From 375156937a0783432c5d18e199b5d8d2b3ec33f7 Mon Sep 17 00:00:00 2001 From: ramelg01 Date: Sat, 26 Feb 2022 22:06:20 +0000 Subject: Implementation of ClPooling3d - For NDHWC layout - For F16 and F32 data types - Mixed Precision stil not supported Resolves: COMPMID-4670 Signed-off-by: ramy.elgammal@arm.com Change-Id: I0e14a13e4625569e8e5ee67e6033bd1efe0da469 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7262 Comments-Addressed: Arm Jenkins Reviewed-by: SiCong Li Reviewed-by: Gunes Bayir Tested-by: Arm Jenkins --- src/core/CL/ICLKernel.cpp | 3 +- src/core/CL/ICLKernel.h | 10 ++ src/core/CL/cl_kernels/helpers.h | 16 +- src/core/CL/cl_kernels/nhwc/pooling_3d_layer.cl | 190 ++++++++++++++++++++++++ 4 files changed, 217 insertions(+), 2 deletions(-) create mode 100644 src/core/CL/cl_kernels/nhwc/pooling_3d_layer.cl (limited to 'src/core/CL') diff --git a/src/core/CL/ICLKernel.cpp b/src/core/CL/ICLKernel.cpp index 9bbc710c88..109a076e9a 100644 --- a/src/core/CL/ICLKernel.cpp +++ b/src/core/CL/ICLKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2021 Arm Limited. + * Copyright (c) 2016-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -173,6 +173,7 @@ template void ICLKernel::add_tensor_argument<1>(unsigned &idx, const ICLTensor * template void ICLKernel::add_tensor_argument<2>(unsigned &idx, const ICLTensor *tensor, const Window &window); template void ICLKernel::add_tensor_argument<3>(unsigned &idx, const ICLTensor *tensor, const Window &window); template void ICLKernel::add_tensor_argument<4>(unsigned &idx, const ICLTensor *tensor, const Window &window); +template void ICLKernel::add_tensor_argument<5>(unsigned &idx, const ICLTensor *tensor, const Window &window); #endif /* DOXYGEN_SKIP_THIS */ void ICLKernel::set_target(cl::Device &device) diff --git a/src/core/CL/ICLKernel.h b/src/core/CL/ICLKernel.h index 4c8028e42a..046679e34e 100644 --- a/src/core/CL/ICLKernel.h +++ b/src/core/CL/ICLKernel.h @@ -238,6 +238,16 @@ public: { add_tensor_argument<4>(idx, tensor, window); } + /** Add the passed 5D tensor's parameters to the object's kernel's arguments starting from the index idx. + * + * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. + * @param[in] tensor Tensor to set as an argument of the object's kernel. + * @param[in] window Window the kernel will be executed on. + */ + void add_5D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window) + { + add_tensor_argument<5>(idx, tensor, window); + } /** Add the passed NHW 3D tensor's parameters to the object's kernel's arguments by passing strides, dimensions and the offset to the first valid element in bytes. * diff --git a/src/core/CL/cl_kernels/helpers.h b/src/core/CL/cl_kernels/helpers.h index bfb693e376..4018c40b16 100644 --- a/src/core/CL/cl_kernels/helpers.h +++ b/src/core/CL/cl_kernels/helpers.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2021 Arm Limited. + * Copyright (c) 2016-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -831,6 +831,20 @@ uint name##_step_w, \ uint name##_offset_first_element_in_bytes +#define TENSOR5D_DECLARATION(name) \ + __global uchar *name##_ptr, \ + uint name##_stride_x, \ + uint name##_step_x, \ + uint name##_stride_y, \ + uint name##_step_y, \ + uint name##_stride_z, \ + uint name##_step_z, \ + uint name##_stride_w, \ + uint name##_step_w, \ + uint name##_stride_v, \ + uint name##_step_v, \ + uint name##_offset_first_element_in_bytes + #define CONVERT_TO_VECTOR_STRUCT(name) \ update_vector_workitem_ptr(name##_ptr, name##_offset_first_element_in_bytes, name##_stride_x, name##_step_x) diff --git a/src/core/CL/cl_kernels/nhwc/pooling_3d_layer.cl b/src/core/CL/cl_kernels/nhwc/pooling_3d_layer.cl new file mode 100644 index 0000000000..7c6414312f --- /dev/null +++ b/src/core/CL/cl_kernels/nhwc/pooling_3d_layer.cl @@ -0,0 +1,190 @@ +/* + * Copyright (c) 2022 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 "tile_helpers.h" // Needed for GET_SPATIAL_IDX() + +#if defined(POOL_AVG) || defined(POOL_L2) +#define POOL_OP(x, y) ((x) + (y)) +#else /* defined(POOL_AVG) || defined(POOL_L2) */ +#define POOL_OP(x, y) (fmax((x), (y))) +#endif /* defined(POOL_AVG) || defined(POOL_L2) */ + +#define SQRT_OP(x) sqrt((x)) + +#if defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_DEPTH) && defined(DST_BATCH_SIZE) && defined(ACC_DATA_TYPE) + +#if defined(POOL_SIZE_X) && defined(POOL_SIZE_Y) && defined(POOL_SIZE_Z) + +/** Performs 3d pooling layer of size equal to MxNXD. This OpenCL kernel can perform the following pooling types: + * -# max, -DPOOL_MAX must be passed at compile time + * -# average, -DPOOL_AVG must be passed at compile time. If padding has to be excluded, -DEXCLUDE_PADDING should be passed at compile time + * -# l2 normalisation, -DPOOL_L2 must be passed at compile time + * + * @note Datatype must be passed at compile type using -DDATA_TYPE e.g. -DDATA_TYPE=half. Supported data types are F32/F16 + * @note Accumulation data type must be passed at compile time using -DACC_DATA_TYPE e.g. -DACC_DATA_TYPE=float + * @note If -DFP_MIXED_PRECISION is passed at compile time, the kernel will use F32 for the partial result + * @note Pool size must be passed at compile time using -DPOOL_SIZE_X, -DPOOL_SIZE_Y, and -DPOOL_SIZE_Z. e.g. -DPOOL_SIZE_X=4, -DPOOL_SIZE_Y=4, -DPOOL_SIZE_Z=2 + * @note Input tensor width, height and depth must be passed at compile time using -DSRC_WIDTH, -DSRC_HEIGHT, and -DSRC_DEPTH + * @note Output tensor height, channels, depth, and batch size must be passed at compile time using -DDST_HEIGHT, -DDST_CHANNELS, -DDST_DEPTH, and -DDST_BATCH_SIZE + * @note Pool strides must be passed at compile time using -DSTRIDE_X, -DSTRIDE_Y and -DSTRIDE_Z which are the steps of the window along the x, y and z directions + * @note Pool pads must be passed at compile time using -DPAD_X, -DPAD_Y, -DPAD_Z + * @note Vector size must be passed at compile time using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * @note Leftover vector size must 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 + * @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 tensor. Supported data types: F32/F16 + * @param[in] input_stride_x Stride of the source tensor 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 tensor 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_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) + * @param[in] input_stride_v Stride of the source tensor in V dimension (in bytes) + * @param[in] input_step_v input_stride_v * number of elements along V processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor 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 tensor 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 destination 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_stride_w Stride of the destination tensor in W dimension (in bytes) + * @param[in] output_step_w output_stride_w * number of elements along W processed per workitem(in bytes) + * @param[in] output_stride_v Stride of the destination tensor in V dimension (in bytes) + * @param[in] output_step_v output_stride_v * number of elements along V processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void pooling_3d_layer_MxN_ndhwc( + TENSOR5D_DECLARATION(input), + TENSOR5D_DECLARATION(output)) +{ + // Note: If C is not multiple of VEC_SIZE, we shift back of VEC_SIZE_LEFTOVER elements to compute the leftover elements for get_global_id(0) == 0 + // Note: If C is less than VEC_SIZE, VEC_SIZE should be SHRINKED to the closest smaller VEC_SIZE. This operation is performed on the host side + int idx_out_c = GET_SPATIAL_IDX(0, VEC_SIZE, VEC_SIZE_LEFTOVER); + int idx_out_w = GET_SPATIAL_IDX(1, 1, 0); + + // The depth size dimension and the batch size dimension are collapsed over the height dimension + int idx_out_h = GET_SPATIAL_IDX(2, 1, 0) % DST_HEIGHT; + int idx_out_d = (GET_SPATIAL_IDX(2, 1, 0) / DST_HEIGHT) % DST_DEPTH; + int idx_out_n = (GET_SPATIAL_IDX(2, 1, 0) / DST_HEIGHT) / DST_DEPTH; + + __global unsigned char *in_base_ptr = input_ptr + input_offset_first_element_in_bytes + idx_out_c * sizeof(DATA_TYPE) + idx_out_n * input_stride_v; + + __global unsigned char *out_base_ptr = output_ptr + output_offset_first_element_in_bytes + idx_out_c * sizeof(DATA_TYPE) + idx_out_w * output_stride_y + idx_out_h * output_stride_z + idx_out_d * + output_stride_w + idx_out_n * output_stride_v; + + VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) + res0 = INITIAL_VALUE; + + int idx_in_w = idx_out_w * STRIDE_X - (int)PAD_X; + int idx_in_h = idx_out_h * STRIDE_Y - (int)PAD_Y; + int idx_in_d = idx_out_d * STRIDE_Z - (int)PAD_Z; + + // The start of width to consider in calculation should exclude padding + int pool_x_s = max((int)0, -idx_in_w); + // Assumed Symmetric Padding (left padding = right padding = PAD_X), the filter end should be either the pool width or what is remaining from current pos to the (src width + pad right) + int pool_x_e = min((int)POOL_SIZE_X, (int)SRC_WIDTH + PAD_X - idx_in_w); + int pool_y_s = max((int)0, -idx_in_h); + int pool_y_e = min((int)POOL_SIZE_Y, (int)SRC_HEIGHT + PAD_Y - idx_in_h); + int pool_z_s = max((int)0, -idx_in_d); + int pool_z_e = min((int)POOL_SIZE_Z, (int)SRC_DEPTH + PAD_Z - idx_in_d); + + // The filter size with all padding in all directions considered. + int filter_size = pool_z_e * pool_y_e * pool_x_e; + + // The end of width to consider in calculation should exclude PAD_X + pool_x_e = min(pool_x_e, SRC_WIDTH - idx_in_w); + pool_y_e = min(pool_y_e, SRC_HEIGHT - idx_in_h); + pool_z_e = min(pool_z_e, SRC_DEPTH - idx_in_d); + +#if defined(EXCLUDE_PADDING) + filter_size = (pool_z_e - pool_z_s) * (pool_y_e - pool_y_s) * (pool_x_e - pool_x_s); +#endif // defined(EXCLUDE_PADDING) + +#if POOL_SIZE_X == SRC_WIDTH && POOL_SIZE_Y == SRC_HEIGHT && POOL_SIZE_Z == SRC_DEPTH && PAD_X == 0 && PAD_Y == 0 && PAD_Z == 0 + // Global pooling path + for(int z = 0; z < POOL_SIZE_Z; ++z) + { + int depth_offset_src = (z + idx_in_d) * input_stride_w; + for(int y = 0; y < POOL_SIZE_Y; ++y) + { + int height_offset_src = (y + idx_in_h) * input_stride_z; +#pragma unroll 8 + for(int x = 0; x < POOL_SIZE_X; ++x) + { + int width_offset_src = (x + idx_in_w) * input_stride_y; +#else // POOL_SIZE_X == SRC_WIDTH && POOL_SIZE_Y == SRC_HEIGHT && POOL_SIZE_Z == SRC_DEPTH && PAD_X == 0 && PAD_Y == 0 && PAD_Z == 0 + for(int z = pool_z_s; z < pool_z_e; ++z) + { + int depth_offset_src = (z + idx_in_d) * input_stride_w; + for(int y = pool_y_s; y < pool_y_e; ++y) + { + int height_offset_src = (y + idx_in_h) * input_stride_z; +#pragma unroll 8 + for(int x = pool_x_s; x < pool_x_e; ++x) + { + int width_offset_src = (x + idx_in_w) * input_stride_y; +#endif // POOL_SIZE_X == SRC_WIDTH && POOL_SIZE_Y == SRC_HEIGHT && POOL_SIZE_Z == SRC_DEPTH && PAD_X == 0 && PAD_Y == 0 && PAD_Z == 0 + VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) + data0; +#if defined(FP_MIXED_PRECISION) + // In case of FP_MIXED_PRECISION, ACC_DATA_TYPE is != DATA_TYPE + data0 = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(in_base_ptr + width_offset_src + height_offset_src + depth_offset_src)), + VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)); +#else // defined(FP_MIXED_PRECISION) + data0 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(in_base_ptr + width_offset_src + height_offset_src + depth_offset_src)); +#endif // defined(FP_MIXED_PRECISION) + +#if defined(POOL_L2) + // Raise to power of 2 for L2 Pooling + data0 *= data0; +#endif // defined(POOL_L2) + res0 = POOL_OP(res0, data0); + } + } + } + +#if defined(POOL_AVG) || defined(POOL_L2) + res0 /= (VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE))filter_size; +#endif // defined(POOL_AVG) || defined(POOL_L2) + +#if defined(POOL_L2) + // Take square root of the result in L2 pooling + res0 = SQRT_OP(res0); +#endif // defined(POOL_L2) + + // Store result +#if defined(FP_MIXED_PRECISION) + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res_converted0 = CONVERT(res0, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); + STORE_VECTOR_SELECT(res_converted, DATA_TYPE, out_base_ptr, VEC_SIZE, VEC_SIZE_LEFTOVER, (VEC_SIZE_LEFTOVER != 0) && get_global_id(0) == 0); +#else // defined(FP_MIXED_PRECISION) + STORE_VECTOR_SELECT(res, DATA_TYPE, out_base_ptr, VEC_SIZE, VEC_SIZE_LEFTOVER, (VEC_SIZE_LEFTOVER != 0) && get_global_id(0) == 0); +#endif // defined(FP_MIXED_PRECISION) +} +#endif // defined(POOL_SIZE_X) && defined(POOL_SIZE_Y) && defined(POOL_SIZE_Z) +#endif // defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_DEPTH) && defined(DST_BATCH_SIZE) && defined(ACC_DATA_TYPE) -- cgit v1.2.1