COMPMID-935 - Implementing Convolution with Winograd on OpenCL (part 4)
Implemented Winograd Output Transform (2x2,3x3) on OpenCL
Implemented CLWinogradConvolutionLayer on OpenCL
Change-Id: I6a113fc5f052ca07f878d2b800d2ab003f84af65
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125148
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
diff --git a/tests/datasets/LargeConvolutionLayerDataset.h b/tests/datasets/LargeConvolutionLayerDataset.h
index 086b2e3..ec8e09f 100644
--- a/tests/datasets/LargeConvolutionLayerDataset.h
+++ b/tests/datasets/LargeConvolutionLayerDataset.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -37,6 +37,28 @@
{
namespace datasets
{
+class LargeWinogradConvolutionLayer3x3Dataset final : public ConvolutionLayerDataset
+{
+public:
+ LargeWinogradConvolutionLayer3x3Dataset()
+ {
+ // Kernel size 3
+ // Batch size 1
+ add_config(TensorShape(224U, 222U, 64U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(112U, 113U, 64U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 113U, 128U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(112U, 112U, 128U), TensorShape(3U, 3U, 128U, 129U), TensorShape(129U), TensorShape(112U, 110U, 129U), PadStrideInfo(1, 1, 1, 0));
+ add_config(TensorShape(53U, 56U, 125U), TensorShape(3U, 3U, 125U, 256U), TensorShape(256U), TensorShape(51U, 56U, 256U), PadStrideInfo(1, 1, 0, 1));
+ add_config(TensorShape(56U, 56U, 256U), TensorShape(3U, 3U, 256U, 256U), TensorShape(256U), TensorShape(56U, 54U, 256U), PadStrideInfo(1, 1, 1, 0));
+ add_config(TensorShape(28U, 28U, 257U), TensorShape(3U, 3U, 257U, 512U), TensorShape(512U), TensorShape(26U, 28U, 512U), PadStrideInfo(1, 1, 0, 1));
+ add_config(TensorShape(28U, 28U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(14U, 14U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(12U, 12U, 512U), PadStrideInfo(1, 1, 0, 0));
+ // Batch size 3, 2 and 4
+ add_config(TensorShape(224U, 222U, 64U, 3U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 222U, 64U, 3U), PadStrideInfo(1, 1, 1, 1));
+ add_config(TensorShape(112U, 113U, 64U, 2U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(110U, 113U, 128U, 2U), PadStrideInfo(1, 1, 0, 1));
+ add_config(TensorShape(111U, 112U, 127U, 4U), TensorShape(3U, 3U, 127U, 128U), TensorShape(128U), TensorShape(111U, 112U, 128U, 4U), PadStrideInfo(1, 1, 1, 1));
+ }
+};
+
class LargeConvolutionLayerDataset final : public ConvolutionLayerDataset
{
public:
diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h
index adb61de..696c396 100644
--- a/tests/datasets/SmallConvolutionLayerDataset.h
+++ b/tests/datasets/SmallConvolutionLayerDataset.h
@@ -37,10 +37,10 @@
{
namespace datasets
{
-class SmallWinogradLayerDataset final : public ConvolutionLayerDataset
+class SmallWinogradConvolutionLayer3x3Dataset final : public ConvolutionLayerDataset
{
public:
- SmallWinogradLayerDataset()
+ SmallWinogradConvolutionLayer3x3Dataset()
{
// Kernel size 3
// Batch size 1
@@ -48,8 +48,14 @@
// Batch size 4
add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(21U, 25U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 1, 1));
+ }
+};
- // Kernel size 5
+class SmallWinogradConvolutionLayer5x5Dataset final : public ConvolutionLayerDataset
+{
+public:
+ SmallWinogradConvolutionLayer5x5Dataset()
+ {
add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U, 1U), TensorShape(1U), TensorShape(4U, 4U, 1U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 2, 2));
}
diff --git a/tests/datasets/WinogradOutputTransformDataset.h b/tests/datasets/WinogradOutputTransformDataset.h
new file mode 100644
index 0000000..c42d6c8
--- /dev/null
+++ b/tests/datasets/WinogradOutputTransformDataset.h
@@ -0,0 +1,153 @@
+/*
+ * Copyright (c) 2018 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.
