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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/nchw/pooling_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/nchw/pooling_layer_quantized.cl')
-rw-r--r-- | src/core/CL/cl_kernels/nchw/pooling_layer_quantized.cl | 142 |
1 files changed, 142 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nchw/pooling_layer_quantized.cl b/src/core/CL/cl_kernels/nchw/pooling_layer_quantized.cl new file mode 100644 index 0000000000..1440ef3ed1 --- /dev/null +++ b/src/core/CL/cl_kernels/nchw/pooling_layer_quantized.cl @@ -0,0 +1,142 @@ +/* + * Copyright (c) 2017-2021 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(INITIAL_VALUE) +#define VEC_TYPE(VEC_SIZE) VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + +#if defined(POOL_AVG) +#define POOL_OP(x, y) ((x) + (y)) +#else /* defined(POOL_AVG) */ +#define POOL_OP(x, y) (max((x), (y))) +#endif /* defined(POOL_AVG) */ + +#define DIV_OP(x, y) (x * (1.f / y)) + +#if defined(POOL_L2) +#error "L2 pooling is not supported" +#endif /* defined(POOL_L2) */ + +int calculate_avg_scale(const int pool_size_x, const int pool_size_y, const int upper_bound_w, const int upper_bound_h, + const int pad_x, const int pad_y, const int stride_x, const int stride_y) +{ + int start_x = get_global_id(0) * stride_x - pad_x; + int start_y = get_global_id(1) * stride_y - pad_y; + const int end_x = min(start_x + pool_size_x, upper_bound_w); + const int end_y = min(start_y + pool_size_y, upper_bound_h); +#if defined(EXCLUDE_PADDING) + start_x = max(0, start_x); + start_y = max(0, start_y); +#endif /* defined(EXCLUDE_PADDING) */ + return ((end_y - start_y) * (end_x - start_x)); +} + +/** Performs a pooling function of pool size equal to N (NCHW) + * + * @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13; + * @note In case of average pooling the following information must be passed at compile time: + * -DPOOL_AVG must be provided otherwise max pooling will be performed. + * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) + * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions + * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension + * @note Input data type must be passed at compile time using -DDAT_TYPE=type, e.g. -DDATA_TYPE=uchar + * @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0 + * + * @param[in] input_ptr Pointer to the source image. Supported data types: QASYMM8/QASYMM8_SIGNED + * @param[in] input_stride_x Stride of the source image 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 image 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 image + * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination image 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 image 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 source 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 image + */ +__kernel void pooling_layer_MxN_quantized_nchw( + TENSOR3D_DECLARATION(input), + TENSOR3D_DECLARATION(output)) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); + + int8 vdata = INITIAL_VALUE; + int sdata = INITIAL_VALUE; + + // Load data + for(int y = 0; y < POOL_SIZE_Y; y++) + { + int x = 0; + for(; x <= ((int)POOL_SIZE_X - 8); x += 8) + { + VEC_TYPE(8) + data = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)); + int8 data0 = convert_int8(data); + vdata = POOL_OP(vdata, data0); + } + + // Leftover + for(; x < (int)POOL_SIZE_X; ++x) + { + DATA_TYPE data = *((__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)); + int data0 = convert_int(data); + sdata = POOL_OP(sdata, data0); + } + } + + // Reduce result + int4 reduce4 = POOL_OP(vdata.s0123, vdata.s4567); + int2 reduce2 = POOL_OP(reduce4.s01, reduce4.s23); + int res = POOL_OP(reduce2.s0, reduce2.s1); + res = POOL_OP(res, sdata); + +#if defined(POOL_AVG) + res = round(DIV_OP(res, calculate_avg_scale(POOL_SIZE_X, POOL_SIZE_Y, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y))); +#endif /* defined(POOL_AVG) */ + + DATA_TYPE result_q8 = CONVERT(res, DATA_TYPE); + +#if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) + + const float result_f32 = convert_float(result_q8); + const float input_offset = (float)OFFSET_IN1; + const float input_scale = (float)SCALE_IN1; + const float scale_out = (float)SCALE_OUT; + const float offset_out = (float)OFFSET_OUT; + const float in_f32 = (result_f32 - input_offset) * input_scale; + const float out_f32 = in_f32 / scale_out + offset_out; + result_q8 = CONVERT_SAT(convert_int_rte(out_f32), DATA_TYPE); + +#endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */ + + *(__global DATA_TYPE *)output.ptr = result_q8; +} +#endif // defined(DATA_TYPE) && defined(INITIAL_VALUE)
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