COMPMID-1775: Implement CLGEMMReshapeRHSMatrixKernel to reshape the RHS matrix of GEMM/GEMMLowp

Change-Id: I77f2bfcc5d170bcc2428a2f27104942c1ec877d7
Reviewed-on: https://review.mlplatform.org/375
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 111 insertions, 0 deletions

diff --git a/tests/validation/reference/GEMMReshapeRHSMatrix.cpp b/tests/validation/reference/GEMMReshapeRHSMatrix.cpp
new file mode 100644
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+++ b/tests/validation/reference/GEMMReshapeRHSMatrix.cpp
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+/*
+ * 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.
+ */
+#include "GEMMReshapeRHSMatrix.h"
+
+#include "arm_compute/core/Types.h"
+
+#include "tests/validation/Helpers.h"
+
+#include <algorithm>
+#include <cmath>
+#include <cstring>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> gemm_reshape_rhs_matrix(const SimpleTensor<T> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info)
+{
+    ARM_COMPUTE_ERROR_ON(in.shape().num_dimensions() > 3);
+
+    SimpleTensor<T> out{ output_shape, in.data_type() };
+
+    // Initialize the output tensor with zero
+    std::memset(&out[0], 0, out.num_elements() * sizeof(T));
+
+    const unsigned int N = in.shape()[0];
+    const unsigned int K = in.shape()[1];
+    const unsigned int B = in.shape()[2];
+
+    const unsigned int num_tiles_x = std::ceil(N / static_cast<float>(rhs_info.n0));
+    const unsigned int num_tiles_y = std::ceil(K / static_cast<float>(rhs_info.k0));
+
+    const TensorShape tile_dims(rhs_info.n0, rhs_info.k0);
+    const TensorShape tile_dims_transposed(rhs_info.k0, rhs_info.n0);
+
+    // Simple tensor for the input tile
+    SimpleTensor<T> src_tile{ tile_dims, in.data_type() };
+
+    // Simple tensor for the input tile
+    SimpleTensor<T> src_tile_transposed{ tile_dims_transposed, in.data_type() };
+
+    // Simple tensor to use when storing the values
+    SimpleTensor<T> *tile_to_use = rhs_info.transpose ? &src_tile_transposed : &src_tile;
+
+    const unsigned int offset_output_x = rhs_info.interleave ? tile_to_use->shape()[0] : tile_to_use->shape()[0] * tile_to_use->shape()[1];
+    const unsigned int step_output_x   = rhs_info.interleave ? tile_to_use->shape()[0] * rhs_info.h0 : tile_to_use->shape()[0];
+
+    for(unsigned int z = 0; z < B; ++z)
+    {
+        for(unsigned int y = 0; y < num_tiles_y; ++y)
+        {
+            for(unsigned int x = 0; x < num_tiles_x; ++x)
+            {
+                // Get the tile from the input tensor
+                get_tile<T>(in, src_tile, Coordinates(x * rhs_info.n0, y * rhs_info.k0, z, 0));
+
+                if(rhs_info.transpose)
+                {
+                    // Transpose matrix
+                    transpose_matrix<T>(src_tile, src_tile_transposed);
+                }
+
+                // Store
+                const unsigned int offset_output = (y * rhs_info.k0 * rhs_info.n0 * rhs_info.h0) + ((x % rhs_info.h0) * offset_output_x) + ((x / rhs_info.h0) * out.shape()[0]) + (z * out.shape()[0] * out.shape()[1]);
+
+                for(unsigned int i = 0; i < tile_to_use->shape()[1]; ++i)
+                {
+                    const unsigned int offset_tile = i * tile_to_use->shape()[0];
+
+                    // Copy per row
+                    std::copy(&(*tile_to_use)[offset_tile], &(*tile_to_use)[offset_tile + tile_to_use->shape()[0]], &out[offset_output + i * step_output_x]);
+                }
+            }
+        }
+    }
+
+    return out;
+}
+template SimpleTensor<int> gemm_reshape_rhs_matrix(const SimpleTensor<int> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
+template SimpleTensor<short> gemm_reshape_rhs_matrix(const SimpleTensor<short> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
+template SimpleTensor<char> gemm_reshape_rhs_matrix(const SimpleTensor<char> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
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