COMPMID-2063: New Winograd implementation

Refactoring of winograd code reducing the size of the binaries
about 8X.

Change-Id: If8845bda324573e1a5cf436f354ac8603e88a92e
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/959
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Anthony Barbier <Anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 0 insertions, 311 deletions

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
deleted file mode 100644
index 4203945dd3..0000000000
--- a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp
+++ /dev/null
@@ -1,311 +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 Tiles = InputTransformImplTiles<3, 3, 4, 4, float>;
-
-namespace
-{
-
-
-template <bool Specialized, int PadTop=0, int PadLeft=0, int PadBottom=0, int PadRight=0>
-void winograd_input_transform_4x4_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,
-     const int _pad_top,
-     const int _pad_left,
-     const int _pad_bottom,
-     const int _pad_right
-  )
-{
-const int pad_top = Specialized ? PadTop : _pad_top;
-  const int pad_left = Specialized ? PadLeft : _pad_left;
-  const int pad_bottom = Specialized ? PadBottom : _pad_bottom;
-  const int pad_right = Specialized ? PadRight : _pad_right;
-
-  constexpr int inner_tile_i = 4, inner_tile_j = 4;
-  const int cells_i = inner_tile_i - pad_bottom;
-  const int cells_j = inner_tile_i - pad_right;
-
-
-
-  float *outptr = matrix_base;
-
-  // Get pointers into the input tile
-  const float *x_ptrs[inner_tile_i][inner_tile_j];
-  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_i][inner_tile_j];
-  float XTx[inner_tile_i][inner_tile_j];
-  float U[inner_tile_i][inner_tile_j];
-
-  for (int i = 0; i < inner_tile_i; i++)
-  {
-    for (int j = 0; j < inner_tile_j; 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_i][inner_tile_j];
-    float32x4_t XTx[inner_tile_i][inner_tile_j];
-    float32x4_t U[inner_tile_i][inner_tile_j];
-
-    for (int i = 0; i < inner_tile_i; i++)
-    {
-      for (int j = 0; j < inner_tile_j; j++)
-      {
-        x[i][j] = vdupq_n_f32(0.0f);
-        XTx[i][j] = vdupq_n_f32(0.0f);
-      }
-    }
-
-    // Load x
-    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] = x[0][j] - x[2][j];
-      XTx[0][j] = vsubq_f32(x[0][j], x[2][j]);
-
-      // XTx[1][j] = x[1][j] + x[2][j];
-      XTx[1][j] = vaddq_f32(x[1][j], x[2][j]);
-
-      // XTx[2][j] = x[2][j] - x[1][j];
-      XTx[2][j] = vsubq_f32(x[2][j], x[1][j]);
-
-      // XTx[3][j] = x[1][j] - x[3][j];
-      XTx[3][j] = vsubq_f32(x[1][j], x[3][j]);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < inner_tile_i; i++)
-    {
-      // U[i][0] = XTx[i][0] - XTx[i][2];
-      U[i][0] = vsubq_f32(XTx[i][0], XTx[i][2]);
-
-      // U[i][1] = XTx[i][1] + XTx[i][2];
-      U[i][1] = vaddq_f32(XTx[i][1], XTx[i][2]);
-
-      // U[i][2] = XTx[i][2] - XTx[i][1];
-      U[i][2] = vsubq_f32(XTx[i][2], XTx[i][1]);
-
-      // U[i][3] = XTx[i][1] - XTx[i][3];
-      U[i][3] = vsubq_f32(XTx[i][1], XTx[i][3]);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < inner_tile_i; i++)
-    {
-      for (int j = 0; j < inner_tile_j; 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_i][inner_tile_j];
-    float32x2_t XTx[inner_tile_i][inner_tile_j];
-    float32x2_t U[inner_tile_i][inner_tile_j];
-
-    for (int i = 0; i < inner_tile_i; i++)
-    {
-      for (int j = 0; j < inner_tile_j; j++)
-      {
-        x[i][j] = vdup_n_f32(0.0f);
-        XTx[i][j] = vdup_n_f32(0.0f);
-      }
-    }
-
-    // Load x
-    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] = x[0][j] - x[2][j];
-      XTx[0][j] = vsub_f32(x[0][j], x[2][j]);
-
-      // XTx[1][j] = x[1][j] + x[2][j];
-      XTx[1][j] = vadd_f32(x[1][j], x[2][j]);
-
-      // XTx[2][j] = x[2][j] - x[1][j];
-      XTx[2][j] = vsub_f32(x[2][j], x[1][j]);
-
-      // XTx[3][j] = x[1][j] - x[3][j];
-      XTx[3][j] = vsub_f32(x[1][j], x[3][j]);
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < inner_tile_i; i++)
-    {
-      // U[i][0] = XTx[i][0] - XTx[i][2];
-      U[i][0] = vsub_f32(XTx[i][0], XTx[i][2]);
-
-      // U[i][1] = XTx[i][1] + XTx[i][2];
-      U[i][1] = vadd_f32(XTx[i][1], XTx[i][2]);
-
-      // U[i][2] = XTx[i][2] - XTx[i][1];
-      U[i][2] = vsub_f32(XTx[i][2], XTx[i][1]);
-
-      // U[i][3] = XTx[i][1] - XTx[i][3];
-      U[i][3] = vsub_f32(XTx[i][1], XTx[i][3]);
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < inner_tile_i; i++)
-    {
-      for (int j = 0; j < inner_tile_j; 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] = x[0][j] - x[2][j];
-      XTx[1][j] = x[1][j] + x[2][j];
-      XTx[2][j] = x[2][j] - x[1][j];
-      XTx[3][j] = x[1][j] - x[3][j];
-    }
-
-    // Compute U = XT . x . X
-    for (int i = 0; i < inner_tile_i; i++)
-    {
-      U[i][0] = XTx[i][0] - XTx[i][2];
-      U[i][1] = XTx[i][1] + XTx[i][2];
-      U[i][2] = XTx[i][2] - XTx[i][1];
-      U[i][3] = XTx[i][1] - XTx[i][3];
-    }
-
-    // Store the transformed matrix
-    for (int i = 0, m = 0; i < inner_tile_i; i++)
-    {
-      for (int j = 0; j < inner_tile_j; j++, m++)
-      {
-        *(outptr + m*matrix_stride) = U[i][j];
-      }
-    }
-    outptr++;
-  }
-}
-
-}  // namespace (anonymous)
-
-template <>
-const Tiles::TileFn Tiles::tilefn_generic = winograd_input_transform_4x4_fp32_process_tile<false>;
-
-template <>
-const Tiles::TileFn Tiles::tilefn_unpadded = winograd_input_transform_4x4_fp32_process_tile<true>;
-
-
-template <>
-const Tiles::TileFn Tiles::tilefn_top_padded[n_pad_top] = {
-  winograd_input_transform_4x4_fp32_process_tile<true, 1, 0, 0, 0>,
-};
-
-template <>
-const Tiles::TileFn Tiles::tilefn_left_padded[n_pad_left] = {
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 1, 0, 0>,
-};
-
-template <>
-const Tiles::TileFn Tiles::tilefn_bottom_padded[n_pad_bottom] = {
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 1, 0>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 2, 0>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 3, 0>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 4, 0>,
-};
-
-template <>
-const Tiles::TileFn Tiles::tilefn_right_padded[n_pad_right] = {
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 0, 1>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 0, 2>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 0, 3>,
-  winograd_input_transform_4x4_fp32_process_tile<true, 0, 0, 0, 4>,
-};
-
-template class InputTransform<3, 3, 4, 4, float>;
-}  // namespace winograd