Reorganize the kernels into nhwc, nchw and common folders

The Following kernels have been split into nchw/nhwc kernels files:

- batchnormalization_layer
- batch_to_space
- channel_shuffle
- depth_to_space
- dequantization_layer
- im2col
- normalization_layer
- normalize_planar_yuv_layer
- normalize_planar_yuv_layer_quantized
- pooling_layer
- pooling_layer_quantized
- remap
- reorg_layer
- scale
- scale_quantized
- space_to_batch
- space_to_depth
- upsample_layer
- winograd_filter_transform
- winograd_input_transform
- winograd_output_transform

The following kernels have been moved to nchw folder:
- direct_convolution1x1
- direct_convolution3x3
- direct_convolution5x5
- direct_convolution_quantized
- prior_box_layer

The following kernels have been moved to nhwc folder:
- direct_convolution
- dwc_native_fp_nhwc
- dwc_native_quantized_nhwc

The following kernels have been removed:
- sobel_filter

While the rest kerenls have been moved to the common folder.

Partially resolves COMPMID-4453

Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: Ic327ac935687ec351c610c65a3c6357f364a5a58
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5919
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 189 deletions

diff --git a/src/core/CL/cl_kernels/l2_normalize.cl b/src/core/CL/cl_kernels/l2_normalize.cl
deleted file mode 100644
index fbe3406239..0000000000
--- a/src/core/CL/cl_kernels/l2_normalize.cl
+++ /dev/null
@@ -1,189 +0,0 @@
-/*
- * Copyright (c) 2016-2021 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 "helpers.h"
-
-#if defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X)
-/** This kernel performs l2 normalization on x-axis
- *
- * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
- * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
- *
- * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
- * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  input_step_y                         input_stride_y * number of elements along X processed per workitem(in bytes)
- * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
- * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
- * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
- * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in]  epsilon                              Epsilon value
- */
-__kernel void l2_normalize_x(
-    IMAGE_DECLARATION(input),
-    IMAGE_DECLARATION(sum),
-    IMAGE_DECLARATION(output),
-    DATA_TYPE epsilon)
-{
-    // Offset computation
-    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
-
-    // Address computation
-    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y;
-    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + get_global_id(1) * sum_stride_y;
-    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y;
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(*((__global DATA_TYPE *)sum_addr), epsilon));
-
-    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    data0 = in * normalize_value;
-
-    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
-}
-
-/** This kernel performs l2 normalization on y-axis.
- *
- * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
- * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
- *
- * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
- * @param[in]  input_step_x                         input_stride_x * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
- * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
- * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
- * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in]  epsilon                              Epsilon value
- */
-__kernel void l2_normalize_y(
-    IMAGE_DECLARATION(input),
-    IMAGE_DECLARATION(sum),
-    IMAGE_DECLARATION(output),
-    DATA_TYPE epsilon)
-{
-    // Offset computation
-    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
-
-    // Address computation
-    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y;
-    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE);
-    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y;
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr);
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(sums, epsilon));
-
-    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    data0 = in * normalize_value;
-
-    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
-}
-
-/** This kernel performs l2 normalization on z-axis.
- *
- * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
- * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
- *
- * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
- * @param[in]  input_step_x                         input_stride_x * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  input_stride_z                       Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
- * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_stride_z                         Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  sum_step_z                           sum_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
- * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
- * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  output_stride_z                      Stride of the destination tensor in Z dimension (in bytes)
- * @param[in]  output_step_z                        output_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in]  epsilon                              Epsilon value
- */
-__kernel void l2_normalize_z(
-    TENSOR3D_DECLARATION(input),
-    TENSOR3D_DECLARATION(sum),
-    TENSOR3D_DECLARATION(output),
-    DATA_TYPE epsilon)
-{
-    // Offset computation
-    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
-
-    // Address computation
-    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y + get_global_id(2) * input_stride_z;
-    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * sum_stride_y;
-    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y + get_global_id(2) * output_stride_z;
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr);
-
-    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
-    data0 = in * ((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))(rsqrt(fmax(sums, epsilon))));
-
-    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
-}
-#endif // defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X)
\ No newline at end of file