COMPMID-935 Implementing Convolution with Winograd on OpenCL (part 3)
Change-Id: I51f92f30602fb0a02314f344fa67061f448694bf
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/122793
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp
index 313b059..3d554f0 100644
--- a/tests/validation/Helpers.cpp
+++ b/tests/validation/Helpers.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,6 +23,9 @@
*/
#include "tests/validation/Helpers.h"
+#include <algorithm>
+#include <cmath>
+
namespace arm_compute
{
namespace test
@@ -133,6 +136,111 @@
}
return dst;
}
+
+void matrix_multiply(const SimpleTensor<float> &a, const SimpleTensor<float> &b, SimpleTensor<float> &out)
+{
+ ARM_COMPUTE_ERROR_ON(a.shape()[0] != b.shape()[1]);
+ ARM_COMPUTE_ERROR_ON(a.shape()[1] != out.shape()[1]);
+ ARM_COMPUTE_ERROR_ON(b.shape()[0] != out.shape()[0]);
+
+ const int M = a.shape()[1]; // Rows
+ const int N = b.shape()[0]; // Cols
+ const int K = b.shape()[1];
+
+ for(int y = 0; y < M; ++y)
+ {
+ for(int x = 0; x < N; ++x)
+ {
+ float acc = 0.0f;
+ for(int k = 0; k < K; ++k)
+ {
+ acc += a[y * K + k] * b[x + k * N];
+ }
+
+ out[x + y * N] = acc;
+ }
+ }
+}
+
+void transpose_matrix(const SimpleTensor<float> &in, SimpleTensor<float> &out)
+{
+ ARM_COMPUTE_ERROR_ON((in.shape()[0] != out.shape()[1]) || (in.shape()[1] != out.shape()[0]));
+
+ const int width = in.shape()[0];
+ const int height = in.shape()[1];
+
+ for(int y = 0; y < height; ++y)
+ {
+ for(int x = 0; x < width; ++x)
+ {
+ const float val = in[x + y * width];
+
+ out[x * height + y] = val;
+ }
+ }
+}
+
+template <typename T>
+void get_tile(const SimpleTensor<T> &in, SimpleTensor<T> &tile, const Coordinates &coord)
+{
+ ARM_COMPUTE_ERROR_ON(tile.shape().num_dimensions() != 2);
+
+ const int w_tile = tile.shape()[0];
+ const int h_tile = tile.shape()[1];
+
+ // Fill the tile with zeros
+ std::fill(tile.data() + 0, (tile.data() + (w_tile * h_tile)), static_cast<T>(0));
+
+ // Check if with the dimensions greater than 2 we could have out-of-bound reads
+ for(size_t d = 2; d < Coordinates::num_max_dimensions; ++d)
+ {
+ if(coord[d] < 0 || coord[d] >= static_cast<int>(in.shape()[d]))
+ {
+ ARM_COMPUTE_ERROR("coord[d] < 0 || coord[d] >= in.shape()[d] with d >= 2");
+ }
+ }
+
+ // Since we could have out-of-bound reads along the X and Y dimensions,
+ // we start calculating the input address with x = 0 and y = 0
+ Coordinates start_coord = coord;
+ start_coord[0] = 0;
+ start_coord[1] = 0;
+
+ // Get input and roi pointers
+ auto in_ptr = static_cast<const T *>(in(start_coord));
+ auto roi_ptr = static_cast<T *>(tile.data());
+
+ const int x_in_start = std::max(0, coord[0]);
+ const int y_in_start = std::max(0, coord[1]);
+ const int x_in_end = std::min(static_cast<int>(in.shape()[0]), coord[0] + w_tile);
+ const int y_in_end = std::min(static_cast<int>(in.shape()[1]), coord[1] + h_tile);
+
+ // Number of elements to copy per row
+ const int n = x_in_end - x_in_start;
+
+ // Starting coordinates for the ROI
+ const int x_tile_start = coord[0] > 0 ? 0 : std::abs(coord[0]);
+ const int y_tile_start = coord[1] > 0 ? 0 : std::abs(coord[1]);
+
+ // Update input pointer
+ in_ptr += x_in_start;
+ in_ptr += (y_in_start * in.shape()[0]);
+
+ // Update ROI pointer
+ roi_ptr += x_tile_start;
+ roi_ptr += (y_tile_start * tile.shape()[0]);
+
+ for(int y = y_in_start; y < y_in_end; ++y)
+ {
+ // Copy per row
+ std::copy(in_ptr, in_ptr + n, roi_ptr);
+
+ in_ptr += in.shape()[0];
+ roi_ptr += tile.shape()[0];
+ }
+}
+
+template void get_tile(const SimpleTensor<float> &in, SimpleTensor<float> &roi, const Coordinates &coord);
} // namespace validation
} // namespace test
} // namespace arm_compute