COMPMID-1498 - Enable grouping in CLGEMMConvolutionLayer
Change-Id: I15c7df21773145b03f42b6f78bd7ad2e5b8a5219
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/144126
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/datasets/LargeConvolutionLayerDataset.h b/tests/datasets/LargeConvolutionLayerDataset.h
index 3eb98db..170d562 100644
--- a/tests/datasets/LargeConvolutionLayerDataset.h
+++ b/tests/datasets/LargeConvolutionLayerDataset.h
@@ -166,31 +166,51 @@
// Batch size 1
add_config(TensorShape(227U, 227U, 3U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U), PadStrideInfo(4, 4, 0, 0));
add_config(TensorShape(27U, 27U, 96U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U), PadStrideInfo(1, 1, 2, 2));
- add_config(TensorShape(13U, 13U, 256U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(13U, 13U, 256U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 0, 0));
+ add_config(TensorShape(13U, 13U, 384U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(224U, 224U, 3U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U), PadStrideInfo(2, 2, 3, 3));
add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0));
// Batch size 4
add_config(TensorShape(227U, 227U, 3U, 4U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 4U), PadStrideInfo(4, 4, 0, 0));
add_config(TensorShape(27U, 27U, 96U, 4U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 4U), PadStrideInfo(1, 1, 2, 2));
- add_config(TensorShape(13U, 13U, 256U, 4U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U, 4U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(13U, 13U, 256U, 4U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 0, 0));
+ add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(224U, 224U, 3U, 4U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U, 4U), PadStrideInfo(2, 2, 3, 3));
add_config(TensorShape(28U, 28U, 256U, 4U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U, 4U), PadStrideInfo(1, 1, 0, 0));
// Batch size 8
add_config(TensorShape(227U, 227U, 3U, 8U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 8U), PadStrideInfo(4, 4, 0, 0));
add_config(TensorShape(27U, 27U, 96U, 8U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 8U), PadStrideInfo(1, 1, 2, 2));
- add_config(TensorShape(13U, 13U, 256U, 8U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1));
- add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U, 8U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(13U, 13U, 256U, 8U), TensorShape(1U, 1U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 0, 0));
+ add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(1U, 1U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(224U, 224U, 3U, 8U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U, 8U), PadStrideInfo(2, 2, 3, 3));
add_config(TensorShape(28U, 28U, 256U, 8U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U, 8U), PadStrideInfo(1, 1, 0, 0));
// Arbitrary batch size
add_config(TensorShape(227U, 227U, 3U, 5U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 5U), PadStrideInfo(4, 4, 0, 0));
}
};
+
+class LargeGroupedConvolutionLayerDataset final : public ConvolutionLayerDataset
+{
+public:
+ LargeGroupedConvolutionLayerDataset()
+ {
+ // Batch size 1
+ add_config(TensorShape(227U, 227U, 4U), TensorShape(11U, 11U, 2U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U), PadStrideInfo(4, 4, 0, 0));
+ add_config(TensorShape(27U, 27U, 96U), TensorShape(5U, 5U, 24U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U), PadStrideInfo(1, 1, 2, 2));
+ add_config(TensorShape(13U, 13U, 256U), TensorShape(1U, 1U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 0, 0));
+ add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1));
+ // Batch size 4
+ add_config(TensorShape(227U, 227U, 4U, 4U), TensorShape(11U, 11U, 2U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 4U), PadStrideInfo(4, 4, 0, 0));
+ add_config(TensorShape(27U, 27U, 96U, 4U), TensorShape(5U, 5U, 24U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 4U), PadStrideInfo(1, 1, 2, 2));
+ add_config(TensorShape(13U, 13U, 256U, 4U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(13U, 13U, 384U, 4U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 4U), PadStrideInfo(1, 1, 1, 1));
+ // Batch size 8
+ add_config(TensorShape(227U, 227U, 4U, 8U), TensorShape(11U, 11U, 2U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U, 8U), PadStrideInfo(4, 4, 0, 0));
+ add_config(TensorShape(27U, 27U, 96U, 8U), TensorShape(5U, 5U, 24U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U, 8U), PadStrideInfo(1, 1, 2, 2));
+ add_config(TensorShape(13U, 13U, 256U, 8U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(13U, 13U, 384U, 8U), TensorShape(3U, 3U, 128U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U, 8U), PadStrideInfo(1, 1, 1, 1));
+ }
+};
} // namespace datasets
} // namespace test
} // namespace arm_compute
diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h
index ae12dd4..a288d07 100644
--- a/tests/datasets/SmallConvolutionLayerDataset.h
