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Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp')
-rw-r--r--src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp220
1 files changed, 0 insertions, 220 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp
deleted file mode 100644
index 3fde4a7a6b..0000000000
--- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp
+++ /dev/null
@@ -1,220 +0,0 @@
-/*
- * 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.
- */
-
-#include "arm.hpp"
-#include "kernel.hpp"
-
-namespace winograd
-{
-
-template <>
-void WeightTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>::execute(
- const int n_output_channels,
- const int n_input_channels,
- const float* const input,
- float* const output,
- const int matrix_stride,
- const int matrix_row_stride
-)
-{
- constexpr int inner_tile_i = 4;
- constexpr int inner_tile_j = 4;
-
- // Get pointers to each cell of the weight tensor
- const auto weight_col_stride = n_input_channels * n_output_channels;
- const auto weight_row_stride = 3 * weight_col_stride;
- const float *inptrs[3][3];
- for (int i = 0; i < 3; i++)
- {
- for (int j = 0; j < 3; j++)
- {
- inptrs[i][j] = input + i*weight_row_stride + j*weight_col_stride;
- }
- }
-
- // For each input channel
- for (int ic = 0; ic < n_input_channels; ic++)
- {
- float *outptr = output + ic * matrix_row_stride;
-
- // For each output channel
- int channels_remaining = n_output_channels;
-#ifdef __aarch64__
- for (; channels_remaining >= 4; channels_remaining -= 4)
- {
- // Matrices used and computed in this kernel
- float32x4_t w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j];
-
- // Read weights
- for (int i = 0; i < 3; i++)
- {
- for (int j = 0; j < 3; j++)
- {
- w[i][j] = vld1q_f32(inptrs[i][j]);
- inptrs[i][j] += 4;
- }
- }
-
- // Compute the matrix W w
- for (int j = 0; j < 3; j++)
- {
- Ww[0][j] = w[0][j];
-
- // Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]);
- Ww[1][j] = vmulq_n_f32(vaddq_f32(vaddq_f32(w[0][j], w[1][j]), w[2][j]), 0.5f);
-
- // Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]);
- Ww[2][j] = vmulq_n_f32(vaddq_f32(vsubq_f32(w[0][j], w[1][j]), w[2][j]), 0.5f);
-
- Ww[3][j] = w[2][j];
- }
-
- // Compute V = W w WT
- for (int i = 0; i < inner_tile_i; i++)
- {
- V[i][0] = Ww[i][0];
-
- // V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]);
- V[i][1] = vmulq_n_f32(vaddq_f32(vaddq_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f);
-
- // V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]);
- V[i][2] = vmulq_n_f32(vaddq_f32(vsubq_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f);
-
- V[i][3] = Ww[i][2];
- }
-
- // Store the transformed weights
- 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, V[i][j]);
- }
- }
- outptr += 4;
- }
-#endif // __aarch64__
-#ifdef __arm_any__
- for (; channels_remaining >= 2; channels_remaining -= 2)
- {
- // Matrices used and computed in this kernel
- float32x2_t w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j];
-
- // Read weights
- for (int i = 0; i < 3; i++)
- {
- for (int j = 0; j < 3; j++)
- {
- w[i][j] = vld1_f32(inptrs[i][j]);
- inptrs[i][j] += 2;
- }
- }
-
- // Compute the matrix W w
- for (int j = 0; j < 3; j++)
- {
- Ww[0][j] = w[0][j];
-
- // Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]);
- Ww[1][j] = vmul_n_f32(vadd_f32(vadd_f32(w[0][j], w[1][j]), w[2][j]), 0.5f);
-
- // Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]);
- Ww[2][j] = vmul_n_f32(vadd_f32(vsub_f32(w[0][j], w[1][j]), w[2][j]), 0.5f);
-
- Ww[3][j] = w[2][j];
- }
-
- // Compute V = W w WT
- for (int i = 0; i < inner_tile_i; i++)
- {
- V[i][0] = Ww[i][0];
-
- // V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]);
- V[i][1] = vmul_n_f32(vadd_f32(vadd_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f);
-
- // V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]);
- V[i][2] = vmul_n_f32(vadd_f32(vsub_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f);
-
- V[i][3] = Ww[i][2];
- }
-
- // Store the transformed weights
- 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, V[i][j]);
- }
- }
- outptr += 2;
- }
-#endif // __arm_any__
- for (; channels_remaining; channels_remaining--)
- {
- // Matrices used and computed in this kernel
- float w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j];
-
- // Read weights
- for (int i = 0; i < 3; i++)
- {
- for (int j = 0; j < 3; j++)
- {
- w[i][j] = *(inptrs[i][j]++);
- }
- }
-
- // Compute the matrix W w
- for (int j = 0; j < 3; j++)
- {
- Ww[0][j] = w[0][j];
- Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]);
- Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]);
- Ww[3][j] = w[2][j];
- }
-
- // Compute V = W w WT
- for (int i = 0; i < inner_tile_i; i++)
- {
- V[i][0] = Ww[i][0];
- V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]);
- V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]);
- V[i][3] = Ww[i][2];
- }
-
- // Store the transformed weights
- 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) = V[i][j];
- }
- }
- outptr++;
- }
- }
-}
-
-template class WeightTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>;
-
-} // namespace
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 23:22:19 +0000