+ */
+#ifndef ARM_COMPUTE_TEST_WINOGRAD_OUTPUT_TRANSFORM_DATASET
+#define ARM_COMPUTE_TEST_WINOGRAD_OUTPUT_TRANSFORM_DATASET
+
+#include "utils/TypePrinter.h"
+
+#include "arm_compute/core/TensorShape.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace datasets
+{
+class WinogradOutputTransformDataset
+{
+public:
+ using type = std::tuple<TensorShape, Size2D, Size2D, Size2D, DataLayout>;
+
+ struct iterator
+ {
+ iterator(std::vector<TensorShape>::const_iterator a_it,
+ std::vector<Size2D>::const_iterator b_it,
+ std::vector<Size2D>::const_iterator c_it,
+ std::vector<Size2D>::const_iterator d_it,
+ std::vector<DataLayout>::const_iterator data_layout_it)
+ : _a_it{ std::move(a_it) },
+ _b_it{ std::move(b_it) },
+ _c_it{ std::move(c_it) },
+ _d_it{ std::move(d_it) },
+ _data_layout_it{ std::move(data_layout_it) }
+ {
+ }
+
+ std::string description() const
+ {
+ std::stringstream description;
+ description << "Input=" << *_a_it << ":";
+ description << "KernelDims=" << *_b_it << ":";
+ description << "OutputDims=" << *_c_it << ":";
+ description << "NumTiles=" << *_d_it << ":";
+ description << "DataLayout=" << *_data_layout_it;
+ return description.str();
+ }
+
+ WinogradOutputTransformDataset::type operator*() const
+ {
+ return std::make_tuple(*_a_it, *_b_it, *_c_it, *_d_it, *_data_layout_it);
+ }
+
+ iterator &operator++()
+ {
+ ++_a_it;
+ ++_b_it;
+ ++_c_it;
+ ++_d_it;
+ ++_data_layout_it;
+
+ return *this;
+ }
+
+ private:
+ std::vector<TensorShape>::const_iterator _a_it;
+ std::vector<Size2D>::const_iterator _b_it;
+ std::vector<Size2D>::const_iterator _c_it;
+ std::vector<Size2D>::const_iterator _d_it;
+ std::vector<DataLayout>::const_iterator _data_layout_it;
+ };
+
+ iterator begin() const
+ {
+ return iterator(_a_shapes.begin(), _b_dims.begin(), _c_dims.begin(), _d_dims.begin(), _data_layout.begin());
+ }
+
+ int size() const
+ {
+ return std::min(_a_shapes.size(), std::min(_b_dims.size(), std::min(_c_dims.size(), std::min(_d_dims.size(), _data_layout.size()))));
+ }
+
+ void add_config(TensorShape a, Size2D b, Size2D c, Size2D d, DataLayout data_layout)
+ {
+ _a_shapes.emplace_back(std::move(a));
+ _b_dims.emplace_back(std::move(b));
+ _c_dims.emplace_back(std::move(c));
+ _d_dims.emplace_back(std::move(d));
+ _data_layout.emplace_back(std::move(data_layout));
+ }
+
+protected:
+ WinogradOutputTransformDataset() = default;
+ WinogradOutputTransformDataset(WinogradOutputTransformDataset &&) = default;
+
+private:
+ std::vector<TensorShape> _a_shapes{};
+ std::vector<Size2D> _b_dims{};
+ std::vector<Size2D> _c_dims{};
+ std::vector<Size2D> _d_dims{};
+ std::vector<DataLayout> _data_layout{};
+};
+
+class SmallWinogradOutputTransformDataset final : public WinogradOutputTransformDataset
+{
+public:
+ SmallWinogradOutputTransformDataset()
+ {
+ add_config(TensorShape(24U, 49U, 16U), Size2D(3, 3), Size2D(14U, 14U), Size2D(7U, 7U), DataLayout::NCHW);
+ add_config(TensorShape(13U, 6U, 16U), Size2D(3, 3), Size2D(5U, 4U), Size2D(3U, 2U), DataLayout::NCHW);
+ add_config(TensorShape(7U, 20U, 16U), Size2D(3, 3), Size2D(8U, 9U), Size2D(4U, 5U), DataLayout::NCHW);
+ add_config(TensorShape(24U, 49U, 16U, 3U), Size2D(3, 3), Size2D(14U, 14U), Size2D(7U, 7U), DataLayout::NCHW);
+ add_config(TensorShape(13U, 6U, 16U, 2U), Size2D(3, 3), Size2D(5U, 4U), Size2D(3U, 2U), DataLayout::NCHW);
+ add_config(TensorShape(7U, 20U, 16U, 5U), Size2D(3, 3), Size2D(8U, 9U), Size2D(4U, 5U), DataLayout::NCHW);
+ }
+};
+
+class LargeWinogradOutputTransformDataset final : public WinogradOutputTransformDataset
+{
+public:
+ LargeWinogradOutputTransformDataset()
+ {
+ add_config(TensorShape(128U, 3136U, 16U), Size2D(3, 3), Size2D(112U, 112U), Size2D(56U, 56U), DataLayout::NCHW);
+ add_config(TensorShape(256U, 784U, 16U), Size2D(3, 3), Size2D(55U, 55U), Size2D(28U, 28U), DataLayout::NCHW);
+ add_config(TensorShape(512U, 169U, 16U), Size2D(3, 3), Size2D(26U, 26U), Size2D(13U, 13U), DataLayout::NCHW);
+ add_config(TensorShape(128U, 3136U, 16U, 3U), Size2D(3, 3), Size2D(112U, 112U), Size2D(56U, 56U), DataLayout::NCHW);
+ add_config(TensorShape(256U, 784U, 16U, 2U), Size2D(3, 3), Size2D(55U, 55U), Size2D(28U, 28U), DataLayout::NCHW);
+ add_config(TensorShape(512U, 169U, 16U, 5U), Size2D(3, 3), Size2D(26U, 26U), Size2D(13U, 13U), DataLayout::NCHW);
+ }
+};
+} // namespace datasets
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_WINOGRAD_OUTPUT_TRANSFORM_DATASET */