1 files changed, 125 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/weights_6_3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/weights_6_3_fp32.cpp
new file mode 100644
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+++ b/src/core/NEON/kernels/convolution/winograd/transforms/weights_6_3_fp32.cpp
@@ -0,0 +1,125 @@
+/*
+ * 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 "arm_compute/core/NEON/kernels/convolution/common/arm.hpp"
+#include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp"
+#include "arm_compute/core/NEON/kernels/convolution/winograd/transforms/kernel.hpp"
+
+
+namespace winograd
+{
+  template <>
+  template <>
+  void WinogradGEMM<1, 6, 1, 3>::WeightsTransform<float>::execute(
+    const int n_output_channels,
+    const int n_input_channels,
+    const float* const input,  // NOTE: Data in HWIO order
+    float* const output,
+    const int matrix_stride,
+    const int matrix_row_stride
+  )
+  {
+    // Get pointers to each cell of the weight tensor
+    const auto weight_col_stride = n_input_channels * n_output_channels;
+    const float *inptrs[3];
+    for (int j = 0; j < 3; j++)
+    {
+      inptrs[j] = input + j*weight_col_stride;
+    }
+
+    // For each input channel
+    for (int ic = 0; ic < n_input_channels; ic++)
+    {
+      float *outptr = output + ic * matrix_row_stride;
+
+      // For each output channel
+      int channels_remaining = n_output_channels;
+      for (; channels_remaining; channels_remaining--)
+      {
+        // Matrices used and computed in this kernel
+        float w[3], V[inner_tile_cols];
+
+        // Read weights
+        for (int j = 0; j < 3; j++)
+        {
+          w[j] = *(inptrs[j]++);
+        }
+
+        // Compute V = w WT
+        V[0] = (w[0]*-1) / 36.0f;
+        V[1] = (w[1]*-1 + w[0]*1 + w[2]*1) / 48.0f;
+        V[2] = (w[0]*1 + w[1]*1 + w[2]*1) / 48.0f;
+        V[3] = (w[0]*-1 + w[2]*-4 + w[1]*2) / 120.0f;
+        V[4] = (w[0]*-1 + w[2]*-4 + w[1]*-2) / 120.0f;
+        V[5] = (w[1]*-3 + w[2]*9 + w[0]*1) / 720.0f;
+        V[6] = (w[1]*3 + w[2]*9 + w[0]*1) / 720.0f;
+        V[7] = (w[2]*1) / 1;
+
+        // Store the transformed weights
+        for (int j = 0; j < inner_tile_cols; j++)
+        {
+          *(outptr + j*matrix_stride) = V[j];
+        }
+        outptr++;
+      }
+    }
+  }
+
+  template <>
+  template <>
+  int WinogradGEMM<1, 6, 1, 3>::WeightsTransform<float>::ops_performed(const KernelShape &shape)
+  {
+    (void) shape;
+    return 0;  // TODO
+  }
+
+  template <>
+  template <>
+  void WinogradGEMM<6, 1, 3, 1>::WeightsTransform<float>::execute(
+    const int n_output_channels,
+    const int n_input_channels,
+    const float* const input,  // NOTE: Data in HWIO order
+    float* const output,
+    const int matrix_stride,
+    const int matrix_row_stride
+  )
+  {
+    // Redirect to the 1xN implementation
+    WinogradGEMM<1, 6, 1, 3>::template WeightsTransform<float>::execute(
+      n_output_channels, n_input_channels, input, output, matrix_stride,
+      matrix_row_stride
+    );
+  }
+
+  template <>
+  template <>
+  int WinogradGEMM<6, 1, 3, 1>::WeightsTransform<float>::ops_performed(const KernelShape &shape)
+  {
+    (void) shape;
+    return 0;  // TODO
+  }
+
+  template struct WinogradGEMM<1, 6, 1, 3>::WeightsTransform<float>;
+  template struct WinogradGEMM<6, 1, 3, 1>::WeightsTransform<float>;
+}