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Diffstat (limited to 'src/core/CL/cl_kernels/softmax_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/softmax_layer.cl | 531 |
1 files changed, 0 insertions, 531 deletions
diff --git a/src/core/CL/cl_kernels/softmax_layer.cl b/src/core/CL/cl_kernels/softmax_layer.cl deleted file mode 100644 index 4d2d89dd73..0000000000 --- a/src/core/CL/cl_kernels/softmax_layer.cl +++ /dev/null @@ -1,531 +0,0 @@ -/* - * 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(MIN_VALUE) && defined(VECTOR_SIZE) && defined(VECTOR_SIZE_LEFTOVER) - -/** Divides all the values of the input tensor by the sum calculated from softmax_layer_shift_exp_sum kernel. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE, e.g. -DDATA_TYPE=float - * @note The zero value for the given data type must be given as a preprocessor argument using -DMIN_VALUE, e.g. -DMIN_VALUE=0 - * @note Vector size should be given as a preprocessor argument using -DVECTOR_SIZE=size. e.g. -DVECTOR_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVECTOR_SIZE_LEFTOVER. e.g. -DVECTOR_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VECTOR_SIZE - * @note In case of log softmax, -DLOG_SOFTMAX must be passed. - * - * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor 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 tensor - * @param[in] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the sum values tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the sum values tensor in Z dimension (in bytes) - * @param[in] sum_step_z sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the sum values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 dst_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 dst_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 dst_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 - */ -__kernel void softmax_layer_norm( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(sum), - TENSOR3D_DECLARATION(dst)) -{ - const int x_offs = max((int)(get_global_id(0) * VECTOR_SIZE - (VECTOR_SIZE - VECTOR_SIZE_LEFTOVER) % VECTOR_SIZE), 0) * sizeof(DATA_TYPE); - - __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; - - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT_NO_STEP(sum); - - // Load max value of 1D logits vector (row) - DATA_TYPE sum_val = *((__global DATA_TYPE *)offset(&sum, 0, get_global_id(1))); - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - data0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)src_addr); - -#if defined(LOG_SOFTMAX) - sum_val = log(sum_val); - data0 -= sum_val; -#else // defined(LOG_SOFTMAX) - data0 /= sum_val; -#endif // defined(LOG_SOFTMAX) - - STORE_VECTOR_SELECT(data, DATA_TYPE, dst_addr, VECTOR_SIZE, VECTOR_SIZE_LEFTOVER, VECTOR_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} - -#if defined(SRC_WIDTH) && defined(LOG_VECTOR_SIZE) && defined(MINVAL) - -/* Number of workitems in dimension 0. */ -#if !defined(GRID_SIZE) -#define GRID_SIZE 1 -#endif /* !defined(GRID_SIZE) */ - -#define VEC_TYPE VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) -#define SELECT_TYPE SELECT_VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - -/** Identifies the maximum value across the 1st dimension and shifts the values of the input tensor by this maximum value, - * then gets the exponent of each element as sums all elements across each row. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE, e.g. -DDATA_TYPE=float - * @note The zero value for the given data type must be given as a preprocessor argument using -DMIN_VALUE, e.g. -DMIN_VALUE=0 - * @note Vector size should be given as a preprocessor argument using -DVECTOR_SIZE=size. e.g. -DVECTOR_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVECTOR_SIZE_LEFTOVER. e.g. -DVECTOR_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VECTOR_SIZE - * @note In case the input is not a multiple of VECTOR_SIZE (2,4,8,16) -DNON_MULTIPLE_OF_VECTOR_SIZE must be passed. - * @note Beta can be optionally passed at compile time using -DBETA (by default, it is 1.0). - * @note In case of log softmax, -DLOG_SOFTMAX must be passed. - * @note Based on the data type, the minimum possible value must be passed using -DMINVAL. For float it should be defined as -FLT_MAX, while for half it should be -HALF_MAX - * - * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor 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 tensor - * @param[in] maxo_ptr Pointer to the max values tensor slice. Supported data types: same as @p src_ptr - * @param[in] maxo_stride_x Stride of the max values tensor in X dimension (in bytes) - * @param[in] maxo_step_x max_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] maxo_stride_y Stride of the max values tensor in Y dimension (in bytes) - * @param[in] maxo_step_y max_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] maxo_stride_z Stride of the max values tensor in Z dimension (in bytes) - * @param[in] maxo_step_z max_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] maxo_offset_first_element_in_bytes The offset of the first element in the max values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 dst_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 dst_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 dst_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[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the sum values tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the sum values tensor in Z dimension (in bytes) - * @param[in] sum_step_z sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the sum values tensor - */ -__kernel void softmax_layer_max_shift_exp_sum_serial( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(maxo), - TENSOR3D_DECLARATION(dst), - TENSOR3D_DECLARATION(sum)) -{ - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + 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 + get_global_id(1) * dst_stride_y + get_global_id(2) * dst_stride_z; - - Image maxo = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(maxo); - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(sum); - -#ifdef BETA - // Initialize beta - VEC_TYPE beta = (VEC_TYPE)BETA; -#endif /* BETA */ - - // Initialize local maximum - VEC_TYPE max_val_vec = (VEC_TYPE)(MINVAL); - -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)src_addr); - SELECT_TYPE widx = (SELECT_TYPE)VECTOR_SIZE_LEFTOVER > VEC_OFFS(SELECT_DATA_TYPE(DATA_TYPE), VECTOR_SIZE); - max_val_vec = max(max_val_vec, select((VEC_TYPE)(MINVAL), data, widx)); -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ - - for(uint i = VECTOR_SIZE_LEFTOVER; i < SRC_WIDTH; i += VECTOR_SIZE) - { - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr + i * sizeof(DATA_TYPE))); - max_val_vec = max(data, max_val_vec); - } - - // Perform max reduction - DATA_TYPE max_val = MAX_REDUCE(max_val_vec, VECTOR_SIZE); - *((__global DATA_TYPE *)maxo.ptr) = max_val; - - /* Second section */ - - // Set sum vector - VEC_TYPE sum1D = 0; - -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - data -= max_val; -#ifdef BETA - data *= beta; -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE_PARTIAL(VECTOR_SIZE, VECTOR_SIZE_LEFTOVER) - (data, 0, (__global DATA_TYPE *)dst_addr); - data = exp(data); - data = select(0, data, widx); -#else /* LOG_SOFTMAX */ - data = exp(data); - data = select(0, data, widx); - VSTORE_PARTIAL(VECTOR_SIZE, VECTOR_SIZE_LEFTOVER) - (data, 0, (__global DATA_TYPE *)dst_addr); -#endif /* LOG_SOFTMAX */ - sum1D += data; -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ - - // Shift values, exp and sum - for(uint i = VECTOR_SIZE_LEFTOVER; i < SRC_WIDTH; i += VECTOR_SIZE) - { - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr + i * sizeof(DATA_TYPE))); - data -= max_val; -#ifdef BETA - data *= beta; -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + i * sizeof(DATA_TYPE))); - data = exp(data); -#else /* LOG_SOFTMAX */ - data = exp(data); - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + i * sizeof(DATA_TYPE))); -#endif /* LOG_SOFTMAX */ - sum1D += data; - } - - // Perform sum reduction - *((__global DATA_TYPE *)sum.ptr) = SUM_REDUCE(sum1D, VECTOR_SIZE); -} - -/** Identifies the maximum value across the 1st dimension and shifts the values of the input tensor by this maximum value, - * then gets the exponent of each element as sums all elements across each row. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE, e.g. -DDATA_TYPE=float - * @note The zero value for the given data type must be given as a preprocessor argument using -DMIN_VALUE, e.g. -DMIN_VALUE=0 - * @note Vector size should be given as a preprocessor argument using -DVECTOR_SIZE=size. e.g. -DVECTOR_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVECTOR_SIZE_LEFTOVER. e.g. -DVECTOR_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VECTOR_SIZE - * @note In case the input is not a multiple of VECTOR_SIZE (2,4,8,16) -DNON_MULTIPLE_OF_VECTOR_SIZE must be passed. - * @note Beta can be optionally passed at compile time using -DBETA (by default, it is 1.0). - * @note In case of log softmax, -DLOG_SOFTMAX must be passed. - * @note Based on the data type, the minimum possible value must be passed using -DMINVAL. For float it should be defined as -FLT_MAX, while for half it should be -HALF_MAX - * - * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor 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 tensor - * @param[in] maxo_ptr Pointer to the max values tensor slice. Supported data types: same as @p src_ptr - * @param[in] maxo_stride_x Stride of the max values tensor in X dimension (in bytes) - * @param[in] maxo_step_x max_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] maxo_stride_y Stride of the max values tensor in Y dimension (in bytes) - * @param[in] maxo_step_y max_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] maxo_stride_z Stride of the max values tensor in Z dimension (in bytes) - * @param[in] maxo_step_z max_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] maxo_offset_first_element_in_bytes The offset of the first element in the max values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 dst_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 dst_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 dst_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[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the sum values tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the sum values tensor in Z dimension (in bytes) - * @param[in] sum_step_z sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the sum values tensor - */ -__kernel void softmax_layer_max_shift_exp_sum_parallel( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(maxo), - TENSOR3D_DECLARATION(dst), - TENSOR3D_DECLARATION(sum)) -{ - const uint lid = get_local_id(0); - const uint x_offs = (VECTOR_SIZE_LEFTOVER + lid * VECTOR_SIZE) * sizeof(DATA_TYPE); - - __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; - - Image maxo = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(maxo); - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(sum); - -#ifdef BETA - // Initialize beta - VEC_TYPE beta = (VEC_TYPE)BETA; -#endif /* BETA */ - - // Define one temporary vector per work-item. - __local VEC_TYPE tmp_local[GRID_SIZE]; - __local DATA_TYPE max_local; - - VEC_TYPE max_val_vec = (VEC_TYPE)(MINVAL); - - // Number of iterations per work-item. - const uint width = (SRC_WIDTH / GRID_SIZE) >> LOG_VECTOR_SIZE; - // Calculate max of row - uint i = 0; - for(; i < width; ++i) - { - VEC_TYPE data_max = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - max_val_vec = max(data_max, max_val_vec); - } -#ifdef NON_MULTIPLE_OF_GRID_SIZE - // How many work-items needed to complete the computation. - int boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; - if(lid < boundary_workitems) - { - VEC_TYPE data_max = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - max_val_vec = max(data_max, max_val_vec); - } -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - SELECT_TYPE widx; - if(lid == 0) - { - // Handle non multiple of 4 - VEC_TYPE data_max = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr - VECTOR_SIZE_LEFTOVER * sizeof(DATA_TYPE))); - widx = (SELECT_TYPE)VECTOR_SIZE_LEFTOVER > VEC_OFFS(SELECT_DATA_TYPE(DATA_TYPE), VECTOR_SIZE); - max_val_vec = max(max_val_vec, select((VEC_TYPE)(MINVAL), data_max, widx)); - } -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ -#endif /* NON_MULTIPLE_OF_GRID_SIZE */ - tmp_local[lid] = max_val_vec; - - barrier(CLK_LOCAL_MEM_FENCE); - - if(GRID_SIZE >= 256) - { - if(lid < 128) - { - tmp_local[lid] = max(tmp_local[lid + 128], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 128) - { - if(lid < 64) - { - tmp_local[lid] = max(tmp_local[lid + 64], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 64) - { - if(lid < 32) - { - tmp_local[lid] = max(tmp_local[lid + 32], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 32) - { - if(lid < 16) - { - tmp_local[lid] = max(tmp_local[lid + 16], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 16) - { - if(lid < 8) - { - tmp_local[lid] = max(tmp_local[lid + 8], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 8) - { - if(lid < 4) - { - tmp_local[lid] = max(tmp_local[lid + 4], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 4) - { - if(lid < 2) - { - tmp_local[lid] = max(tmp_local[lid + 2], tmp_local[lid]); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(lid == 0) - { - max_val_vec = max(tmp_local[lid + 1], tmp_local[lid]); - max_local = MAX_REDUCE(max_val_vec, VECTOR_SIZE); - } - barrier(CLK_LOCAL_MEM_FENCE); - - /* Second section */ - - // Set sum vector - VEC_TYPE sum1D = 0; - DATA_TYPE max_val = max_local; - - // Shift values, exp and sum - for(i = 0; i < width; ++i) - { - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - data -= max_val; -#ifdef BETA - data *= beta; -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - data = exp(data); -#else /* LOG_SOFTMAX */ - data = exp(data); - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); -#endif /* LOG_SOFTMAX */ - sum1D += data; - } -#ifdef NON_MULTIPLE_OF_GRID_SIZE - boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; - if(lid < boundary_workitems) - { - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(__global DATA_TYPE *)(src_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - data -= max_val; -#ifdef BETA - data *= beta; -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); - data = exp(data); -#else /* LOG_SOFTMAX */ - data = exp(data); - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)(dst_addr + (i * GRID_SIZE * VECTOR_SIZE) * sizeof(DATA_TYPE))); -#endif /* LOG_SOFTMAX */ - sum1D += data; - } -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - if(lid == 0) - { - // Handle non multiple of vector size ((GRID_SIZE * i * 4) + 4, 0); move 4 float positions ahead, *4 is due to the stride - VEC_TYPE data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(src_addr - VECTOR_SIZE_LEFTOVER * sizeof(DATA_TYPE))); - data -= max_val; -#ifdef BETA - data *= beta; -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE_PARTIAL(VECTOR_SIZE, VECTOR_SIZE_LEFTOVER) - (data, 0, (__global DATA_TYPE *)(dst_addr - VECTOR_SIZE_LEFTOVER * sizeof(DATA_TYPE))); - data = exp(data); - data = select(0, data, widx); -#else /* LOG_SOFTMAX */ - data = exp(data); - data = select(0, data, widx); - VSTORE_PARTIAL(VECTOR_SIZE, VECTOR_SIZE_LEFTOVER) - (data, 0, (__global DATA_TYPE *)(dst_addr - VECTOR_SIZE_LEFTOVER * sizeof(DATA_TYPE))); -#endif /* LOG_SOFTMAX */ - sum1D += data; - } -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ -#endif /* NON_MULTIPLE_OF_GRID_SIZE */ - tmp_local[lid] = sum1D; - - barrier(CLK_LOCAL_MEM_FENCE); - - if(GRID_SIZE >= 256) - { - if(lid < 128) - { - tmp_local[lid] += tmp_local[lid + 128]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 128) - { - if(lid < 64) - { - tmp_local[lid] += tmp_local[lid + 64]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 64) - { - if(lid < 32) - { - tmp_local[lid] += tmp_local[lid + 32]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 32) - { - if(lid < 16) - { - tmp_local[lid] += tmp_local[lid + 16]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 16) - { - if(lid < 8) - { - tmp_local[lid] += tmp_local[lid + 8]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 8) - { - if(lid < 4) - { - tmp_local[lid] += tmp_local[lid + 4]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 4) - { - if(lid < 2) - { - tmp_local[lid] += tmp_local[lid + 2]; - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(lid == 0) - { - sum1D = (tmp_local[lid + 1] + tmp_local[lid]); - // Perform sum reduction - *((__global DATA_TYPE *)sum.ptr) = SUM_REDUCE(sum1D, VECTOR_SIZE); - } -} - -#endif // defined(SRC_WIDTH) && defined(LOG_VECTOR_SIZE) && defined(MINVAL) -#endif // defined(DATA_TYPE) && defined(MIN_VALUE) && defined(VECTOR_SIZE) && defined(VECTOR_SIZE_LEFTOVER)
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