COMPMID-1550: Winograd integrate RSH changes.

Refactors the transforms to make use of partial specialization.

Change-Id: Idff68d22817a00a7ee9eef5351a5a9fd33147540
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146635
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

5 files changed, 719 insertions, 1024 deletions

diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_6_3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_1x8_fp32.cpp
index 67e46499cd..042d4debbc 100644
--- a/src/core/NEON/kernels/convolution/winograd/transforms/input_6_3_fp32.cpp
+++ b/src/core/NEON/kernels/convolution/winograd/transforms/input_1x8_fp32.cpp
@@ -26,24 +26,11 @@
 #include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp"
 #include "arm_compute/core/NEON/kernels/convolution/common/arm.hpp"
 
-
-namespace winograd
-{
-
-using Transform = WinogradGEMM<1, 6, 1, 3>::InputTransform<float>;
-
-template <>
-template <>
-int Transform::ops_performed(const Tensor4DShape &input_shape)
+namespace
 {
-  (void) input_shape;
-  return 0;  // TODO
-}
 
-template <>
-template <>
 template <int pad_top, int pad_left, int pad_bottom, int pad_right>
-void Transform::process_tile(
+void winograd_input_transform_1x8_fp32_process_tile(
   int n_channels,
   const float* const input_base,
   const int input_row_stride,
@@ -53,23 +40,23 @@ void Transform::process_tile(
 )
 {
   (void) input_row_stride;  // No rows over which to stride
-  constexpr int inner_tile_j = 8;
-  constexpr int cells_j = inner_tile_j - pad_right;
+  constexpr int inner_tile_cols = 8;
+  constexpr int cells_j = inner_tile_cols - pad_right;
 
   float *outptr = matrix_base;
 
   // Get pointers into the input tile
-  const float *x_ptrs[inner_tile_j];
+  const float *x_ptrs[inner_tile_cols];
   for (int j = pad_left, xj = 0; j < cells_j; j++, xj++)
   {
     x_ptrs[j] = input_base + xj*input_col_stride;
   }
 
   // Vectors used/computed in this kernel.
-  float x[inner_tile_j];
-  float U[inner_tile_j];
+  float x[inner_tile_cols];
+  float U[inner_tile_cols];
 
-  for (int j = 0; j < inner_tile_j; j++)
+  for (int j = 0; j < inner_tile_cols; j++)
   {
     x[j] = 0.0f;
   }
@@ -80,7 +67,7 @@ void Transform::process_tile(
 #ifdef __arm_any__
   for (; channels_remaining >= 4; channels_remaining -= 4)
   {
-    float32x4_t x[inner_tile_j], U[inner_tile_j];
+    float32x4_t x[inner_tile_cols], U[inner_tile_cols];
     for (int j = 0; j < inner_tile_cols; j++)
     {
       x[j] = vdupq_n_f32(0.0f);
@@ -104,16 +91,15 @@ void Transform::process_tile(
     U[7] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36);
 
     // Store the transformed vector
-    for (int j = 0; j < inner_tile_j; j++)
+    for (int j = 0; j < inner_tile_cols; j++)
     {
       vst1q_f32(outptr + j*matrix_stride, U[j]);
     }
     outptr += 4;
   }
-
   for (; channels_remaining >= 2; channels_remaining -= 2)
   {
-    float32x2_t x[inner_tile_j], U[inner_tile_j];
+    float32x2_t x[inner_tile_cols], U[inner_tile_cols];
     for (int j = 0; j < inner_tile_cols; j++)
     {
       x[j] = vdup_n_f32(0.0f);
@@ -137,7 +123,7 @@ void Transform::process_tile(
     U[7] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36);
 
     // Store the transformed vector
-    for (int j = 0; j < inner_tile_j; j++)
+    for (int j = 0; j < inner_tile_cols; j++)
     {
       vst1_f32(outptr + j*matrix_stride, U[j]);
     }
@@ -163,7 +149,7 @@ void Transform::process_tile(
     U[7] = x[1]*-36 + x[5]*-14 + x[3]*49 + x[7]*1;
 
     // Store the transformed vector
-    for (int j = 0; j < inner_tile_j; j++)
+    for (int j = 0; j < inner_tile_cols; j++)
     {
       *(outptr + j*matrix_stride) = U[j];
     }
@@ -171,56 +157,118 @@ void Transform::process_tile(
   }
 }
 
+}
+
+namespace winograd
+{
+template <int x>
+using Transform = InputTransformImpl<1, x, 1, 8, float>;
+
 template <>
-template <>
-const Transform::TileFn Transform::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
+const Transform<3>::TileFn
+  Transform<3>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
 {
   {
     {
       {
-        Transform::template process_tile<0, 0, 0, 0>,
-        Transform::template process_tile<0, 0, 0, 1>,
-        Transform::template process_tile<0, 0, 0, 2>,
-        Transform::template process_tile<0, 0, 0, 3>,
-        Transform::template process_tile<0, 0, 0, 4>,
-        Transform::template process_tile<0, 0, 0, 5>,
-        Transform::template process_tile<0, 0, 0, 6>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 6>,
       }
     },
     {
       {
-        Transform::template process_tile<0, 1, 0, 0>,
-        Transform::template process_tile<0, 1, 0, 1>,
-        Transform::template process_tile<0, 1, 0, 2>,
-        Transform::template process_tile<0, 1, 0, 3>,
-        Transform::template process_tile<0, 1, 0, 4>,
-        Transform::template process_tile<0, 1, 0, 5>,
-        Transform::template process_tile<0, 1, 0, 6>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 6>,
       }
     }
   }
 };
 
