COMPMID-470: Neon Deconvolution.

Implemented by up-sampling the input with zeros insertions between the input samples and convolving the Deconvolution kernels on the up-sampled result.

The upsampling is performed by the function NEDeconvolutionLayerUpsample.
Convolving is done by NEDirectConvolutionLayer.

Change-Id: I25f7ba7c6b99cd9310797972ede40aeff4a54900
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/85319
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

2 files changed, 163 insertions, 0 deletions

diff --git a/tests/validation/CPP/DeconvolutionLayer.cpp b/tests/validation/CPP/DeconvolutionLayer.cpp
new file mode 100644
index 0000000000..34f3d10edb
--- /dev/null
+++ b/tests/validation/CPP/DeconvolutionLayer.cpp
@@ -0,0 +1,108 @@
+/*
+ * 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 "ConvolutionLayer.h"
+
+#include "tests/validation/FixedPoint.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &bias, const TensorShape &output_shape,
+                                    const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a)
+{
+    // Create reference
+    TensorShape scaled_shape = src.shape();
+    scaled_shape.set(0, output_shape.x());
+    scaled_shape.set(1, output_shape.y());
+    SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1, src.fixed_point_position() };
+
+    const int          width_in      = src.shape().x();
+    const int          height_in     = src.shape().y();
+    const int          width_scaled  = scaled.shape().x();
+    const int          height_scaled = scaled.shape().y();
+    const int          num_2d_slices = src.shape().total_size() / (width_in * height_in);
+    const auto         width_ratio   = static_cast<float>(width_in) / static_cast<float>(width_scaled);
+    const auto         height_ratio  = static_cast<float>(height_in) / static_cast<float>(height_scaled);
+    const int          ax            = a.first;  // The number of zeros added to right edge of the input.
+    const int          ay            = a.second; // The number of zeros added to bottom edge of the input.
+    const unsigned int kernel_size   = weights.shape().x();
+    ARM_COMPUTE_ERROR_ON(info.pad().first > (kernel_size - 1));
+    const int transposed_convolution_padx = kernel_size - info.pad().first - 1;
+    const int transposed_convolution_pady = kernel_size - info.pad().second - 1;
+    const int stridex                     = info.stride().first;
+    const int stridey                     = info.stride().second;
+
+    for(int j = 0; j < scaled.num_elements(); ++j)
+    {
+        scaled[j] = T(0);
+    }
+
+    for(int slice = 0; slice < num_2d_slices; ++slice)
+    {
+        const int offset_slice_in  = slice * width_in * height_in;
+        const int offset_slice_out = slice * width_scaled * height_scaled;
+        for(int yi = ay; yi < height_scaled; yi += stridey)
+        {
+            for(int xi = transposed_convolution_padx; xi < width_scaled; xi += stridex)
+            {
+                const float x_src     = (xi + 0.5f) * width_ratio - 0.5f;
+                const float y_src     = (yi + 0.5f) * height_ratio - 0.5f;
+                T          *out       = scaled.data() + offset_slice_out + xi + yi * width_scaled;
+                const bool  in_bounds = x_src > -1 && y_src > -1 && x_src < width_in && y_src < height_in;
+                const bool  in_axy    = xi < transposed_convolution_padx || xi >= (width_scaled - ax)  // this is checking if the x coordinate is in the padded left/right area
+                                        || yi < ay || yi >= (height_scaled - transposed_convolution_pady); // like above but top and bottom padding in the upscaled XY plane
+                if(!in_axy)
+                {
+                    if(in_bounds)
+                    {
+                        const int in_scaled_x = support::cpp11::round(x_src);
+                        const int in_scaled_y = support::cpp11::round(y_src);
+                        const T *in          = src.data() + offset_slice_in + in_scaled_x + in_scaled_y * width_in;
+                        *out                  = *in;
+                    }
+                    else
+                    {
+                        *out = T(0);
+                    }
+                }
+            }
+        }
+    }
+    const PadStrideInfo conv_info(1, 1, 1, 1, DimensionRoundingType::CEIL);
+    return convolution_layer(scaled, weights, bias, output_shape, conv_info);
+}
+
+template SimpleTensor<float> deconvolution_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape,
+                                                 const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/CPP/DeconvolutionLayer.h b/tests/validation/CPP/DeconvolutionLayer.h
new file mode 100644
index 0000000000..8222e32027
--- /dev/null
+++ b/tests/validation/CPP/DeconvolutionLayer.h
@@ -0,0 +1,55 @@
+/*
+ * 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.
+ */
+#ifndef __ARM_COMPUTE_TEST_DECONVOLUTION_LAYER_H__
+#define __ARM_COMPUTE_TEST_DECONVOLUTION_LAYER_H__
+
+#include "tests/SimpleTensor.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+/** Deconvolution reference implementation.
+ *
+ * src              Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32.
+ * weights          The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input.
+ * bias             Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input.
+ * output_shape     Output tensor shape. The output has the same number of dimensions as the @p input.
+ * info             Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
+ * a                The number of zeros added to right edge of the input.
+ *
+ */
+template <typename T>
+SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &bias, const TensorShape &output_shape, const PadStrideInfo &info,
+                                    const std::pair<unsigned int, unsigned int> &a);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_DECONVOLUTION_LAYER_H__ */