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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/minmax_layer.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/minmax_layer.cl')
-rw-r--r-- | src/core/CL/cl_kernels/minmax_layer.cl | 101 |
1 files changed, 0 insertions, 101 deletions
diff --git a/src/core/CL/cl_kernels/minmax_layer.cl b/src/core/CL/cl_kernels/minmax_layer.cl deleted file mode 100644 index 655696f9a1..0000000000 --- a/src/core/CL/cl_kernels/minmax_layer.cl +++ /dev/null @@ -1,101 +0,0 @@ -/* - * Copyright (c) 2017 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(WIDTH) && defined(HEIGHT) && defined(DEPTH) -/** This function identifies the min and maximum value of an input 3D tensor. - * - * @note The width, height and depth of the input tensor must be provided at compile time using -DWIDTH, -DHEIGHT and -DDEPTH (e.g. -DWIDTH=320, -DHEIGHT=240, -DDEPTH=3) - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: F32 - * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] src_stride_z Stride of the source image in Z dimension (in bytes) - * @param[in] src_step_z src_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 source image - * @param[in] dst_ptr Pointer to the min/max vector. Minimum value in position 0, maximum value in position 1. Supported data types: F32. - * @param[in] dst_stride_x Stride of the min/max vector in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the min/max vector - */ -__kernel void minmax_layer( - TENSOR3D_DECLARATION(src), - VECTOR_DECLARATION(dst)) -{ - Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); - Vector dst = CONVERT_TO_VECTOR_STRUCT(dst); - - float4 min_value = (float4)FLT_MAX; - float4 max_value = (float4) - FLT_MAX; - float2 min_max_value = (float2)(FLT_MAX, -FLT_MAX); - - for(int z = 0; z < DEPTH; ++z) - { - for(int y = 0; y < HEIGHT; ++y) - { - int x = 0; - __global float *src_addr = (__global float *)(src.ptr + y * src_stride_y + z * src_stride_z); - - for(; x <= (int)(WIDTH - 8); x += 8) - { - float8 value = *(src_addr + x); - - min_value = select(value.s0123, min_value, min_value < value.s0123); - min_value = select(value.s4567, min_value, min_value < value.s4567); - - max_value = select(value.s0123, max_value, max_value > value.s0123); - max_value = select(value.s4567, max_value, max_value > value.s4567); - } - - for(; x < WIDTH; ++x) - { - float value = *(src_addr + x); - - min_max_value.s0 = min(min_max_value.s0, value); - min_max_value.s1 = max(min_max_value.s1, value); - } - } - } - - // Perform min/max reduction - min_value.s01 = min(min_value.s01, min_value.s23); - min_value.s0 = min(min_value.s0, min_value.s1); - max_value.s01 = max(max_value.s01, max_value.s23); - max_value.s0 = max(max_value.s0, max_value.s1); - - min_max_value.s0 = min(min_max_value.s0, min_value.s0); - min_max_value.s1 = max(min_max_value.s1, max_value.s0); - - if(min_max_value.s0 == min_max_value.s1) - { - min_max_value.s0 = 0.0f; - min_max_value.s1 = 1.0f; - } - - // Store min and max - vstore2(min_max_value, 0, (__global float *)dst.ptr); -} -#endif // defined(WIDTH) && defined(HEIGHT) && defined(DEPTH)
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