-template <int x, int y>
-using TransformTransposed = typename WinogradGEMM<x, 1, y, 1>::template InputTransform<float>;
-
 template <>
-template <>
-const TransformTransposed<6, 3>::TileFn
-  TransformTransposed<6, 3>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] = {};
-
-template <>
-template <>
-const TransformTransposed<4, 5>::TileFn
-  TransformTransposed<4, 5>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] = {};
+const Transform<5>::TileFn
+  Transform<5>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
+{
+  {
+    {
+      {
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 6>,
+      }
+    },
+    {
+      {
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 2, 0, 6>,
+      }
+    }
+  }
+};
 
 template <>
-template <>
-const TransformTransposed<2, 7>::TileFn
-  TransformTransposed<2, 7>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] = {};
-
-
+const Transform<7>::TileFn
+  Transform<7>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
+{
+  {
+    {
+      {
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 0, 0, 6>,
+      }
+    },
+    {
+      {
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 1, 0, 6>,
+      }
+    },
+    {
+      {
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 0>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 1>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 2>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 3>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 4>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 5>,
+        winograd_input_transform_1x8_fp32_process_tile<0, 3, 0, 6>,
+      }
+    }
+  }
+};
 
-template struct WinogradGEMM<1, 6, 1, 3>::InputTransform<float>;
-template struct WinogradGEMM<6, 1, 3, 1>::InputTransform<float>;
+template class InputTransform<1, 3, 1, 8, float>;
+template class InputTransform<3, 1, 8, 1, float>;
+template class InputTransform<1, 5, 1, 8, float>;
+template class InputTransform<5, 1, 8, 1, float>;
+template class InputTransform<1, 7, 1, 8, float>;
+template class InputTransform<7, 1, 8, 1, float>;
 }  // namespace winograd
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp
index 97b2695d69..a9d5d52d15 100644
--- a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp
+++ b/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp
@@ -29,22 +29,7 @@
 namespace winograd
 {
 
-using Transform = WinogradGEMM<2, 2, 3, 3>::InputTransform<float>;
-
-/******************************************************************************
- * Cost methods for the input transform.
- * =====================================
- */
-template <>
-template <>
-int Transform::ops_performed(const Tensor4DShape &input_shape)
-{
-  // NOTE: Cost in FLOPs rather than instructions or uops.
-  const int tile_M = iceildiv(input_shape.n_rows, inner_tile_rows);
-  const int tile_N = iceildiv(input_shape.n_cols, inner_tile_cols);
-  return 16 * 16 * tile_M * tile_N * input_shape.n_channels;
-}
-/*****************************************************************************/
+using Transform = InputTransformImpl<3, 3, 4, 4, float>;
 
 /*****************************************************************************
 * F(2x2, 3x3) implies the use of a 4x4 input tile. Such tiles can require a
@@ -100,7 +85,6 @@ int Transform::ops_performed(const Tensor4DShape &input_shape)
 *     Padding right in {0, 1, 2}
 */
 template <>
-template <>
 template <int pad_top, int pad_left, int pad_bottom, int pad_right>
 void Transform::process_tile(
   int n_channels,
@@ -328,7 +312,6 @@ void Transform::process_tile(
 }
 
 template <>
-template <>
 const Transform::TileFn Transform::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
 {
   {
@@ -405,5 +388,5 @@ const Transform::TileFn Transform::tile_fns[n_pad_top][n_pad_left][n_pad_bottom]
   }
 };
 
