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diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp
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index 0000000000..fcbd21fcd0
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+++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp
@@ -0,0 +1,265 @@
+/*
+ * Copyright (c) 2019 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.
+ */
+
+#pragma once
+
+#include "winograd.hpp"
+#include "padding.hpp"
+
+#define MEMBERFN(RTYPE) template <\
+  int InnerTileRows, int InnerTileCols,\
+  typename TIn, typename TOut, WinogradRoots Roots\
+> RTYPE InputTransform<InnerTileRows, InnerTileCols, TIn, TOut, Roots>
+
+
+#define Nx1MEMBERFN(RTYPE) template <\
+  int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots\
+> RTYPE InputTransform<InnerTileRows, 1, TIn, TOut, Roots>
+
+namespace winograd
+{
+
+MEMBERFN()::InputTransform(
+  const int kernel_rows,
+  const int kernel_cols,
+  const int n_batches,
+  const int n_rows,
+  const int n_cols,
+  const int n_channels,
+  const int padding_top,
+  const int padding_left,
+  const int padding_bottom,
+  const int padding_right
+) : _n_batches(n_batches), _n_rows(n_rows), _n_cols(n_cols), _n_channels(n_channels),
+    _inptr(nullptr), _outptr(nullptr),
+    _overlap_rows(kernel_rows - 1), _overlap_cols(kernel_cols - 1),
+    _padding_top(padding_top), _padding_left(padding_left), _padding_bottom(padding_bottom), _padding_right(padding_right),
+    _tiles_M(iceildiv(padding_top + n_rows + padding_bottom - kernel_rows + 1, InnerTileRows - kernel_rows + 1)),
+    _tiles_N(iceildiv(padding_left + n_cols + padding_right - kernel_cols + 1, InnerTileCols - kernel_cols + 1)),
+    _matrix_stride(0), _matrix_row_stride(0), _matrix_batch_stride(0),
+    _in_col_stride(0), _in_row_stride(0), _in_batch_stride(0),
+    _working_space_col_stride(n_channels),
+    _working_space_row_stride(InnerTileCols * _working_space_col_stride),
+    _working_space(nullptr)
+{
+}
+
+MEMBERFN(void)::set_input_tensor(const void* const inptr)
+{
+  set_input_tensor(inptr, _n_channels);
+}
+
+MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol)
+{
+  set_input_tensor(inptr, _n_cols * ldcol, ldcol);
+}
+
+MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol)
+{
+  set_input_tensor(inptr, _n_rows * ldrow, ldrow, ldcol);
+}
+
+MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol)
+{
+  _inptr = static_cast<const TIn *>(inptr);
+  _in_batch_stride = ldbatch;
+  _in_row_stride = ldrow;
+  _in_col_stride = ldcol;
+}
+
+MEMBERFN(void)::set_output_matrices(void * const mptr, const int ldmatrix, const int ldrow)
+{
+  _outptr = static_cast<TOut *>(mptr);
+  _matrix_stride = ldmatrix;
+  _matrix_row_stride = ldrow;
+  _matrix_batch_stride = _tiles_M * _tiles_N * ldrow;
+}
+
+Nx1MEMBERFN()::InputTransform(
+  const int kernel_rows,
+  const int kernel_cols,
+  const int n_batches,
+  const int n_rows,
+  const int n_cols,
+  const int n_channels,
+  const int padding_top,
+  const int padding_left,
+  const int padding_bottom,
+  const int padding_right
+) : InputTransform<1, InnerTileRows, TIn, TOut, Roots>::InputTransform(
+    /* Transpose rows and columns */
+    kernel_cols, kernel_rows, n_batches, n_cols, n_rows, n_channels,
+    padding_left, padding_top, padding_right, padding_bottom
+  )
+{
+}
+
+Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr)
+{
+  set_input_tensor(inptr, this->_n_channels);
+}
+
+Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol)
+{
+  set_input_tensor(inptr, this->_n_cols * ldcol, ldcol);
+}
+
+Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol)
+{
+  set_input_tensor(inptr, this->_n_rows * ldrow, ldrow, ldcol);
+}
+
+Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol)
+{
+  // Transpose row and column strides
+  Base::set_input_tensor(inptr, ldbatch, ldcol, ldrow);
+}
+
+MEMBERFN(size_t)::get_working_space_size(const unsigned int nthreads) const
+{
+  return sizeof(TIn) * InnerTileRows * _working_space_row_stride * nthreads;
+}
+
+MEMBERFN(void)::set_working_space(void * const buffer)
+{
+  _working_space = static_cast<TIn *>(buffer);
+}
+
+MEMBERFN(unsigned int)::get_window(void) const
+{
+  return iceildiv(_n_channels, WINDOW_BLOCK);
+}
+
+MEMBERFN(void)::run(
+  const unsigned int start,
+  const unsigned int stop,
+  const unsigned int threadid
+)
+{
+  // Determine the channels on which to work
+  if (start >= get_window())
+  {
+    return;  // No work to do beyond the end of the window
+  }
+  const unsigned int start_channel = start * WINDOW_BLOCK;
+  const unsigned int stop_channel = std::min<unsigned int>(_n_channels , stop * WINDOW_BLOCK);
+  const unsigned int n_channels = stop_channel - start_channel;
+
+  // Loop over batches
+  for (int batch = 0; batch < _n_batches; batch++)
+  {
+    const TIn* const inptr_batch = _inptr + start_channel + batch*_in_batch_stride;
+    TOut* const outptr_batch = _outptr + start_channel + batch*_matrix_batch_stride;
+
+    // Loop over rows of tiles
+    for (int tile_i = 0; tile_i < _tiles_M; tile_i++)
+    {
+      // Compute the starting and ending row of pixels within the row of tiles,
+      // hence compute the padding to apply to the top and bottom of each tile.
