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, 101 insertions, 0 deletions

diff --git a/src/core/CL/cl_kernels/nchw/normalize_planar_yuv_layer_quantized.cl b/src/core/CL/cl_kernels/nchw/normalize_planar_yuv_layer_quantized.cl
new file mode 100644
index 0000000000..0f02ef6184
--- /dev/null
+++ b/src/core/CL/cl_kernels/nchw/normalize_planar_yuv_layer_quantized.cl
@@ -0,0 +1,101 @@
+/*
+ * Copyright (c) 2018-2021 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(DATA_TYPE) && defined(VEC_SIZE) && defined(OFFSET) && defined(SCALE)
+
+#define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+#define OFFSET_FLT ((float)OFFSET)
+#define SCALE_FLT ((float)SCALE)
+
+#if defined(NUM_CHANNELS)
+
+/** Apply normalize_planar_yuv layer on tensors with NCHW data layout.
+ *
+ * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8
+ * @note The depth of the input tensor should be given as a preprocessor argument using -DNUM_CHANNELS e.g. -DNUM_CHANNELS=8
+ * @note The quantization offset should be given as a preprocessor argument using -DOFFSET e.g. -DOFFSET=8
+ * @note The quantization scale should be given as a preprocessor argument using -DSCALE e.g. -DSCALE=8
+ *
+ * @param[in]  src_ptr                            Pointer to the first source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
+ * @param[in]  src_stride_x                       Stride of the first source tensor in X dimension (in bytes)
+ * @param[in]  src_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  src_stride_y                       Stride of the first source tensor in Y dimension (in bytes)
+ * @param[in]  src_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  src_stride_z                       Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in]  src_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  src_offset_first_element_in_bytes  The offset of the first element in the first source tensor
+ * @param[out] dst_ptr                            Pointer to the destination tensor. Supported data types: same as @p src_ptr
+ * @param[in]  dst_stride_x                       Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  dst_step_x                         output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  dst_stride_y                       Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in]  dst_step_y                         output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  dst_stride_z                       Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in]  dst_step_z                         output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  dst_offset_first_element_in_bytes  The offset of the first element in the destination tensor
+ * @param[in]  mean_ptr                           Pointer to the mean source tensor. Supported data types: same as @p src_ptr
+ * @param[in]  mean_stride_x                      Stride of the mean source tensor in X dimension (in bytes)
+ * @param[in]  mean_step_x                        mean_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor
+ * @param[in]  std_ptr                            Pointer to the std tensor. Supported data types: same as @p src_ptr
+ * @param[in]  std_stride_x                       Stride of the std tensor in X dimension (in bytes)
+ * @param[in]  std_step_x                         std_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  std_offset_first_element_in_bytes  The offset of the first element in the var source tensor
+ */
+__kernel void normalize_planar_yuv_layer_q8_nchw(TENSOR3D_DECLARATION(src),
+                                                 TENSOR3D_DECLARATION(dst),
+                                                 VECTOR_DECLARATION(mean),
+                                                 VECTOR_DECLARATION(std))
+{
+    Tensor3D src  = CONVERT_TO_TENSOR3D_STRUCT(src);
+    Tensor3D dst  = CONVERT_TO_TENSOR3D_STRUCT(dst);
+    Vector   mean = CONVERT_TO_VECTOR_STRUCT(mean);
+    Vector   std  = CONVERT_TO_VECTOR_STRUCT(std);
+
+    const uint current_slice = get_global_id(2) % NUM_CHANNELS;
+
+    VEC_DATA_TYPE(float, VEC_SIZE)
+    curr_mean_flt = (VEC_DATA_TYPE(float, VEC_SIZE))(*((__global DATA_TYPE *)(mean.ptr + current_slice * sizeof(DATA_TYPE))));
+    curr_mean_flt = round(curr_mean_flt - OFFSET_FLT) * SCALE_FLT;
+
+    VEC_DATA_TYPE(float, VEC_SIZE)
+    curr_std_flt = (VEC_DATA_TYPE(float, VEC_SIZE))(*((__global DATA_TYPE *)(std.ptr + current_slice * sizeof(DATA_TYPE))));
+    curr_std_flt = round(curr_std_flt - OFFSET_FLT) * SCALE_FLT;
+
+    VEC_DATA_TYPE(float, VEC_SIZE)
+    data_flt = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr), VEC_DATA_TYPE(float, VEC_SIZE));
+    data_flt = round(data_flt - OFFSET_FLT) * SCALE_FLT;
+
+    // Perform normalization
+    VEC_DATA_TYPE(float, VEC_SIZE)
+    res_flt = (data_flt - curr_mean_flt) / curr_std_flt;
+
+    const TYPE res_u8 = CONVERT_SAT(round(res_flt / SCALE_FLT) + OFFSET_FLT, TYPE);
+    VSTORE(VEC_SIZE)
+    (res_u8, 0, (__global DATA_TYPE *)dst.ptr);
+}
+
+#endif // defined(NUM_CHANNELS)
+#endif // defined(DATA_TYPE) && defined(VEC_SIZE) && defined(OFFSET) && defined(SCALE)
\ No newline at end of file