-template struct WinogradGEMM<2, 2, 3, 3>::InputTransform<float>;
+template class InputTransform<3, 3, 4, 4, float>;
 }  // namespace winograd
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_5x5_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_5x5_fp32.cpp
deleted file mode 100644
index 30c9463bb8..0000000000
--- a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_5x5_fp32.cpp
+++ /dev/null
@@ -1,458 +0,0 @@
-/*
- * 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/winograd/transforms/input.hpp"
-#include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp"
-#include "arm_compute/core/NEON/kernels/convolution/common/arm.hpp"
-
-namespace winograd
-{
-
-using Transform = WinogradGEMM<2, 2, 5, 5>::InputTransform<float>;
-
-template <>
-template <>
-int Transform::ops_performed(const Tensor4DShape &input_shape)
-{
-  (void) input_shape;
-  return 0;  // TODO
-}
-
-/*****************************************************************************
-* F(2x2, 5x5) implies the use of a 6x6 input tile.
-*
-* Build an array of the specialised methods that deal with each of the
-* different padding combinations which may be required. These padding
-* constraints are the space:
-*
-*     Padding top in {0, 2}
-*     Padding left in {0, 2}
-*     Padding bottom in {0, 1, 2, 3, 4}
-*     Padding right in {0, 1, 2, 3, 4}
-*/
-template <>
-template <>
-template <int pad_top, int pad_left, int pad_bottom, int pad_right>
-void Transform::process_tile(
-  int n_channels,
-  const float* const input_base,
-  const int input_row_stride,
-  const int input_col_stride,
-  float* const matrix_base,
-  const int matrix_stride
-)
-{
-  constexpr int cells_i = 6 - pad_bottom;
-  constexpr int cells_j = 6 - pad_right;
-
-  float *outptr = matrix_base;
-
-  // Get pointers into the input tile
-  const float *x_ptrs[6][6];
-  for (int i = pad_top, xi = 0; i < cells_i; i++, xi++)
-  {
-    // Get a pointer into the row
-    const float* const row_ptr = input_base + xi*input_row_stride;
-
-    for (int j = pad_left, xj = 0; j < cells_j; j++, xj++)
-    {
-      x_ptrs[i][j] = row_ptr + xj*input_col_stride;
-    }
-  }
-
-  // Matrices used/computed in this kernel.
-  float x[6][6], XTx[6][6], U[6][6];
-  for (int i = 0; i < 6; i++)
-  {
-    for (int j = 0; j < 6; j++)
-    {
-      x[i][j] = XTx[i][j] = 0.0f;
-    }
-  }
-
-  // Perform the Winograd input transformation for each channel in the input
-  // tensor.
-  int channels_remaining = n_channels;
-#ifdef __aarch64__
-  for (; channels_remaining >= 4; channels_remaining -= 4)
-  {
-    // Matrices used/computed in this kernel
-    float32x4_t x[6][6], XTx[6][6], U[6][6];
-    for (int i = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++)
-      {
-        x[i][j] = vdupq_n_f32(0.0f);
-        XTx[i][j] = vdupq_n_f32(0.0f);
-      }
-    }
-
-    // Read a 6x6 tile in the Winograd domain
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = vld1q_f32(x_ptrs[i][j]);
-        x_ptrs[i][j] += 4;
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[0][j] = vmlsq_n_f32(vmlaq_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
-
-      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[1][j] = vmlsq_n_f32(vaddq_f32(x[3][j], x[4][j]), vaddq_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[2][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[3][j]), vsubq_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[3][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[3][j], x[1][j]), 2.0f);
-
-      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[4][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[1][j], x[3][j]), 2.0f);
-
-      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-      XTx[5][j] = vmlsq_n_f32(vmlaq_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][0] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
-
-      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][1] = vmlsq_n_f32(vaddq_f32(XTx[i][3], XTx[i][4]), vaddq_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][3]), vsubq_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][3], XTx[i][1]), 2.0f);
-
-      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][1], XTx[i][3]), 2.0f);
-
-      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-      U[i][5] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        vst1q_f32(outptr + m*matrix_stride, U[i][j]);
-      }
-    }
-    outptr += 4;
-  }
-#endif  // __aarch64__
-#ifdef __arm_any__
-  for (; channels_remaining >= 2; channels_remaining -= 2)
-  {
-    // Matrices used/computed in this kernel
-    float32x2_t x[6][6], XTx[6][6], U[6][6];
-    for (int i = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++)
-      {
-        x[i][j] = vdup_n_f32(0.0f);
-        XTx[i][j] = vdup_n_f32(0.0f);
-      }
-    }
-
-    // Read a 6x6 tile in the Winograd domain
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = vld1_f32(x_ptrs[i][j]);
-        x_ptrs[i][j] += 2;
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[0][j] = vmls_n_f32(vmla_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
-
-      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[1][j] = vmls_n_f32(vadd_f32(x[3][j], x[4][j]), vadd_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[2][j] = vmla_n_f32(vsub_f32(x[4][j], x[3][j]), vsub_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[3][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[3][j], x[1][j]), 2.0f);
-
-      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[4][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[1][j], x[3][j]), 2.0f);
-
-      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-      XTx[5][j] = vmls_n_f32(vmla_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][0] = vmls_n_f32(vmla_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
-
-      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][1] = vmls_n_f32(vadd_f32(XTx[i][3], XTx[i][4]), vadd_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][3]), vsub_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][3], XTx[i][1]), 2.0f);
-
-      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][1], XTx[i][3]), 2.0f);
-
-      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-      U[i][5] = vmls_n_f32(vmla_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        vst1_f32(outptr + m*matrix_stride, U[i][j]);
-      }
-    }
-    outptr += 2;
-  }
-#endif  // __arm_any__
-  for (; channels_remaining; channels_remaining--)
-  {
-    // Load x
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = *(x_ptrs[i][j]++);
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        *(outptr + m*matrix_stride) = U[i][j];
-      }
-    }
-    outptr++;
-  }
-}
-
-template <>
-template <>
-const Transform::TileFn Transform::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
-{
-  {
-    {
-      {
-        Transform::template process_tile<0, 0, 0, 0>,  // No padding
-        Transform::template process_tile<0, 0, 0, 1>,  // Right
-        Transform::template process_tile<0, 0, 0, 2>,  // "   "
-        Transform::template process_tile<0, 0, 0, 3>,  // "   "
-        Transform::template process_tile<0, 0, 0, 4>,  // "   "
-      },
-      {
-        Transform::template process_tile<0, 0, 1, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 1, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 1, 2>,  // "          "
-        Transform::template process_tile<0, 0, 1, 3>,  // "          "
