_target), _reference, tolerance_fixed);
-}
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
template <typename T>
using CLGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
@@ -320,29 +267,125 @@
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
QuantizedActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })),
QuantizedActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // QASYMM8
+TEST_SUITE_END() // Quantized
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // GEMMConvolutionLayer
+
+template <typename T>
+using CLGEMMGroupedConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
+
+TEST_SUITE(GroupedGEMMConvolutionLayer)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ GroupedCNNDataTypes),
+ ActivationFunctionsDataset),
+ input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
+{
+ ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
+
+ // The number of groups is calculated dividing the number of input channels of the input tensor by the number of input channels of the weights shape
+ const int num_groups = input_shape[2] / weights_shape[2];
+
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(input_shape, data_type);
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1);
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type, 1);
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ CLGEMMConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info, num_groups);
+
+ // Validate valid region
+ const ValidRegion src_valid_region = shape_to_valid_region(input_shape);
+ const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape);
+ const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape);
+ const ValidRegion dst_valid_region = shape_to_valid_region(output_shape);
+
+ validate(src.info()->valid_region(), src_valid_region);
+ validate(weights.info()->valid_region(), weights_valid_region);
+ validate(bias.info()->valid_region(), bias_valid_region);
+ validate(dst.info()->valid_region(), dst_valid_region);
+
+ // Validate padding
+}
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // Float
+
+TEST_SUITE_END() // GroupedGEMMConvolutionLayer
+TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute