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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/nhwc/scale.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/nhwc/scale.cl')
-rw-r--r-- | src/core/CL/cl_kernels/nhwc/scale.cl | 174 |
1 files changed, 174 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nhwc/scale.cl b/src/core/CL/cl_kernels/nhwc/scale.cl new file mode 100644 index 0000000000..1ea5e73df1 --- /dev/null +++ b/src/core/CL/cl_kernels/nhwc/scale.cl @@ -0,0 +1,174 @@ +/* + * 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" +#include "warp_helpers.h" + +#if defined(DEPTH_OUT) +/** Performs scale on an image interpolating with the NEAREAST NEIGHBOUR method. Input and output are single channel F32. (NHWC) + * + * @note Sampling policy to used is passed as -DSAMPLING_POLICY_(TYPE) e.g. -DSAMPLING_POLICY_TOP_LEFT + * @note Output tensor's depth should be given as a preprocessor argument using -DDEPTH_OUT=size. e.g. -DDEPTH=16 + * + * @param[in] in_ptr Pointer to the source image. Supported data types: U8/S16/F16/F32. + * @param[in] in_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] in_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] in_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in_stride_z Stride of the source image in Z dimension (in bytes) + * @param[in] in_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in_offset_first_element_in_bytes The offset of the first element in the source image + * @param[out] out_ptr Pointer to the destination image. Supported data types: same as @p in_ptr + * @param[in] out_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] out_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] out_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the destination image in Z dimension (in bytes) + * @param[in] out_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination image + * @param[in] input_width Input image width + * @param[in] input_height Input image height + * @param[in] scale_x The scale factor along x dimension + * @param[in] scale_y The scale factor along y dimension + */ +__kernel void scale_nearest_neighbour_nhwc( + TENSOR4D_DECLARATION(in), + TENSOR4D_DECLARATION(out), + const float input_width, + const float input_height, + const float scale_x, + const float scale_y) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(in, 0); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(out, DEPTH_OUT); + +#ifdef SAMPLING_POLICY_TOP_LEFT + float new_x = get_global_id(1) * scale_x; + float new_y = (get_global_id(2) % DEPTH_OUT) * scale_y; +#elif SAMPLING_POLICY_CENTER + float new_x = (get_global_id(1) + 0.5f) * scale_x; + float new_y = ((get_global_id(2) % DEPTH_OUT) + 0.5f) * scale_y; +#else /* SAMPLING_POLICY */ +#error("Unsupported sampling policy"); +#endif /* SAMPLING_POLICY */ +#ifdef ALIGN_CORNERS + new_x = round(new_x); + new_y = round(new_y); +#endif /* ALIGN_CORNERS */ + const float clamped_x = clamp(new_x, 0.0f, input_width - 1); + const float clamped_y = clamp(new_y, 0.0f, input_height - 1); + + *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x), convert_int(clamped_y), (get_global_id(2) / DEPTH_OUT))); +} + +/** Performs scale on an image interpolating with the BILINEAR method. (NHWC) + * + * @note Sampling policy to be used is passed as -DSAMPLING_POLICY_(TYPE) e.g. -DSAMPLING_POLICY_TOP_LEFT + * @note If border mode replicate is used, is should be passed as -DBORDER_MODE_REPLICATE + * @note Output tensor's depth should be given as a preprocessor argument using -DDEPTH_OUT=size. e.g. -DDEPTH=16 + * @note The value to be used at the edges of the images shoud be given as a preprocessor argument using -DCONSTANT_VALUE=value. + * + * @param[in] in_ptr Pointer to the source image. Supported data types: U8/S16/F16/F32. + * @param[in] in_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] in_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] in_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in_stride_z Stride of the source image in Z dimension (in bytes) + * @param[in] in_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in_offset_first_element_in_bytes The offset of the first element in the source image + * @param[out] out_ptr Pointer to the destination image. Supported data types: same as @p in_ptr + * @param[in] out_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] out_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] out_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the destination image in Z dimension (in bytes) + * @param[in] out_step_z dst_stride_y * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination image + * @param[in] input_width Input image width + * @param[in] input_height Input image height + * @param[in] scale_x The scale factor along x dimension + * @param[in] scale_y The scale factor along y dimension + * + */ +__kernel void scale_bilinear_nhwc( + TENSOR4D_DECLARATION(in), + TENSOR4D_DECLARATION(out), + const float input_width, + const float input_height, + const float scale_x, + const float scale_y) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(in, 0); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(out, DEPTH_OUT); + +#ifdef SAMPLING_POLICY_TOP_LEFT + const float new_x = get_global_id(1) * scale_x; + const float new_y = (get_global_id(2) % DEPTH_OUT) * scale_y; +#elif SAMPLING_POLICY_CENTER + const float new_x = (get_global_id(1) + 0.5f) * scale_x - 0.5f; + const float new_y = ((get_global_id(2) % DEPTH_OUT) + 0.5f) * scale_y - 0.5f; +#else /* SAMPLING_POLICY */ +#error("Unsupported sampling policy"); +#endif /* SAMPLING_POLICY */ + + const float new_xf = floor(new_x); + const float new_yf = floor(new_y); + const float clamped_x = clamp(new_xf, 0.0f, input_width - 1); + const float clamped_x1 = clamp(new_xf + 1, 0.0f, input_width - 1); + const float clamped_y = clamp(new_yf, 0.0f, input_height - 1); + const float clamped_y1 = clamp(new_yf + 1, 0.0f, input_height - 1); + +#ifndef BORDER_MODE_REPLICATE + const bool check_x = (0.f <= new_xf && new_xf < input_width); + const bool check_x1 = (-1.f <= new_xf && new_xf < input_width - 1); + const bool check_y = (0.f <= new_yf && new_yf < input_height); + const bool check_y1 = (-1.f <= new_yf && new_yf < input_height - 1); + const float ins_0 = select((float)(CONSTANT_VALUE), (float)(*((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x), convert_int(clamped_y), + (get_global_id(2) / DEPTH_OUT)))), + check_x && check_y); + const float ins_1 = select((float)(CONSTANT_VALUE), (float)(*((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x1), convert_int(clamped_y), + (get_global_id(2) / DEPTH_OUT)))), + check_x1 && check_y); + const float ins_2 = select((float)(CONSTANT_VALUE), (float)(*((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x), convert_int(clamped_y1), + (get_global_id(2) / DEPTH_OUT)))), + check_x && check_y1); + const float ins_3 = select((float)(CONSTANT_VALUE), (float)(*((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x1), convert_int(clamped_y1), + (get_global_id(2) / DEPTH_OUT)))), + check_x1 && check_y1); + float4 ins = (float4)(ins_0, ins_1, ins_2, ins_3); +#else /* BORDER_MODE_REPLICATE */ + float4 ins = (float4)(*((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x), convert_int(clamped_y), (get_global_id(2) / DEPTH_OUT))), + *((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x1), convert_int(clamped_y), (get_global_id(2) / DEPTH_OUT))), + *((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x), convert_int(clamped_y1), (get_global_id(2) / DEPTH_OUT))), + *((__global DATA_TYPE *)tensor4D_offset(&in, get_global_id(0), convert_int(clamped_x1), convert_int(clamped_y1), (get_global_id(2) / DEPTH_OUT)))); +#endif /* BORDER_MODE_REPLICATE */ + + const float a = new_x - new_xf; + const float b = 1.f - a; + const float a1 = new_y - new_yf; + const float b1 = 1.f - a1; + const float fr = ((ins.s0 * b * b1) + (ins.s1 * a * b1) + (ins.s2 * b * a1) + (ins.s3 * a * a1)); + + *((__global DATA_TYPE *)out.ptr) = CONVERT(fr, DATA_TYPE); +} +#endif /* defined(DEPTH_OUT) */
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