-        Transform::template process_tile<0, 0, 1, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 2, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 2, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 2, 2>,  // "          "
-        Transform::template process_tile<0, 0, 2, 3>,  // "          "
-        Transform::template process_tile<0, 0, 2, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 3, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 3, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 3, 2>,  // "          "
-        Transform::template process_tile<0, 0, 3, 3>,  // "          "
-        Transform::template process_tile<0, 0, 3, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 4, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 4, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 4, 2>,  // "          "
-        Transform::template process_tile<0, 0, 4, 3>,  // "          "
-        Transform::template process_tile<0, 0, 4, 4>,  // "          "
-      }
-    },
-    {
-      {
-        Transform::template process_tile<0, 2, 0, 0>,  // Left
-        Transform::template process_tile<0, 2, 0, 1>,
-        Transform::template process_tile<0, 2, 0, 2>,
-        Transform::template process_tile<0, 2, 0, 3>,
-        Transform::template process_tile<0, 2, 0, 4>,
-      },
-      {
-        Transform::template process_tile<0, 2, 1, 0>,  // Bottom left
-        Transform::template process_tile<0, 2, 1, 1>,
-        Transform::template process_tile<0, 2, 1, 2>,
-        Transform::template process_tile<0, 2, 1, 3>,
-        Transform::template process_tile<0, 2, 1, 4>,
-      },
-      {
-        Transform::template process_tile<0, 2, 2, 0>,  // "          "
-        Transform::template process_tile<0, 2, 2, 1>,
-        Transform::template process_tile<0, 2, 2, 2>,
-        Transform::template process_tile<0, 2, 2, 3>,
-        Transform::template process_tile<0, 2, 2, 4>,
-      },
-      {
-        Transform::template process_tile<0, 2, 3, 0>,  // "          "
-        Transform::template process_tile<0, 2, 3, 1>,
-        Transform::template process_tile<0, 2, 3, 2>,
-        Transform::template process_tile<0, 2, 3, 3>,
-        Transform::template process_tile<0, 2, 3, 4>,
-      },
-      {
-        Transform::template process_tile<0, 2, 4, 0>,  // "          "
-        Transform::template process_tile<0, 2, 4, 1>,
-        Transform::template process_tile<0, 2, 4, 2>,
-        Transform::template process_tile<0, 2, 4, 3>,
-        Transform::template process_tile<0, 2, 4, 4>,
-      }
-    }
-  },
-  {
-    {
-      {
-        Transform::template process_tile<2, 0, 0, 0>,  // Top
-        Transform::template process_tile<2, 0, 0, 1>,  // Top right
-        Transform::template process_tile<2, 0, 0, 2>,  // "       "
-        Transform::template process_tile<2, 0, 0, 3>,  // "       "
-        Transform::template process_tile<2, 0, 0, 4>,  // "       "
-      },
-      {
-        Transform::template process_tile<2, 0, 1, 0>,
-        Transform::template process_tile<2, 0, 1, 1>,
-        Transform::template process_tile<2, 0, 1, 2>,
-        Transform::template process_tile<2, 0, 1, 3>,
-        Transform::template process_tile<2, 0, 1, 4>,
-      },
-      {
-        Transform::template process_tile<2, 0, 2, 0>,
-        Transform::template process_tile<2, 0, 2, 1>,
-        Transform::template process_tile<2, 0, 2, 2>,
-        Transform::template process_tile<2, 0, 2, 3>,
-        Transform::template process_tile<2, 0, 2, 4>,
-      },
-      {
-        Transform::template process_tile<2, 0, 3, 0>,
-        Transform::template process_tile<2, 0, 3, 1>,
-        Transform::template process_tile<2, 0, 3, 2>,
-        Transform::template process_tile<2, 0, 3, 3>,
-        Transform::template process_tile<2, 0, 3, 4>,
-      },
-      {
-        Transform::template process_tile<2, 0, 4, 0>,
-        Transform::template process_tile<2, 0, 4, 1>,
-        Transform::template process_tile<2, 0, 4, 2>,
-        Transform::template process_tile<2, 0, 4, 3>,
-        Transform::template process_tile<2, 0, 4, 4>,
-      },
-    },
-    {
-      {
-        Transform::template process_tile<2, 2, 0, 0>,  // Top left
-        Transform::template process_tile<2, 2, 0, 1>,
-        Transform::template process_tile<2, 2, 0, 2>,
-        Transform::template process_tile<2, 2, 0, 3>,
-        Transform::template process_tile<2, 2, 0, 4>,
-      },
-      {
-        Transform::template process_tile<2, 2, 1, 0>,
-        Transform::template process_tile<2, 2, 1, 1>,
-        Transform::template process_tile<2, 2, 1, 2>,
-        Transform::template process_tile<2, 2, 1, 3>,
-        Transform::template process_tile<2, 2, 1, 4>,
-      },
-      {
-        Transform::template process_tile<2, 2, 2, 0>,
-        Transform::template process_tile<2, 2, 2, 1>,
-        Transform::template process_tile<2, 2, 2, 2>,
-        Transform::template process_tile<2, 2, 2, 3>,
-        Transform::template process_tile<2, 2, 2, 4>,
-      },
-      {
-        Transform::template process_tile<2, 2, 3, 0>,
-        Transform::template process_tile<2, 2, 3, 1>,
-        Transform::template process_tile<2, 2, 3, 2>,
-        Transform::template process_tile<2, 2, 3, 3>,
-        Transform::template process_tile<2, 2, 3, 4>,
-      },
-      {
-        Transform::template process_tile<2, 2, 4, 0>,
-        Transform::template process_tile<2, 2, 4, 1>,
-        Transform::template process_tile<2, 2, 4, 2>,
-        Transform::template process_tile<2, 2, 4, 3>,
-        Transform::template process_tile<2, 2, 4, 4>,
-      }
-    }
-  }
-};
-
-template struct WinogradGEMM<2, 2, 5, 5>::InputTransform<float>;
-}  // namespace winograd
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp
deleted file mode 100644
index 7f93187132..0000000000
--- a/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp
+++ /dev/null
@@ -1,486 +0,0 @@
-/*
- * 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/winograd/transforms/input.hpp"
-#include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp"
-#include "arm_compute/core/NEON/kernels/convolution/common/arm.hpp"
-
-namespace winograd
-{
-
-using Transform = WinogradGEMM<4, 4, 3, 3>::InputTransform<float>;
-
-template <>
-template <>
-int Transform::ops_performed(const Tensor4DShape &input_shape)
-{
-  // NOTE: Cost in FLOPs rather than instructions or uops.
-  const int tile_M = iceildiv(input_shape.n_rows, inner_tile_rows);
-  const int tile_N = iceildiv(input_shape.n_cols, inner_tile_cols);
-  return 12 * 24 * tile_M * tile_N * input_shape.n_channels;
-}
-
-/* F(4x4, 3x3) implies the use of a 6x6 input tile. Such tiles can require a
-* variety of padding types. For example, tiles at the top and left of an
-* image can require one row or column of padding on their top and left sides
-* if the padding type is SAME (where X represents a padded value):
-*
-*      ___________    ___________
-*     |X X X X X X|  |X X X X X X|
-*     |X          |  |           |
-*     |X          |  |           |
-*     |X          |  |           |
-*     |X          |  |           |
-*     |X__________|  |___________|
-*      ___________
-*     |X          |
-*     |X          |
-*     |X          |
-*     |X          |
-*     |X          |
-*     |X__________|
-*
-* For tiles near the right or bottom of the image it is more complicated.
