COMPMID-594: Implement reference and CL/NEON validation for LocallyConnected

Change-Id: I01e7abcf3f1b19458128e277044af850ad9fa224
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118610
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

1 files changed, 111 insertions, 0 deletions

diff --git a/tests/validation/reference/LocallyConnected.cpp b/tests/validation/reference/LocallyConnected.cpp
new file mode 100644
index 0000000000..08e3f02761
--- /dev/null
+++ b/tests/validation/reference/LocallyConnected.cpp
@@ -0,0 +1,111 @@
+/*
+ * Copyright (c) 2017-2018 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.
+ */
+#include "LocallyConnected.h"
+
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/Convolution3d.h"
+#include "tests/validation/reference/Utils.h"
+
+#include "tests/framework/Asserts.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename TB>
+SimpleTensor<T> locally_connected(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info)
+{
+    // Create reference
+    SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+
+    // Compute reference
+    const int width_in  = src.shape().x();
+    const int height_in = src.shape().y();
+    const int depth_in  = src.shape().z();
+
+    const int width_out  = dst.shape().x();
+    const int height_out = dst.shape().y();
+    const int depth_out  = dst.shape().z();
+
+    const int width_weights  = weights.shape().x();
+    const int height_weights = weights.shape().y();
+    const int depth_weights  = weights.shape().z();
+
+    const int pad_left  = info.pad_left();
+    const int pad_top   = info.pad_top();
+    const int stride_xi = info.stride().first;
+    const int stride_yi = info.stride().second;
+
+    auto output_wh = scaled_dimensions(width_in, height_in, width_weights, height_weights, info);
+
+    const int start_xi    = width_weights / 2 - pad_left;
+    const int start_yi    = height_weights / 2 - pad_top;
+    const int end_xi      = output_wh.first * stride_xi;
+    const int end_yi      = output_wh.second * stride_yi;
+    const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in);
+
+    for(int r = 0; r < num_batches; ++r)
+    {
+        int count = 0;
+        for(int yi = start_yi; yi < start_yi + end_yi; yi += stride_yi)
+        {
+            for(int xi = start_xi; xi < start_xi + end_xi; xi += stride_xi)
+            {
+                for(int ofm = 0; ofm < depth_out; ++ofm)
+                {
+                    // Compute input and output offsets
+                    const int offset_in  = r * width_in * height_in * depth_in;
+                    const int xo         = (xi - start_xi) / stride_xi;
+                    const int yo         = (yi - start_yi) / stride_yi;
+                    const int offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out;
+
+                    ARM_COMPUTE_ASSERT(xo < width_out);
+                    ARM_COMPUTE_ASSERT(yo < height_out);
+
+                    // Compute 3D convolution
+                    convolution_3d::detail::convolution3d(src, weights, bias, dst,
+                                                          offset_in, count * width_weights * height_weights * depth_weights, count, offset_out,
+                                                          xi, yi,
+                                                          width_in, height_in, depth_in,
+                                                          width_weights, height_weights);
+                    count++;
+                }
+            }
+        }
+    }
+
+    return dst;
+}
+
+// Locally Connected only supports F32
+template SimpleTensor<float> locally_connected(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape,
+                                               const PadStrideInfo &info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute