| /* |
| * Copyright (c) 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 "helpers_asymm.h" |
| #include "tile_helpers.h" |
| |
| //! @cond Doxygen_Suppress |
| /** OpenCL kernel to compute the direct convolution. |
| * |
| * @note Data layout supported: NHWC |
| * @note Data type supported: F32/F16/QASYMM8/QASYMM8_SIGNED |
| * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=half) |
| * @note The accumulation data type must be passed at compile time using -DACC_DATA_TYPE (e.g. -DDATA_TYPE_PROMOTED=half) |
| * @note The convolution padding (left and top) must be passed at compile time using -DPAD_LEFT and -DPAD_TOP (e.g. -DPAD_LEFT=2, -DPAD_TOP=2) |
| * @note The convolution strides must be passed at compile time using -DSTRIDE and -DPAD_TOP (e.g. -DPAD_LEFT=2, -DPAD_TOP=2) |
| * @note The spatial dimensions of the weights must be passed at compile time using -DWEI_WIDTH and -DWEI_HEIGHT (e.g. -DWEI_WIDTH=9, -DWEI_HEIGHT=9) |
| * @note The spatial dimensions of the source tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT (e.g. -DSRC_WIDTH=96, -DSRC_HEIGHT=64) |
| * @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH and -DDST_HEIGHT (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64) |
| * @note The channels of the source tensor must be passed at compile time using -DSRC_CHANNELS (e.g. -DSRC_CHANNELS=64) |
| * @note The channels of the destination tensor must be passed at compile time using -DDST_CHANNELS (e.g. -DDDST_CHANNELS=64) |
| * @note The tensor type ("BUFFER" or "IMAGE") of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER) |
| * @note The tensor type ("BUFFER" or "IMAGE") of the weights tensor must be passed at compile time using -DWEI_TENSOR_TYPE (e.g. -DWEI_TENSOR_TYPE=BUFFER) |
| * @note The tensor type ("BUFFER" or "IMAGE") of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER) |
| * @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float) |
| * @note The data type of the weights tensor must be passed at compile time using -DWEI_DATA_TYPE (e.g. -DWEI_DATA_TYPE=float) |
| * @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float) |
| * @note The data type of the accumulators must be passed at compile time using -DACC_DATA_TYPE (e.g. -DACC_DATA_TYPE=float) |
| * @note The number of M0 rows (width*height) to process must be passed at compile time using -DM0 (e.g. -DM0=2) |
| * @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2) |
| * @note The number of K0 inner accumulations must be passed at compile time using -DK0 (e.g. -DK0=2) |
| * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1) |
| * @note The zero value must be passed at compile time using -DZERO_VALUE (e.g. -DZERO_VALUE=0) |
| * @note Only the following configurations of M0, N0 and K0 are currently supported: |
| * - M0 = 1, 2, 3, 4, 5, .... n |
| * - N0 = 2, 3, 4, 8, 16 |
| * - K0 = 2, 3, 4, 8, 16 (only 4, 8 and 16 if WEI_TENSOR_TYPE=IMAGE) |
| * |
| *@note In case of QASYMM8/QASYMM8_SIGNED, the following extra information must be passed at compile time: |
| * - -DIS_QUANTIZED |
| * - The destination quantization multiplier e.g. -DDST_MULTIPLIER=1234 |
| * - The destination quantization shift e.g. -DDST_SHIFT=4 |
| * - The destination offset e.g. -DDST_OFFSET=4 |
| * - The source offset e.g. -DSRC_OFFSET=4 |
| * - The weights offset e.g. -DWEI_OFFSET=4 |
| * - The quantized zero value e.g. -DZERO_VALUE=4 |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32/QASYMM8 |
| * @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_stride_w Stride of the source tensor in W dimension (in bytes) |
| * @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes) |
| * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: 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_stride_w Stride of the destination tensor in W dimension (in bytes) |
| * @param[in] dst_step_w dst_stride_w * number of elements along W processed per workitem(in bytes) |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| * @param[in] wei_ptr Pointer to the weights tensor. Supported data type: same as @p src_ptr |
| * @param[in] wei_stride_x Stride of the weights tensor in X dimension (in bytes) |
| * @param[in] wei_step_x wei_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] wei_stride_y Stride of the weights tensor in Y dimension (in bytes) |
| * @param[in] wei_step_y wei_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] wei_stride_z Stride of the weights tensor in Z dimension (in bytes) |
| * @param[in] wei_step_z wei_stride_z * number of elements along Z processed per workitem(in bytes) |
| * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes) |
| * @param[in] wei_step_w wei_stride_w * number of elements along W processed per workitem(in bytes) |
| * @param[in] wei_offset_first_element_in_bytes The offset of the first element in the bias matrix |
| * @param[in] bia_ptr (Optional) Pointer to the bias tensor Supported data type: same as @p src_ptr (if F32/F16) or S32 (if QASYMM8/QASYMM8_SIGNED) |
| * @param[in] bia_stride_x (Optional) Stride of the bias tensor in X dimension (in bytes) |
| * @param[in] bia_step_x (Optional) bia_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix |
| */ |
| //! @endcond |
| __kernel void direct_convolution_nhwc( |
| TENSOR4D(src, SRC_TENSOR_TYPE), |
| TENSOR4D(dst, DST_TENSOR_TYPE), |
| TENSOR4D(wei, WEI_TENSOR_TYPE) |
| #if defined(HAS_BIAS) |
| , |
| VECTOR_DECLARATION(bia) |
| #endif // defined(HAS_BIAS) |
| ) |
| { |
| // All the tensor dimensions are passed at compile time. |
| // In case of dynamic tensor support, the following dimensions should be passed as function argument. |
| #define _IWEI_WIDTH WEI_WIDTH |
| #define _IWEI_HEIGHT WEI_HEIGHT |
| #define _ISRC_WIDTH SRC_WIDTH |
| #define _ISRC_HEIGHT SRC_HEIGHT |
| #define _ISRC_CHANNELS SRC_CHANNELS |
| #define _IDST_WIDTH DST_WIDTH |
| #define _IDST_HEIGHT DST_HEIGHT |
| #define _IDST_CHANNELS DST_CHANNELS |
| #define _IY_MULTIPLIER (_IWEI_WIDTH * _IWEI_HEIGHT) |
| |
| // If quantized, the output tile has to be quantized first before being stored to global memory |
| #if defined(IS_QUANTIZED) |
| #define _IOUTPUT_TILE cq |
| #else // defined(IS_QUANTIZED) |
| #define _IOUTPUT_TILE c |
| #endif // defined(IS_QUANTIZED) |
| |
| const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM |
| const int mout = GET_SPATIAL_IDX(1, M0, 0); // WIDTH x HEIGHT |
| const int bout = GET_SPATIAL_IDX(2, 1, 0); // BATCH SIZE IDX |
| |
| // .v = access the whole vector (OpenCL vector) |
| // .s[x] = access the vector element at position x (scalar access) |
| TILE(int, M0, 1, xi); |
| TILE(int, M0, 1, yi); |
| |
| // Convert the linear index to coordinate |
| LOOP_UNROLLING(int, i, 0, M0, 1) |
| { |
| xi[i].v = ((mout + i) % _IDST_WIDTH) * STRIDE_X; |
| yi[i].v = ((mout + i) / _IDST_WIDTH) * STRIDE_Y; |
| xi[i].v -= PAD_LEFT; |
| yi[i].v -= PAD_TOP; |
| } |
| |
| // Initialize the accumulators |
| TILE(ACC_DATA_TYPE, M0, N0, c); |
| |
| LOOP_UNROLLING(int, i, 0, M0, 1) |
| { |
| c[i].v = 0; |
| } |
| |
| for(int i = 0; i < (_IWEI_WIDTH * _IWEI_HEIGHT); ++i) |
| { |
| int ck = 0; |
| int xk = i % _IWEI_WIDTH; |
| int yk = i / _IWEI_WIDTH; |
| |
| int k = 0; |
| for(; k <= (_ISRC_CHANNELS - K0); k += K0) |
| { |
| TILE(SRC_DATA_TYPE, M0, K0, a); |
| TILE(WEI_DATA_TYPE, N0, K0, b); |
| |
| LOOP_UNROLLING(int, i, 0, M0, 1) |
| { |
| a[i].v = ZERO_VALUE; |
| } |
| |
| // Load tile from the src tensor |
| T_LOAD_NHWC_INDIRECT(SRC_DATA_TYPE, 1, M0, K0, SRC_TENSOR_TYPE, src, bout, yk, xk, ck, _ISRC_WIDTH, _ISRC_HEIGHT, src_stride_y, xi, yi, a); |
| |
| // Load tile from the weights tensor |
| T_LOAD(WEI_DATA_TYPE, N0, K0, WEI_TENSOR_TYPE, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); |
| |
| // Compute the matrix multiplication between two tiles |
| T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, K0, NT, T, a, b, c); |
| |
| // Apply the offset correction (correction usually needed for asymmetric quantized computation) |
| // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero |
| T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, K0, SRC_OFFSET, WEI_OFFSET, a, b, c); |
| |
| ck += K0; |
| } |
| |
| // We voluntarily use SRC_CHANNELS rather than _DSRC_CHANNELS |
| // This #if directive should be removed in case of dynamic tensor support |
| #if((SRC_CHANNELS % K0) != 0) |
| // Left-over accumulations |
| for(; k < _ISRC_CHANNELS; ++k) |
| { |
| TILE(SRC_DATA_TYPE, M0, 1, a); |
| TILE(WEI_DATA_TYPE, N0, 1, b); |
| |
| LOOP_UNROLLING(int, i, 0, M0, 1) |
| { |
| a[i].v = ZERO_VALUE; |
| } |
| |
| // Load tile from the src tensor |
| T_LOAD_NHWC_INDIRECT(SRC_DATA_TYPE, 1, M0, 1, SRC_TENSOR_TYPE, src, bout, yk, xk, ck, _ISRC_WIDTH, _ISRC_HEIGHT, src_stride_y, xi, yi, a); |
| |
| // Load tile from the weights tensor |
| // The T_LOAD for the left-over elements can only use BUFFER because we load one element per iteration |
| T_LOAD(WEI_DATA_TYPE, N0, 1, BUFFER, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); |
| |
| // Compute the matrix multiplication between two tiles |
| T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, 1, NT, T, a, b, c); |
| |
| // Apply the offset correction (operation usually needed for asymmetric quantized computation) |
| // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero |
| T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, 1, SRC_OFFSET, WEI_OFFSET, a, b, c); |
| |
| ++ck; |
| } |
| #endif // ((SRC_CHANNELS % K0) != 0) |
| } |
| |
| // Offset correction required for the quantized asymmetric computation |
| // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero |
| T_ADD_CONSTANT(ACC_DATA_TYPE, M0, N0, c, (_IWEI_WIDTH * _IWEI_HEIGHT * _ISRC_CHANNELS * SRC_OFFSET * WEI_OFFSET), c); |
| |
| #if defined(HAS_BIAS) |
| TILE(BIA_DATA_TYPE, 1, N0, bias0); |
| |
| T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout, 0, 1, 0, bias0); |
| |
| // c = c + bias[broadcasted] |
| T_ADD_BROADCAST_X(ACC_DATA_TYPE, M0, N0, c, bias0, c); |
| |
| #endif // HAS_BIAS |
| |
| TILE(uint, M0, 1, dst_indirect_y); |
| |
| // Calculate the destination indirect Y |
| LOOP_UNROLLING(int, i, 0, M0, 1) |
| { |
| dst_indirect_y[i].v = (uint)min(mout + i, (int)(_IDST_WIDTH * _IDST_HEIGHT) - 1); |
| dst_indirect_y[i].v += bout * (int)(_IDST_WIDTH * _IDST_HEIGHT); |
| } |
| |
| bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0; |
| |
| #if defined(IS_QUANTIZED) |
| |
| TILE(DST_DATA_TYPE, M0, N0, cq); |
| |
| // Quantize the tile |
| T_QUANTIZE8_ASYMMETRIC(ACC_DATA_TYPE, DST_DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, cq); |
| #endif // defined(IS_QUANTIZED) |
| |
| // _IOUTPUT_TILE: c = fp32/fp16, cq=qasymm8 |
| // Store the tile in reverse order so the invalid values are overwritten with the valid ones |
| T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, M0, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, _IOUTPUT_TILE, dst_indirect_y); |
| |
| #undef _IWEI_WIDTH |
| #undef _IWEI_HEIGHT |
| #undef _ISRC_WIDTH |
| #undef _ISRC_HEIGHT |
| #undef _ISRC_CHANNELS |
| #undef _IDST_WIDTH |
| #undef _IDST_HEIGHT |
| #undef _IDST_CHANNELS |
| #undef _IY_MULTIPLIER |
| } |