-* Such tiles might require padding by 0, 1, 2 or 3 rows or columns if the
-* padding type is VALID or 1, 2, 3 or 4 rows or columns if the padding
-* type is SAME.
-*
-* Build an array of the specialised methods that deal with each of the
-* different padding combinations which may be required. These padding
-* constraints are the space:
-*
-*     Padding top in {0, 1}
-*     Padding left in {0, 1}
-*     Padding bottom in {0, 1, 2, 3, 4}
-*     Padding right in {0, 1, 2, 3, 4}
-*/
-template <>
-template <>
-template <int pad_top, int pad_left, int pad_bottom, int pad_right>
-void Transform::process_tile(
-  int n_channels,
-  const float* const input_base,
-  const int input_row_stride,
-  const int input_col_stride,
-  float* const matrix_base,
-  const int matrix_stride
-)
-{
-  constexpr int cells_i = 6 - pad_bottom;
-  constexpr int cells_j = 6 - pad_right;
-
-  float *outptr = matrix_base;
-
-  // Get pointers into the input tile
-  const float *x_ptrs[6][6];
-  for (int i = pad_top, xi = 0; i < cells_i; i++, xi++)
-  {
-    // Get a pointer into the row
-    const float* const row_ptr = input_base + xi*input_row_stride;
-
-    for (int j = pad_left, xj = 0; j < cells_j; j++, xj++)
-    {
-      x_ptrs[i][j] = row_ptr + xj*input_col_stride;
-    }
-  }
-
-  // Matrices used/computed in this kernel.
-  float x[6][6], XTx[6][6], U[6][6];
-  for (int i = 0; i < 6; i++)
-  {
-    for (int j = 0; j < 6; j++)
-    {
-      x[i][j] = XTx[i][j] = 0.0f;
-    }
-  }
-
-  // Perform the Winograd input transformation for each channel in the input
-  // tensor.
-  int channels_remaining = n_channels;
-#ifdef __aarch64__
-  for (; channels_remaining >= 4; channels_remaining -= 4)
-  {
-    // Matrices used/computed in this kernel
-    float32x4_t x[6][6], XTx[6][6], U[6][6];
-    for (int i = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++)
-      {
-        x[i][j] = vdupq_n_f32(0.0f);
-        XTx[i][j] = vdupq_n_f32(0.0f);
-      }
-    }
-
-    // Read a 6x6 tile in the Winograd domain
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = vld1q_f32(x_ptrs[i][j]);
-        x_ptrs[i][j] += 4;
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[0][j] = vmlsq_n_f32(vmlaq_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
-
-      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[1][j] = vmlsq_n_f32(vaddq_f32(x[3][j], x[4][j]), vaddq_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[2][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[3][j]), vsubq_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[3][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[3][j], x[1][j]), 2.0f);
-
-      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[4][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[1][j], x[3][j]), 2.0f);
-
-      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-      XTx[5][j] = vmlsq_n_f32(vmlaq_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][0] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
-
-      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][1] = vmlsq_n_f32(vaddq_f32(XTx[i][3], XTx[i][4]), vaddq_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][3]), vsubq_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][3], XTx[i][1]), 2.0f);
-
-      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][1], XTx[i][3]), 2.0f);
-
-      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-      U[i][5] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        vst1q_f32(outptr + m*matrix_stride, U[i][j]);
-      }
-    }
-    outptr += 4;
-  }
-#endif  // __aarch64__
-#ifdef __arm_any__
-  for (; channels_remaining >= 2; channels_remaining -= 2)
-  {
-    // Matrices used/computed in this kernel
-    float32x2_t x[6][6], XTx[6][6], U[6][6];
-    for (int i = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++)
-      {
-        x[i][j] = vdup_n_f32(0.0f);
-        XTx[i][j] = vdup_n_f32(0.0f);
-      }
-    }
-
-    // Read a 6x6 tile in the Winograd domain
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = vld1_f32(x_ptrs[i][j]);
-        x_ptrs[i][j] += 2;
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[0][j] = vmls_n_f32(vmla_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
-
-      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[1][j] = vmls_n_f32(vadd_f32(x[3][j], x[4][j]), vadd_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[2][j] = vmla_n_f32(vsub_f32(x[4][j], x[3][j]), vsub_f32(x[1][j], x[2][j]), 4.0f);
-
-      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[3][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[3][j], x[1][j]), 2.0f);
-
-      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[4][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[1][j], x[3][j]), 2.0f);
-
-      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-      XTx[5][j] = vmls_n_f32(vmla_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][0] = vmls_n_f32(vmla_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
-
-      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][1] = vmls_n_f32(vadd_f32(XTx[i][3], XTx[i][4]), vadd_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][3]), vsub_f32(XTx[i][1], XTx[i][2]), 4.0f);
-
-      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][3], XTx[i][1]), 2.0f);
-
-      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][1], XTx[i][3]), 2.0f);
-
-      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-      U[i][5] = vmls_n_f32(vmla_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        vst1_f32(outptr + m*matrix_stride, U[i][j]);
-      }
-    }
-    outptr += 2;
-  }
-#endif  // __arm_any__
-  for (; channels_remaining; channels_remaining--)
-  {
-    // Load x
-    for (int i = pad_top; i < cells_i; i++)
-    {
-      for (int j = pad_left; j < cells_j; j++)
-      {
-        x[i][j] = *(x_ptrs[i][j]++);
-      }
-    }
-
-    // Compute XT . x
-    for (int j = pad_left; j < cells_j; j++)
-    {
-      XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
-      XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
-      XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
-      XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
-      XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
-      XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < 6; i++)
-    {
-      U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
-      U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
-      U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
-      U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
-      U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
-      U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < 6; i++)
-    {
-      for (int j = 0; j < 6; j++, m++)
-      {
-        *(outptr + m*matrix_stride) = U[i][j];
-      }
-    }
-    outptr++;
-  }
-}
-
-/* In the below, unusual or especially small tiles are routed via the slow
- * path whereas common or large tiles are routed through a faster path.
- */
-template <>
-template <>
-const Transform::TileFn Transform::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
-{
-  {
-    {
-      {
-        Transform::template process_tile<0, 0, 0, 0>,  // No padding
-        Transform::template process_tile<0, 0, 0, 1>,  // Right
-        Transform::template process_tile<0, 0, 0, 2>,  // "   "
-        Transform::template process_tile<0, 0, 0, 3>,  // "   "
-        Transform::template process_tile<0, 0, 0, 4>,  // "   "
