COMPMID-432 - Extended Convolution Layer to support rectangular kernels
Change-Id: I99be1efede4de6dd63ce103fb11196c413757621
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79252
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
diff --git a/tests/dataset/ConvolutionLayerDataset.h b/tests/dataset/ConvolutionLayerDataset.h
index 85f46cc..402fae3 100644
--- a/tests/dataset/ConvolutionLayerDataset.h
+++ b/tests/dataset/ConvolutionLayerDataset.h
@@ -73,7 +73,7 @@
using ConvolutionLayerDataset = GenericDataset<ConvolutionLayerDataObject, Size>;
/** Data set containing small convolution layer shapes */
-class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset<3>
+class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset<6>
{
public:
SmallConvolutionLayerDataset()
@@ -81,7 +81,10 @@
{
ConvolutionLayerDataObject{ TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0) },
ConvolutionLayerDataObject{ TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0) },
- ConvolutionLayerDataObject{ TensorShape(17U, 31U, 2U, 7U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U, 7U), PadStrideInfo(1, 2, 1, 1) }
+ ConvolutionLayerDataObject{ TensorShape(17U, 31U, 2U, 7U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U, 7U), PadStrideInfo(1, 2, 1, 1) },
+ ConvolutionLayerDataObject{ TensorShape(23U, 27U, 5U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U), PadStrideInfo(2, 1, 0, 0) },
+ ConvolutionLayerDataObject{ TensorShape(33U, 27U, 7U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U), PadStrideInfo(3, 2, 1, 0) },
+ ConvolutionLayerDataObject{ TensorShape(17U, 31U, 2U, 7U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U, 7U), PadStrideInfo(1, 2, 1, 1) }
}
{
}
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
new file mode 100644
index 0000000..60e8754
--- /dev/null
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -0,0 +1,191 @@
+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "CL/CLAccessor.h"
+
+#include "TypePrinter.h"
+#include "dataset/ConvolutionLayerDataset.h"
+#include "tests/Globals.h"
+#include "tests/Utils.h"
+#include "validation/Datasets.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+
+#include <random>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::cl;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+
+CLTensor compute_convolution_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt,
+ const PadStrideInfo &conv_info, int fixed_point_position)
+{
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(input_shape, dt, 1, fixed_point_position);
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, dt, 1, fixed_point_position);
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, dt, 1, fixed_point_position);
+ CLTensor dst = create_tensor<CLTensor>(output_shape, dt, 1, fixed_point_position);
+
+ // Create and configure function
+ CLConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, conv_info);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ weights.allocator()->allocate();
+ bias.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ BOOST_TEST(!src.info()->is_resizable());
+ BOOST_TEST(!weights.info()->is_resizable());
+ BOOST_TEST(!bias.info()->is_resizable());
+ BOOST_TEST(!dst.info()->is_resizable());
+
+ // Fill tensors
+ if(dt == DataType::F32)
+ {
+ std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+ library->fill(CLAccessor(src), distribution, 0);
+ library->fill(CLAccessor(weights), distribution, 1);
+ library->fill(CLAccessor(bias), distribution, 2);
+ }
+ else
+ {
+ library->fill_tensor_uniform(CLAccessor(src), 0);
+ library->fill_tensor_uniform(CLAccessor(weights), 1);
+ library->fill_tensor_uniform(CLAccessor(bias), 2);
+ }
+
+ // Compute CLConvolutionLayer function
+ conv.run();
+
+ return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(CL)
+BOOST_AUTO_TEST_SUITE(ConvolutionLayer)
+BOOST_AUTO_TEST_SUITE(GEMM)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration,
+ AlexNetConvolutionLayerDataset() * boost::unit_test::data::make({ DataType::F32 }),
+ conv_set, dt)
+{
+ // Set fixed point position data type allowed
+ int fixed_point_position = (dt == DataType::F32) ? 0 : 3;
+
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(conv_set.src_shape, dt, 1, fixed_point_position);
+ CLTensor weights = create_tensor<CLTensor>(conv_set.weights_shape, dt, 1, fixed_point_position);
+ CLTensor bias = create_tensor<CLTensor>(conv_set.bias_shape, dt, 1, fixed_point_position);
+ CLTensor dst = create_tensor<CLTensor>(conv_set.dst_shape, dt, 1, fixed_point_position);
+
+ BOOST_TEST(src.info()->is_resizable());
+ BOOST_TEST(weights.info()->is_resizable());
+ BOOST_TEST(bias.info()->is_resizable());
+ BOOST_TEST(dst.info()->is_resizable());
+
+ // Create and configure function
+ CLConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, conv_set.info);
+
+ // Validate valid region
+ const ValidRegion src_valid_region = shape_to_valid_region(conv_set.src_shape);
+ const ValidRegion weights_valid_region = shape_to_valid_region(conv_set.weights_shape);
+ const ValidRegion bias_valid_region = shape_to_valid_region(conv_set.bias_shape);
+ const ValidRegion dst_valid_region = shape_to_valid_region(conv_set.dst_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);
+}
+
+#ifdef ARM_COMPUTE_ENABLE_FP16
+BOOST_AUTO_TEST_SUITE(Float16)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(SmallConvolutionLayer,
+ SmallConvolutionLayerDataset() * boost::unit_test::data::make(DataType::F16),
+ conv_set, dt)
+{
+ // Compute function
+ CLTensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Validate output
+ validate(CLAccessor(dst), ref_dst, tolerance_f32);
+}
+BOOST_AUTO_TEST_SUITE_END()
+#endif
+
+BOOST_AUTO_TEST_SUITE(Float)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(SmallConvolutionLayer,
+ SmallConvolutionLayerDataset() * boost::unit_test::data::make(DataType::F32),
+ conv_set, dt)
+{
+ // Compute function
+ CLTensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Validate output
+ validate(CLAccessor(dst), ref_dst, tolerance_f32);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(LargeConvolutionLayer,
+ AlexNetConvolutionLayerDataset() * boost::unit_test::data::make(DataType::F32),
+ conv_set, dt)
+{
+ // Compute function
+ CLTensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Validate output
+ validate(CLAccessor(dst), ref_dst, tolerance_f32);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif