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Diffstat (limited to 'src/core/CL/cl_kernels/common/batchnormalization_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/common/batchnormalization_layer.cl | 183 |
1 files changed, 183 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/common/batchnormalization_layer.cl b/src/core/CL/cl_kernels/common/batchnormalization_layer.cl new file mode 100644 index 0000000000..18f54907df --- /dev/null +++ b/src/core/CL/cl_kernels/common/batchnormalization_layer.cl @@ -0,0 +1,183 @@ +/* + * 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)
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