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author | Adnan AlSinan <adnan.alsinan@arm.com> | 2021-07-05 13:12:52 +0100 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2021-07-25 13:04:23 +0000 |
commit | 7075fe2c5ee6f7cfe7cfd9454d905235e70b9ac4 (patch) | |
tree | b65671bdf37eb1ef8cc30ef64ab572da795546fa /src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl | |
parent | 22f5ed51f1b01f7cf6993a556a0b763e437926fc (diff) | |
download | ComputeLibrary-7075fe2c5ee6f7cfe7cfd9454d905235e70b9ac4.tar.gz |
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>
Diffstat (limited to 'src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl')
-rw-r--r-- | src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl | 166 |
1 files changed, 0 insertions, 166 deletions
diff --git a/src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl b/src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl deleted file mode 100644 index d660fffb58..0000000000 --- a/src/core/CL/cl_kernels/normalize_planar_yuv_layer_quantized.cl +++ /dev/null @@ -1,166 +0,0 @@ -/* - * 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) - -/** Apply normalize_planar_yuv layer on tensors with NHWC 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 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 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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_nhwc(TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(dst), - VECTOR_DECLARATION(mean), - VECTOR_DECLARATION(std)) -{ - uint x_offs = max((int)(get_global_id(0) * VEC_SIZE * sizeof(DATA_TYPE) - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE * sizeof(DATA_TYPE)), 0); - - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x_offs + get_global_id(1) * src_stride_y + get_global_id(2) * src_stride_z; - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x_offs + get_global_id(1) * dst_stride_y + get_global_id(2) * dst_stride_z; - __global uchar *mean_addr = mean_ptr + mean_offset_first_element_in_bytes + x_offs; - __global uchar *std_addr = std_ptr + std_offset_first_element_in_bytes + x_offs; - - VEC_DATA_TYPE(float, VEC_SIZE) - curr_mean_flt = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)mean_addr), VEC_DATA_TYPE(float, VEC_SIZE)); - curr_mean_flt = round(curr_mean_flt - OFFSET_FLT) * SCALE_FLT; - - VEC_DATA_TYPE(float, VEC_SIZE) - curr_std_flt = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)std_addr), VEC_DATA_TYPE(float, VEC_SIZE)); - 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_addr), 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 res0 = CONVERT_SAT(round(res_flt / SCALE_FLT) + OFFSET_FLT, TYPE); - STORE_VECTOR_SELECT(res, DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); -} -#endif // defined(DATA_TYPE) && defined(VEC_SIZE) && defined(OFFSET) && defined(SCALE) |