-      },
-      {
-        Transform::template process_tile<0, 0, 1, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 1, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 1, 2>,  // "          "
-        Transform::template process_tile<0, 0, 1, 3>,  // "          "
-        Transform::template process_tile<0, 0, 1, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 2, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 2, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 2, 2>,  // "          "
-        Transform::template process_tile<0, 0, 2, 3>,  // "          "
-        Transform::template process_tile<0, 0, 2, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 3, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 3, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 3, 2>,  // "          "
-        Transform::template process_tile<0, 0, 3, 3>,  // "          "
-        Transform::template process_tile<0, 0, 3, 4>,  // "          "
-      },
-      {
-        Transform::template process_tile<0, 0, 4, 0>,  // Bottom
-        Transform::template process_tile<0, 0, 4, 1>,  // Bottom right
-        Transform::template process_tile<0, 0, 4, 2>,  // "          "
-        Transform::template process_tile<0, 0, 4, 3>,  // "          "
-        Transform::template process_tile<0, 0, 4, 4>,  // "          "
-      }
-    },
-    {
-      {
-        Transform::template process_tile<0, 1, 0, 0>,  // Left
-        Transform::template process_tile<0, 1, 0, 1>,
-        Transform::template process_tile<0, 1, 0, 2>,
-        Transform::template process_tile<0, 1, 0, 3>,
-        Transform::template process_tile<0, 1, 0, 4>,
-      },
-      {
-        Transform::template process_tile<0, 1, 1, 0>,  // Bottom left
-        Transform::template process_tile<0, 1, 1, 1>,
-        Transform::template process_tile<0, 1, 1, 2>,
-        Transform::template process_tile<0, 1, 1, 3>,
-        Transform::template process_tile<0, 1, 1, 4>,
-      },
-      {
-        Transform::template process_tile<0, 1, 2, 0>,  // "          "
-        Transform::template process_tile<0, 1, 2, 1>,
-        Transform::template process_tile<0, 1, 2, 2>,
-        Transform::template process_tile<0, 1, 2, 3>,
-        Transform::template process_tile<0, 1, 2, 4>,
-      },
-      {
-        Transform::template process_tile<0, 1, 3, 0>,  // "          "
-        Transform::template process_tile<0, 1, 3, 1>,
-        Transform::template process_tile<0, 1, 3, 2>,
-        Transform::template process_tile<0, 1, 3, 3>,
-        Transform::template process_tile<0, 1, 3, 4>,
-      },
-      {
-        Transform::template process_tile<0, 1, 4, 0>,  // "          "
-        Transform::template process_tile<0, 1, 4, 1>,
-        Transform::template process_tile<0, 1, 4, 2>,
-        Transform::template process_tile<0, 1, 4, 3>,
-        Transform::template process_tile<0, 1, 4, 4>,
-      }
-    }
-  },
-  {
-    {
-      {
-        Transform::template process_tile<1, 0, 0, 0>,  // Top
-        Transform::template process_tile<1, 0, 0, 1>,  // Top right
-        Transform::template process_tile<1, 0, 0, 2>,  // "       "
-        Transform::template process_tile<1, 0, 0, 3>,  // "       "
-        Transform::template process_tile<1, 0, 0, 4>,  // "       "
-      },
-      {
-        Transform::template process_tile<1, 0, 1, 0>,
-        Transform::template process_tile<1, 0, 1, 1>,
-        Transform::template process_tile<1, 0, 1, 2>,
-        Transform::template process_tile<1, 0, 1, 3>,
-        Transform::template process_tile<1, 0, 1, 4>,
-      },
-      {
-        Transform::template process_tile<1, 0, 2, 0>,
-        Transform::template process_tile<1, 0, 2, 1>,
-        Transform::template process_tile<1, 0, 2, 2>,
-        Transform::template process_tile<1, 0, 2, 3>,
-        Transform::template process_tile<1, 0, 2, 4>,
-      },
-      {
-        Transform::template process_tile<1, 0, 3, 0>,
-        Transform::template process_tile<1, 0, 3, 1>,
-        Transform::template process_tile<1, 0, 3, 2>,
-        Transform::template process_tile<1, 0, 3, 3>,
-        Transform::template process_tile<1, 0, 3, 4>,
-      },
-      {
-        Transform::template process_tile<1, 0, 4, 0>,
-        Transform::template process_tile<1, 0, 4, 1>,
-        Transform::template process_tile<1, 0, 4, 2>,
-        Transform::template process_tile<1, 0, 4, 3>,
-        Transform::template process_tile<1, 0, 4, 4>,
-      },
-    },
-    {
-      {
-        Transform::template process_tile<1, 1, 0, 0>,  // Top left
-        Transform::template process_tile<1, 1, 0, 1>,
-        Transform::template process_tile<1, 1, 0, 2>,
-        Transform::template process_tile<1, 1, 0, 3>,
-        Transform::template process_tile<1, 1, 0, 4>,
-      },
-      {
-        Transform::template process_tile<1, 1, 1, 0>,
-        Transform::template process_tile<1, 1, 1, 1>,
-        Transform::template process_tile<1, 1, 1, 2>,
-        Transform::template process_tile<1, 1, 1, 3>,
-        Transform::template process_tile<1, 1, 1, 4>,
-      },
-      {
-        Transform::template process_tile<1, 1, 2, 0>,
-        Transform::template process_tile<1, 1, 2, 1>,
-        Transform::template process_tile<1, 1, 2, 2>,
-        Transform::template process_tile<1, 1, 2, 3>,
-        Transform::template process_tile<1, 1, 2, 4>,
-      },
-      {
-        Transform::template process_tile<1, 1, 3, 0>,
-        Transform::template process_tile<1, 1, 3, 1>,
-        Transform::template process_tile<1, 1, 3, 2>,
-        Transform::template process_tile<1, 1, 3, 3>,
-        Transform::template process_tile<1, 1, 3, 4>,
-      },
-      {
-        Transform::template process_tile<1, 1, 4, 0>,
-        Transform::template process_tile<1, 1, 4, 1>,
-        Transform::template process_tile<1, 1, 4, 2>,
-        Transform::template process_tile<1, 1, 4, 3>,
-        Transform::template process_tile<1, 1, 4, 4>,
-      }
-    }
-  }
-};
-
-template struct WinogradGEMM<4, 4, 3, 3>::InputTransform<float>;
-}  // namespace winograd
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_6x6_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_6x6_fp32.cpp
new file mode 100644
index 0000000000..908613068a
--- /dev/null
+++ b/src/core/NEON/kernels/convolution/winograd/transforms/input_6x6_fp32.cpp
@@ -0,0 +1,608 @@
+/*
+ * 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/winograd/transforms/input.hpp"
+#include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp"
+#include "arm_compute/core/NEON/kernels/convolution/common/arm.hpp"
+
+namespace
+{
+
+template <int pad_top, int pad_left, int pad_bottom, int pad_right>
+void winograd_input_transform_6x6_fp32_process_tile(
+  int n_channels,
+  const float* const input_base,
+  const int input_row_stride,
+  const int input_col_stride,
+  float* const matrix_base,
+  const int matrix_stride
+)
+{
+  constexpr int inner_tile_rows = 6;
+  constexpr int inner_tile_cols = 6;
+  constexpr int cells_i = inner_tile_rows - pad_bottom;
+  constexpr int cells_j = inner_tile_cols - pad_right;
+
+  float *outptr = matrix_base;
+
+  // Get pointers into the input tile
+  const float *x_ptrs[inner_tile_rows][inner_tile_cols];
+  for (int i = pad_top, xi = 0; i < cells_i; i++, xi++)
+  {
+    // Get a pointer into the row
+    const float* const row_ptr = input_base + xi*input_row_stride;
+
