/* * 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(EPSILON) /** OpenCL kernel to fuse the weights of convolution or depthwise convolution layer with batch normalization when the data layout is either NCHW or NHWC * * @note The input weights tensor is assumed 4D with the OFMs in the fourth dimension * @note Data type should be passed at compile time using the -DDATA_TYPE, e.g. -DDATA_TYPE=float * @note The third dimension of the input tensor should be passed at compile time when weights belong to a convolution layer using -DDIM2=size. e.g. -DDIM2=16. * For depthwise convolution weight do not pass DIM2 * @note Data layout NHWC should be passed at compile time with -DNHWC. For data layout NCHW it is not required to pass any parameter * @note Batch normalization epsilon parameter should be passed at compile time using -DEPSILON=value. e.g. -DEPSILON=0.001f * * @param[in] w_ptr Pointer to the weights tensor. Supported data types: F16/F32 * @param[in] w_stride_x Stride of the weights tensor in X dimension (in bytes) * @param[in] w_step_x w_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] w_stride_y Stride of the weights tensor in Y dimension (in bytes) * @param[in] w_step_y w_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] w_stride_z Stride of the weights tensor in Z dimension (in bytes) * @param[in] w_step_z w_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] w_offset_first_element_in_bytes The offset of the first element in the weights tensor * @param[in] b_ptr (Optional) Pointer to the bias tensor. Supported data types: same as @p w_ptr * @param[in] b_stride_x (Optional) Stride of the bias tensor in X dimension (in bytes) * @param[in] b_step_x (Optional) b_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] b_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) * @param[in] b_step_y (Optional) b_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] b_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) * @param[in] b_step_z (Optional) b_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] b_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p w_ptr * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes) * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor * @param[in] var_ptr Pointer to the var tensor. Supported data types: same as @p w_ptr * @param[in] var_stride_x Stride of the var tensor in X dimension (in bytes) * @param[in] var_step_x var_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] var_offset_first_element_in_bytes The offset of the first element in the var source tensor * @param[out] w_fused_ptr (Optional) Pointer to the destination weights tensors. Supported data types: same as @p w_ptr * @param[in] w_fused_stride_x (Optional) Stride of the destination weights tensor in X dimension (in bytes) * @param[in] w_fused_step_x (Optional) w_fused_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] w_fused_stride_y (Optional) Stride of the destination weights tensor in Y dimension (in bytes) * @param[in] w_fused_step_y (Optional) w_fused_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] w_fused_stride_z (Optional) Stride of the destination weights tensor in Z dimension (in bytes) * @param[in] w_fused_step_z (Optional) w_fused_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] w_fused_offset_first_element_in_bytes (Optional) The offset of the first element in the destination weights tensor * @param[in] b_fused_ptr (Optional) Pointer to the destination bias tensor. Supported data types: same as @p w_ptr * @param[in] b_fused_stride_x (Optional) Stride of the destination bias tensor in X dimension (in bytes) * @param[in] b_fused_step_x (Optional) b_fused_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] b_fused_offset_first_element_in_bytes (Optional) The offset of the first element in the destination bias tensor * @param[in] beta_ptr (Optional) Pointer to the beta source tensor. Supported data types: same as @p w_ptr * @param[in] beta_stride_x (Optional) Stride of the beta source tensor in X dimension (in bytes) * @param[in] beta_step_x (Optional) beta_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] beta_offset_first_element_in_bytes (Optional) The offset of the first element in the beta source tensor * @param[in] gamma_ptr (Optional) Pointer to the gamma source tensor. Supported data types: same as @p w_ptr * @param[in] gamma_stride_x (Optional) Stride of the gamma source tensor in X dimension (in bytes) * @param[in] gamma_step_x (Optional) gamma_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] gamma_offset_first_element_in_bytes (Optional) The offset of the first element in the gamma source tensor */ __kernel void fuse_batchnormalization_layer(TENSOR3D_DECLARATION(w), #if defined(BIAS) VECTOR_DECLARATION(b), #endif // defined(BIAS) VECTOR_DECLARATION(mean), VECTOR_DECLARATION(var) #ifndef IN_PLACE_W , TENSOR3D_DECLARATION(w_fused) #endif // ifndef IN_PLACE_W #ifndef IN_PLACE_B , VECTOR_DECLARATION(b_fused) #endif // ifndef IN_PLACE_B #if defined(BETA) , VECTOR_DECLARATION(beta) #endif // defined(BETA) #if defined(GAMMA) , VECTOR_DECLARATION(gamma) #endif // defined(GAMMA) ) { int x = get_global_id(0); int y = get_global_id(1); int z = get_global_id(2); #if defined(DIM2) int c0 = z % DIM2; int c1 = z / DIM2; #else // ! defined(DIM2) int c0 = 0; #if defined(NHWC) int c1 = x; #else // defined(NHWC) int c1 = z; #endif // defined(NHWC) #endif // defined(DIM2) int w_offset = x * sizeof(DATA_TYPE) + y * w_stride_y + z * w_stride_z; int v_offset = c1 * sizeof(DATA_TYPE); DATA_TYPE w_old = 0.0f; DATA_TYPE b_old = 0.0f; DATA_TYPE w_new = 0.0f; DATA_TYPE b_new = 0.0f; DATA_TYPE gamma = 1.0f; DATA_TYPE mean = 0.0f; DATA_TYPE var = 1.0f; DATA_TYPE beta = 0.0f; w_old = *((__global DATA_TYPE *)(w_ptr + w_offset + w_offset_first_element_in_bytes)); var = *((__global DATA_TYPE *)(var_ptr + v_offset + var_offset_first_element_in_bytes)); mean = *((__global DATA_TYPE *)(mean_ptr + v_offset + mean_offset_first_element_in_bytes)); #if defined(GAMMA) gamma = *((__global DATA_TYPE *)(gamma_ptr + v_offset + gamma_offset_first_element_in_bytes)); #endif // defined(GAMMA) // Compute new weight w_new = (gamma * w_old) / (sqrt(var + EPSILON)); #if defined(IN_PLACE_W) *((__global DATA_TYPE *)(w_ptr + w_offset + w_offset_first_element_in_bytes)) = w_new; #else // defined(IN_PLACE_W) *((__global DATA_TYPE *)(w_fused_ptr + w_offset + w_fused_offset_first_element_in_bytes)) = w_new; #endif // defined(IN_PLACE_W) // Compute bias #if !defined(DIM2) && defined(NHWC) if(z == 0 && y == 0) #else // !defined(DIM2) && defined(NHWC) if(x == 0 && y == 0 && c0 == 0) #endif // !defined(DIM2) && defined(NHWC) { #if defined(BIAS) b_old = *((__global DATA_TYPE *)(b_ptr + v_offset + b_offset_first_element_in_bytes)); #endif // defined(BIAS) #if defined(BETA) beta = *((__global DATA_TYPE *)(beta_ptr + v_offset + beta_offset_first_element_in_bytes)); #endif // defined(BETA) b_new = ((gamma * (b_old - mean)) / (sqrt(var + EPSILON))) + beta; #if defined(BIAS) #if defined(IN_PLACE_B) *((__global DATA_TYPE *)(b_ptr + v_offset + b_offset_first_element_in_bytes)) = b_new; #else // defined(IN_PLACE_B) *((__global DATA_TYPE *)(b_fused_ptr + v_offset + b_fused_offset_first_element_in_bytes)) = b_new; #endif // defined(IN_PLACE_B) #else // defined(BIAS) #ifndef IN_PLACE_B *((__global DATA_TYPE *)(b_fused_ptr + v_offset + b_fused_offset_first_element_in_bytes)) = b_new; #endif // ifndef IN_PLACE_B #endif // defined(BIAS) } } #endif // defined(DATA_TYPE) && defined(EPSILON)