+++ b/tests/datasets/SmallConvolutionLayerDataset.h
@@ -146,6 +146,41 @@
add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR));
}
};
+
+class SmallGroupedConvolutionLayerDataset final : public ConvolutionLayerDataset
+{
+public:
+ SmallGroupedConvolutionLayerDataset()
+ {
+ // Batch size 1
+ // Number of groups = 2
+ add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
+ // Number of groups = 4
+ add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U), PadStrideInfo(3, 2, 1, 0));
+
+ // Batch size 4
+ // Number of groups = 2
+ add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
+ // Number of groups = 4
+ add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 4U), PadStrideInfo(3, 2, 1, 0));
+
+ // Arbitrary batch size
+ add_config(TensorShape(23U, 27U, 8U, 5U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 5U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U, 3U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 3U), PadStrideInfo(3, 2, 1, 0));
+ // Number of groups = 4
+ add_config(TensorShape(23U, 27U, 8U, 2U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 2U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 12U, 5U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 5U), PadStrideInfo(3, 2, 1, 0));
+
+ // Asymmetric padding
+ add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 2U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
+ add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 4U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
+ add_config(TensorShape(33U, 27U, 6U, 5U), TensorShape(5U, 7U, 3U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
+ }
+};
} // namespace datasets
} // namespace test
} // namespace arm_compute
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 54fdc0c..5c96cd4 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -58,6 +58,14 @@
DataType::F32,
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(),
@@ -219,7 +227,7 @@
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // FP16
TEST_SUITE(FP32)
@@ -244,8 +252,8 @@
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, absolute_tolerance_float);
}
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
template <typename T>
using CLGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
@@ -280,11 +288,106 @@
// 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
+ //TODO(COMPMID-415) Need to 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
diff --git a/tests/validation/CL/WeightsReshape.cpp b/tests/validation/CL/WeightsReshape.cpp
index 6dae0c7..30c231d 100644
--- a/tests/validation/CL/WeightsReshape.cpp
+++ b/tests/validation/CL/WeightsReshape.cpp
@@ -79,7 +79,7 @@
FIXTURE_DATA_TEST_CASE(RunSmall, CLWeightsReshapeFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::GroupedWeightsSmallShapes(), framework::dataset::make("DataType",
DataType::F32)),
framework::dataset::make("HasBias", { true, false })),
- framework::dataset::make("NumGroups", { 1, 2, 3 })))
+ framework::dataset::make("NumGroups", { 1, 2, 3, 4 })))
{
// Validate output
validate(CLAccessor(_target), _reference);
@@ -87,7 +87,7 @@
FIXTURE_DATA_TEST_CASE(RunLarge, CLWeightsReshapeFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::GroupedWeightsLargeShapes(), framework::dataset::make("DataType",
DataType::F32)),
framework::dataset::make("HasBias", { true, false })),
- framework::dataset::make("NumGroups", { 1, 2, 3 })))
+ framework::dataset::make("NumGroups", { 1, 2, 3, 4 })))
{
// Validate output
validate(CLAccessor(_target), _reference);
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 4a63264..3b420ea 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -102,6 +102,10 @@
TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const PadStrideInfo &info,
bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info)
{
+ ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
+
+ const unsigned int num_groups = input_shape[2] / weights_shape[2];
+
if(_data_layout == DataLayout::NHWC)
{
permute(input_shape, PermutationVector(2U, 0U, 1U));
@@ -123,7 +127,7 @@
// Create and configure function
FunctionType conv;
- conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation, act_info);
+ conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation, act_info, num_groups);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -155,6 +159,10 @@
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
const Size2D &dilation, const ActivationLayerInfo act_info)
{
+ ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
+
+ const unsigned int num_groups = input_shape[2] / weights_shape[2];
+
// Create reference
SimpleTensor<T> src{ input_shape, _data_type, 1, _quantization_info };
SimpleTensor<T> weights{ weights_shape, _data_type, 1, _quantization_info };
@@ -165,9 +173,9 @@
fill(weights, 1);
fill(bias, 2);
- return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation),
+ return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation, num_groups),
act_info) :
- reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation);
+ reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation, num_groups);
}
TensorType _target{};
@@ -187,7 +195,8 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
DataLayout data_layout, ActivationLayerInfo act_info)
{
- ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, data_layout,
+ ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights,
+ data_type, data_layout,
QuantizationInfo(), act_info);
}
};
diff --git a/tests/validation/reference/ConvolutionLayer.cpp b/tests/validation/reference/ConvolutionLayer.cpp
index 2d31405..f41a6fc 100644
--- a/tests/validation/reference/ConvolutionLayer.cpp
+++ b/tests/validation/reference/ConvolutionLayer.cpp
@@ -47,8 +47,10 @@
template <typename T, typename TB>
SimpleTensor<T> convolution_layer_nchw(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &dst, const PadStrideInfo &info,
- const Size2D &dilation)
+ const Size2D &dilation, unsigned int num_groups)
{
+ ARM_COMPUTE_ERROR_ON((src.shape()[2] / num_groups) != weights.shape()[2]);
+
// Compute reference
const int width_in = src.shape().x();
const int height_in = src.shape().y();
@@ -78,23 +80,28 @@
{
for(int xi = start_xi; xi < start_xi + end_xi; xi += stride_xi)
{
- for(int ofm = 0; ofm < depth_out; ++ofm)
+ for(int group = 0; group < static_cast<int>(num_groups); ++group)
{
- // Compute input and output offsets
- const int offset_in = r * width_in * height_in * depth_in;
- const int xo = (xi - start_xi) / stride_xi;
- const int yo = (yi - start_yi) / stride_yi;
- const int offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out;
+ for(int ofm = 0; ofm < static_cast<int>(depth_out / num_groups); ++ofm)
+ {
+ // Compute input and output offsets
+ const int offset_in = r * width_in * height_in * depth_in + (group * (depth_in / num_groups) * width_in * height_in);
+ const int xo = (xi - start_xi) / stride_xi;
+ const int yo = (yi - start_yi) / stride_yi;
+ const int offset_out = xo + yo * width_out + ((ofm + group * (depth_out / num_groups)) * width_out * height_out) + (r * width_out * height_out * depth_out);
+ const int offset_w = (ofm + group * (depth_out / num_groups)) * width_weights * height_weights * depth_weights;
+ const int offset_b = (ofm + group * (depth_out / num_groups));
- ARM_COMPUTE_ASSERT(xo < width_out);
- ARM_COMPUTE_ASSERT(yo < height_out);
+ ARM_COMPUTE_ASSERT(xo < width_out);
+ ARM_COMPUTE_ASSERT(yo < height_out);
- // Compute 3D convolution
- convolution_3d::detail::convolution3d(src, weights, bias, dst,
- offset_in, ofm * width_weights * height_weights * depth_weights, ofm, offset_out,
- xi, yi,
- width_in, height_in, depth_in,
- width_weights, height_weights, dilation.x(), dilation.y());
+ // Compute 3D convolution
+ convolution_3d::detail::convolution3d(src, weights, bias, dst,
+ offset_in, offset_w, offset_b, offset_out,
+ xi, yi,
+ width_in, height_in, (depth_in / num_groups),
+ width_weights, height_weights, dilation.x(), dilation.y());
+ }
}
}
}
@@ -104,7 +111,7 @@
}
template <typename T, typename TB>
SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info,
- const Size2D &dilation)
+ const Size2D &dilation, unsigned int num_groups)
{
// Create reference
SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.quantization_info() };
@@ -115,20 +122,20 @@
SimpleTensor<T> weights_nchw = reference::permute<T>(weights, PermutationVector(1U, 2U, 0U));
SimpleTensor<T> dst_nchw = reference::permute<T>(dst, PermutationVector(1U, 2U, 0U));
- return reference::permute<T>(convolution_layer_nchw(src_nchw, weights_nchw, bias, dst_nchw, info, dilation), PermutationVector(2U, 0U, 1U));
+ return reference::permute<T>(convolution_layer_nchw(src_nchw, weights_nchw, bias, dst_nchw, info, dilation, num_groups), PermutationVector(2U, 0U, 1U));
}
else
{
- return convolution_layer_nchw(src, weights, bias, dst, info, dilation);
+ return convolution_layer_nchw(src, weights, bias, dst, info, dilation, num_groups);
}
}
template SimpleTensor<float> convolution_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape,
- const PadStrideInfo &info, const Size2D &dilation);
+ const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups);
template SimpleTensor<half> convolution_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &output_shape,
- const PadStrideInfo &info, const Size2D &dilation);
+ const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups);
template SimpleTensor<uint8_t> convolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
- const PadStrideInfo &info, const Size2D &dilation);
+ const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/ConvolutionLayer.h b/tests/validation/reference/ConvolutionLayer.h
index ff3b153..ccce53a 100644
--- a/tests/validation/reference/ConvolutionLayer.h
+++ b/tests/validation/reference/ConvolutionLayer.h
@@ -37,7 +37,7 @@
{
template <typename T, typename TB>
SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info,
- const Size2D &dilation = Size2D(1U, 1U));
+ const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1);
} // namespace reference
} // namespace validation
} // namespace test