Provide tests for fusing pad layer in graph API
There are two tests:
- A unit test that checks if certain padding configurations are to be
fused or not
- A fixture test that compares a reference implementation of pad+conv
vs target implementation using the same fusing logic as graph API
Tests are written for CL backend only to prevent code duplication.
The code written in the graph API remains untested.
Resolves: COMPMID-4702
Change-Id: Ie84d1cb910013033b46ac9d66cf5fc556d4963d2
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6252
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sheri Zhang <sheri.zhang@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h
index 7d1db5a..67eade1 100644
--- a/tests/datasets/SmallConvolutionLayerDataset.h
+++ b/tests/datasets/SmallConvolutionLayerDataset.h
@@ -181,6 +181,17 @@
}
};
+class SmallConvolutionLayerPrePaddingDataset final : public ConvolutionLayerDataset
+{
+public:
+ SmallConvolutionLayerPrePaddingDataset()
+ {
+ // output shape is calculated by accounting pre-padding layer as well -- all the data is in nchw
+ add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(17U, 16U, 19U), PadStrideInfo(1, 2, 1, 1));
+ add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(12U, 13U, 16U), PadStrideInfo(3, 2, 2, 0));
+ }
+};
+
class SmallConvolutionLayerReducedDataset final : public ConvolutionLayerDataset
{
public:
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 6824ce1..ae2949c 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -188,6 +188,8 @@
using CLGEMMConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
template <typename T>
using CLGEMMConvolutionLayerMixedDataLayoutFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T, true>;
+template <typename T>
+using CLConvolutionValidationWithPaddingFixture = ConvolutionValidationWithPaddingFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
TEST_SUITE(Float)
TEST_SUITE(FP16)
@@ -232,6 +234,18 @@
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
+FIXTURE_DATA_TEST_CASE(RunSmallWithPadding, CLConvolutionValidationWithPaddingFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerPrePaddingDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })),
+framework::dataset::make("PrePadLayer", { PaddingList({ { 1, 1 }, { 1, 1 } }) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
diff --git a/tests/validation/CL/PadLayer.cpp b/tests/validation/CL/PadLayer.cpp
index 370195b..ea0cb32 100644
--- a/tests/validation/CL/PadLayer.cpp
+++ b/tests/validation/CL/PadLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -21,8 +21,10 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
+#include "arm_compute/graph/Utils.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "arm_compute/runtime/CL/functions/CLPadLayer.h"
+#include "src/graph/mutators/MutatorUtils.h"
#include "tests/CL/CLAccessor.h"
#include "tests/Globals.h"
#include "tests/datasets/ShapeDatasets.h"
@@ -110,6 +112,63 @@
ARM_COMPUTE_EXPECT(bool(CLPadLayer::validate(&input_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), padding, PixelValue(), mode)) == expected, framework::LogLevel::ERRORS);
}
+DATA_TEST_CASE(CheckFusingWithConvolution, framework::DatasetMode::ALL, zip(zip(
+ framework::dataset::make("DataLayout", { DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NCHW,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::NHWC,
+ DataLayout::UNKNOWN
+ }),
+ framework::dataset::make("PaddingList", { PaddingList({{0, 0}, {1, 1}, {1, 1}}), // nchw
+ PaddingList({{1, 1}, {1, 1}, {0, 0}, {0, 0}}),
+ PaddingList({{1, 1}, {1, 1}}),
+ PaddingList({}),
+ PaddingList({{0, 0}}),
+ PaddingList({{0, 0}, {0, 0}, {0, 0}, {0, 0}}),
+ PaddingList({{0, 0}, {0, 0}, {0, 0}, {1, 0}}),
+ PaddingList({{0, 1}}),
+ PaddingList({{0, 0}, {1, 1}, {1, 1}}), // nhwc
+ PaddingList({{0, 0}, {0, 0}, {1, 1}, {1, 1}}),
+ PaddingList({{0, 0}, {1, 0}, {1, 1}, {0, 0}}),
+ PaddingList({}),
+ PaddingList({{0, 0}}),
+ PaddingList({{0, 1}}),
+ PaddingList({{0, 0}, {1, 1}}),
+ PaddingList({{0, 0}})
+ })), // unknown
+ framework::dataset::make("Expected", { false, // nchw
+ true,
+ true,
+ true,
+ true,
+ true,
+ false,
+ true,
+ true, // nhwc
+ false,
+ true,
+ true,
+ true,
+ false,
+ true,
+ false // unknown
+ })),
+ data_layout, padding_list, expected)
+{
+ ARM_COMPUTE_EXPECT(expected == arm_compute::graph::is_padding_in_height_or_width(data_layout, padding_list), framework::LogLevel::ERRORS);
+}
+
// clang-format on
// *INDENT-ON*
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 6dbf3d5..0b3f070 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -26,7 +26,9 @@
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