+    for (int j = pad_left, xj = 0; j < cells_j; j++, xj++)
+    {
+      x_ptrs[i][j] = row_ptr + xj*input_col_stride;
+    }
+  }
+
+  // Matrices used/computed in this kernel.
+  float x[inner_tile_rows][inner_tile_cols];
+  float XTx[inner_tile_rows][inner_tile_cols];
+  float U[inner_tile_rows][inner_tile_cols];
+  for (int i = 0; i < inner_tile_rows; i++)
+  {
+    for (int j = 0; j < inner_tile_cols; j++)
+    {
+      x[i][j] = XTx[i][j] = 0.0f;
+    }
+  }
+
+  // Perform the Winograd input transformation for each channel in the input
+  // tensor.
+  int channels_remaining = n_channels;
+#ifdef __aarch64__
+  for (; channels_remaining >= 4; channels_remaining -= 4)
+  {
+    // Matrices used/computed in this kernel
+    float32x4_t x[inner_tile_rows][inner_tile_cols];
+    float32x4_t XTx[inner_tile_rows][inner_tile_cols];
+    float32x4_t U[inner_tile_rows][inner_tile_cols];
+    for (int i = 0; i < inner_tile_rows; i++)
+    {
+      for (int j = 0; j < inner_tile_cols; j++)
+      {
+        x[i][j] = vdupq_n_f32(0.0f);
+        XTx[i][j] = vdupq_n_f32(0.0f);
+      }
+    }
+
+    // Read a 6x6 tile in the Winograd domain
+    for (int i = pad_top; i < cells_i; i++)
+    {
+      for (int j = pad_left; j < cells_j; j++)
+      {
+        x[i][j] = vld1q_f32(x_ptrs[i][j]);
+        x_ptrs[i][j] += 4;
+      }
+    }
+
+    // Compute XT . x
+    for (int j = pad_left; j < cells_j; j++)
+    {
+      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
+      XTx[0][j] = vmlsq_n_f32(vmlaq_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
+
+      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
+      XTx[1][j] = vmlsq_n_f32(vaddq_f32(x[3][j], x[4][j]), vaddq_f32(x[1][j], x[2][j]), 4.0f);
+
+      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
+      XTx[2][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[3][j]), vsubq_f32(x[1][j], x[2][j]), 4.0f);
+
+      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
+      XTx[3][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[3][j], x[1][j]), 2.0f);
+
+      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
+      XTx[4][j] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_f32(x[1][j], x[3][j]), 2.0f);
+
+      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
+      XTx[5][j] = vmlsq_n_f32(vmlaq_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
+    }
+
+    // Compute U = XT . x . X
+    for (int i = 0; i < inner_tile_rows; i++)
+    {
+      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
+      U[i][0] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
+
+      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
+      U[i][1] = vmlsq_n_f32(vaddq_f32(XTx[i][3], XTx[i][4]), vaddq_f32(XTx[i][1], XTx[i][2]), 4.0f);
+
+      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
+      U[i][2] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][3]), vsubq_f32(XTx[i][1], XTx[i][2]), 4.0f);
+
+      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
+      U[i][3] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][3], XTx[i][1]), 2.0f);
+
+      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
+      U[i][4] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_f32(XTx[i][1], XTx[i][3]), 2.0f);
+
+      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
+      U[i][5] = vmlsq_n_f32(vmlaq_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
+    }
+
+    // Store the transformed matrix
+    for (int i = 0, m = 0; i < inner_tile_rows; i++)
+    {
+      for (int j = 0; j < inner_tile_cols; j++, m++)
+      {
+        vst1q_f32(outptr + m*matrix_stride, U[i][j]);
+      }
+    }
+    outptr += 4;
+  }
+#endif  // __aarch64__
+#ifdef __arm_any__
+  for (; channels_remaining >= 2; channels_remaining -= 2)
+  {
+    // Matrices used/computed in this kernel
+    float32x2_t x[inner_tile_rows][inner_tile_cols];
+    float32x2_t XTx[inner_tile_rows][inner_tile_cols];
+    float32x2_t U[inner_tile_rows][inner_tile_cols];
+    for (int i = 0; i < inner_tile_rows; i++)
+    {
+      for (int j = 0; j < inner_tile_cols; j++)
+      {
+        x[i][j] = vdup_n_f32(0.0f);
+        XTx[i][j] = vdup_n_f32(0.0f);
+      }
+    }
+
+    // Read a 6x6 tile in the Winograd domain
+    for (int i = pad_top; i < cells_i; i++)
+    {
+      for (int j = pad_left; j < cells_j; j++)
+      {
+        x[i][j] = vld1_f32(x_ptrs[i][j]);
+        x_ptrs[i][j] += 2;
+      }
+    }
+
+    // Compute XT . x
+    for (int j = pad_left; j < cells_j; j++)
+    {
+      // XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
+      XTx[0][j] = vmls_n_f32(vmla_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f);
+
+      // XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
+      XTx[1][j] = vmls_n_f32(vadd_f32(x[3][j], x[4][j]), vadd_f32(x[1][j], x[2][j]), 4.0f);
+
+      // XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
+      XTx[2][j] = vmla_n_f32(vsub_f32(x[4][j], x[3][j]), vsub_f32(x[1][j], x[2][j]), 4.0f);
+
+      // XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
+      XTx[3][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[3][j], x[1][j]), 2.0f);
+
+      // XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
+      XTx[4][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[1][j], x[3][j]), 2.0f);
+
+      // XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
+      XTx[5][j] = vmls_n_f32(vmla_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f);
+    }
+
+    // Compute U = XT . x . X
+    for (int i = 0; i < inner_tile_rows; i++)
+    {
+      // U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
+      U[i][0] = vmls_n_f32(vmla_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f);
+
+      // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
+      U[i][1] = vmls_n_f32(vadd_f32(XTx[i][3], XTx[i][4]), vadd_f32(XTx[i][1], XTx[i][2]), 4.0f);
+
+      // U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
+      U[i][2] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][3]), vsub_f32(XTx[i][1], XTx[i][2]), 4.0f);
+
+      // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
+      U[i][3] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][3], XTx[i][1]), 2.0f);
+
+      // U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
+      U[i][4] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][1], XTx[i][3]), 2.0f);
+
+      // U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
+      U[i][5] = vmls_n_f32(vmla_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f);
+    }
+
+    // Store the transformed matrix
+    for (int i = 0, m = 0; i < inner_tile_rows; i++)
+    {
+      for (int j = 0; j < inner_tile_cols; j++, m++)
+      {
+        vst1_f32(outptr + m*matrix_stride, U[i][j]);
+      }
+    }
+    outptr += 2;
+  }
+#endif  // __arm_any__
+  for (; channels_remaining; channels_remaining--)
+  {
+    // Load x
+    for (int i = pad_top; i < cells_i; i++)
+    {
+      for (int j = pad_left; j < cells_j; j++)
+      {
+        x[i][j] = *(x_ptrs[i][j]++);
+      }
+    }
+
+    // Compute XT . x
+    for (int j = pad_left; j < cells_j; j++)
+    {
+      XTx[0][j] =  4*x[0][j] + -5*x[2][j] +  1*x[4][j];
+      XTx[1][j] = -4*x[1][j] + -4*x[2][j] +  1*x[3][j] +  1*x[4][j];
+      XTx[2][j] =  4*x[1][j] + -4*x[2][j] + -1*x[3][j] +  1*x[4][j];
+      XTx[3][j] = -2*x[1][j] + -1*x[2][j] +  2*x[3][j] +  1*x[4][j];
+      XTx[4][j] =  2*x[1][j] + -1*x[2][j] + -2*x[3][j] +  1*x[4][j];
+      XTx[5][j] =  4*x[1][j] + -5*x[3][j] +  1*x[5][j];
+    }
+
+    // Compute U = XT . x . X
+    for (int i = 0; i < inner_tile_rows; i++)
+    {
+      U[i][0] =  4*XTx[i][0] + -5*XTx[i][2] +  1*XTx[i][4];
+      U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] +  1*XTx[i][3] +  1*XTx[i][4];
+      U[i][2] =  4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] +  1*XTx[i][4];
+      U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] +  2*XTx[i][3] +  1*XTx[i][4];
+      U[i][4] =  2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] +  1*XTx[i][4];
+      U[i][5] =  4*XTx[i][1] + -5*XTx[i][3] +  1*XTx[i][5];
+    }
+
+    // Store the transformed matrix
+    for (int i = 0, m = 0; i < inner_tile_rows; i++)
+    {
+      for (int j = 0; j < inner_tile_cols; j++, m++)
+      {
+        *(outptr + m*matrix_stride) = U[i][j];
+      }
+    }
+    outptr++;
+  }
+}
+}
+
+namespace winograd
+{
+template <int k>
+using Transform = InputTransformImpl<k, k, 6, 6, float>;
+
+template <>
+const Transform<3>::TileFn
+  Transform<3>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
+{
+  {
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 0>,  // No padding
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 1>,  // Right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 2>,  // "   "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 3>,  // "   "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 4>,  // "   "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 4>,  // "          "
+      }
+    },
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 0, 0>,  // Left
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 0, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 0, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 0, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 0, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 1, 0>,  // Bottom left
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 2, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 3, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 4, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 1, 4, 4>,
+      }
+    }
+  },
+  {
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 0, 0>,  // Top
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 0, 1>,  // Top right
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 0, 2>,  // "       "
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 0, 3>,  // "       "
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 0, 4>,  // "       "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 1, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 2, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 3, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 4, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 0, 4, 4>,
+      },
+    },
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 0, 0>,  // Top left
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 0, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 0, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 0, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 0, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 1, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 2, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 3, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 4, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<1, 1, 4, 4>,
+      }
+    }
+  }
+};
+
+template <>
+const Transform<5>::TileFn
+  Transform<5>::tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right] =
+{
+  {
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 0>,  // No padding
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 1>,  // Right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 2>,  // "   "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 3>,  // "   "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 0, 4>,  // "   "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 1, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 2, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 3, 4>,  // "          "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 0>,  // Bottom
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 1>,  // Bottom right
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 2>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 3>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 0, 4, 4>,  // "          "
+      }
+    },
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 0, 0>,  // Left
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 0, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 0, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 0, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 0, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 1, 0>,  // Bottom left
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 2, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 3, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 4, 0>,  // "          "
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<0, 2, 4, 4>,
+      }
+    }
+  },
+  {
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 0, 0>,  // Top
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 0, 1>,  // Top right
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 0, 2>,  // "       "
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 0, 3>,  // "       "
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 0, 4>,  // "       "
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 1, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 2, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 3, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 4, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 0, 4, 4>,
+      },
+    },
+    {
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 0, 0>,  // Top left
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 0, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 0, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 0, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 0, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 1, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 1, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 1, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 1, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 1, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 2, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 2, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 2, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 2, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 2, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 3, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 3, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 3, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 3, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 3, 4>,
+      },
+      {
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 4, 0>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 4, 1>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 4, 2>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 4, 3>,
+        winograd_input_transform_6x6_fp32_process_tile<2, 2, 4, 4>,
+      }
+    }
+  }
+};
+
+template class InputTransform<3, 3, 6, 6, float>;
+template class InputTransform<5, 5, 6, 6, float>;
+}