+      const int row_top = tile_i * (InnerTileRows - _overlap_rows) - _padding_top;
+      const int row_bottom = row_top + InnerTileRows;
+      const int row_pad_top = std::max(0, _padding_top - tile_i * (InnerTileRows - _overlap_rows));
+      const int row_pad_bottom = std::max(0, row_bottom - _n_rows);
+
+      // Get a pointer to the start of the row.
+      const int row_offset = std::min(0, row_pad_top - _padding_top);
+      const TIn* const inptr_row = inptr_batch + _in_row_stride*(row_offset + tile_i*(InnerTileRows - _overlap_rows));
+      TOut* const outptr_row = outptr_batch + tile_i*_tiles_N*_matrix_row_stride;
+
+      // Loop over tiles within the row
+      for (int tile_j = 0; tile_j < _tiles_N; tile_j++)
+      {
+        // Compute the starting and ending column of pixels within the tile,
+        // hence compute the padding to apply to the left and right of the
+        // tile.
+        const int tile_left = tile_j * (InnerTileCols - _overlap_cols) - _padding_left;
+        const int tile_right = tile_left + InnerTileCols;
+        const int tile_pad_left = std::max(0, _padding_left - tile_j * (InnerTileCols - _overlap_cols));
+        const int tile_pad_right = std::max(0, tile_right - _n_cols);
+
+        // Get a pointer to the start of the tile.
+        const int col_offset = std::min(0, tile_pad_left - _padding_left);
+        const TIn* const inptr_tile = inptr_row + _in_col_stride*(col_offset + tile_j*(InnerTileCols - _overlap_cols));
+        TOut* const outptr_tile = outptr_row + tile_j * _matrix_row_stride;
+
+        // Transform the tile, applying padding if necessary.
+        if (row_pad_top || tile_pad_left || row_pad_bottom || tile_pad_right)
+        {
+          transform_padded_tile(
+            threadid, n_channels, outptr_tile, inptr_tile,
+            row_pad_top, tile_pad_left, row_pad_bottom, tile_pad_right
+          );
+        }
+        else
+        {
+          transform_unpadded_tile(threadid, n_channels, outptr_tile, inptr_tile);
+        }
+      }
+    }
+  }
+}
+
+MEMBERFN(void)::transform_unpadded_tile(
+  const unsigned int /* threadid unused */,
+  const int n_channels,
+  TOut * const outptr,
+  const TIn * const inptr
+)
+{
+  transform_tile(
+    n_channels, inptr, _in_row_stride, _in_col_stride, outptr, _matrix_stride
+  );
+}
+
+MEMBERFN(void)::transform_padded_tile(
+  const unsigned int threadid,
+  const int n_channels,
+  TOut * const outptr,
+  const TIn * const inptr,
+  const int padding_top,
+  const int padding_left,
+  const int padding_bottom,
+  const int padding_right
+)
+{
+  padding::copy_and_pad_tile(
+    InnerTileRows, InnerTileCols, n_channels,
+    inptr, _in_row_stride, _in_col_stride,
+    static_cast<TIn *>(get_working_space(threadid)), _working_space_row_stride, _working_space_col_stride,
+    padding_top, padding_left, padding_bottom, padding_right
+  );
+
+  transform_tile(
+    n_channels, static_cast<const TIn *>(get_working_space(threadid)),
+    _working_space_row_stride, _working_space_col_stride,
+    outptr, _matrix_stride
+  );
+}
+
+MEMBERFN(void *)::get_working_space(const unsigned int threadid) const
+{
+  return _working_space + InnerTileRows * _working_space_row_stride * threadid;
+}
+
+}  // namespace winograd