+#include "arm_compute/graph/Utils.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
+#include "src/graph/mutators/MutatorUtils.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/IAccessor.h"
@@ -35,6 +37,7 @@
#include "tests/validation/Helpers.h"
#include "tests/validation/reference/ActivationLayer.h"
#include "tests/validation/reference/ConvolutionLayer.h"
+#include "tests/validation/reference/PadLayer.h"
#include "tests/validation/reference/Permute.h"
#include "tests/validation/reference/Utils.h"
@@ -70,7 +73,7 @@
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights,
DataType data_type, DataType weights_data_type, DataLayout data_layout, QuantizationInfo quantization_info, QuantizationInfo weight_quantization_info, ActivationLayerInfo act_info,
- bool mixed_layout = false)
+ bool mixed_layout = false, PaddingList pre_pad_layer = PaddingList({}))
{
_mixed_layout = mixed_layout;
_data_type = data_type;
@@ -83,8 +86,8 @@
_weight_quantization_info = weight_quantization_info;
_data_layout = data_layout;
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info, pre_pad_layer);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info, pre_pad_layer);
}
protected:
@@ -179,8 +182,9 @@
}
}
+ // given input is IN nchw format
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)
+ bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({}))
{
ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
@@ -191,6 +195,18 @@
permute(input_shape, PermutationVector(2U, 0U, 1U));
permute(weights_shape, PermutationVector(2U, 0U, 1U));
permute(output_shape, PermutationVector(2U, 0U, 1U));
+
+ if(pre_pad_layer.size() > 0)
+ {
+ // make sure paddings exist for each c,h,w dimensions
+ for(unsigned int i = 0; i < 3 - pre_pad_layer.size(); ++i)
+ {
+ pre_pad_layer.push_back({ 0, 0 });
+ }
+
+ // rotate padding info from nchw to nhwc
+ std::rotate(pre_pad_layer.begin(), pre_pad_layer.begin() + 2, pre_pad_layer.begin() + 3);
+ }
}
const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
@@ -207,7 +223,30 @@
// Create and configure function
FunctionType conv;
- detail::configure_conv_function(conv, &src, &weights, &bias, &dst, info, weights_info, dilation, act_info, num_groups);
+
+ const unsigned int height_index = arm_compute::graph::get_dimension_idx(_data_layout, DataLayoutDimension::HEIGHT);
+ const unsigned int width_index = arm_compute::graph::get_dimension_idx(_data_layout, DataLayoutDimension::WIDTH);
+
+ const PaddingInfo pad_w = width_index < pre_pad_layer.size() ? pre_pad_layer[width_index] : PaddingInfo(0, 0);
+ const PaddingInfo pad_h = height_index < pre_pad_layer.size() ? pre_pad_layer[height_index] : PaddingInfo(0, 0);
+
+ if(pre_pad_layer.size() > 0 && arm_compute::graph::is_padding_in_height_or_width(_data_layout, pre_pad_layer))
+ {
+ // this is the logic implemented in NodeFusionMutator -> fuse_pad_with_convolution
+ const PadStrideInfo new_conv_info(
+ info.stride().first,
+ info.stride().second,
+ info.pad_left() + pad_w.first,
+ info.pad_right() + pad_w.second,
+ info.pad_top() + pad_h.first,
+ info.pad_bottom() + pad_h.second,
+ info.round());
+ detail::configure_conv_function(conv, &src, &weights, &bias, &dst, new_conv_info, weights_info, dilation, act_info, num_groups);
+ }
+ else
+ {
+ detail::configure_conv_function(conv, &src, &weights, &bias, &dst, info, weights_info, dilation, act_info, num_groups);
+ }
ARM_COMPUTE_ASSERT(src.info()->is_resizable());
ARM_COMPUTE_ASSERT(weights.info()->is_resizable());
@@ -246,7 +285,7 @@
}
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)
+ const Size2D &dilation, const ActivationLayerInfo act_info, PaddingList pre_pad_layer = PaddingList({}))
{
ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
@@ -273,6 +312,11 @@
regularize_values(static_cast<void *>(weights.data()), weights.num_elements());
}
+ if(pre_pad_layer.size() > 0)
+ {
+ src = reference::pad_layer<T>(src, pre_pad_layer, PixelValue(0), PaddingMode::CONSTANT);
+ }
+
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, num_groups);
@@ -307,6 +351,20 @@
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
+class ConvolutionValidationWithPaddingFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>
+{
+public:
+ template <typename...>
+ 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, PaddingList pre_pad_layer = PaddingList({}))
+ {
+ ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights,
+ data_type, data_type, data_layout,
+ QuantizationInfo(), QuantizationInfo(), act_info, mixed_layout, pre_pad_layer);
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
class ConvolutionValidationQuantizedFixture : public ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T, T>
{
public: