/* * Copyright (c) 2017 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" /** Apply batch normalization. * * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F32 * @param[in] input_stride_x Stride of the first 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 first 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 first 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_offset_first_element_in_bytes The offset of the first element in the first source tensor * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32 * @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_offset_first_element_in_bytes The offset of the first element in the destination tensor * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: F32 * @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: F32 * @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[in] beta_ptr Pointer to the beta source tensor. Supported data types: F32 * @param[in] beta_stride_x Stride of the beta source tensor in X dimension (in bytes) * @param[in] beta_step_x beta_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] beta_offset_first_element_in_bytes The offset of the first element in the beta source tensor * @param[in] gamma_ptr Pointer to the gamma source tensor. Supported data types: F32 * @param[in] gamma_stride_x Stride of the gamma source tensor in X dimension (in bytes) * @param[in] gamma_step_x gamma_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] gamma_offset_first_element_in_bytes The offset of the first element in the gamma source tensor * @param[in] epsilon Epsilon parameter in the batch normalization equation */ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output), VECTOR_DECLARATION(mean), VECTOR_DECLARATION(var), VECTOR_DECLARATION(beta), VECTOR_DECLARATION(gamma), float epsilon) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); Vector var = CONVERT_TO_VECTOR_STRUCT(var); Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); Vector gamma = CONVERT_TO_VECTOR_STRUCT(gamma); float4 _in = 0; float4 denominator = 0; float4 numerator = 0; float4 x_bar = 0; float4 gamma_vec = 0; float4 beta_vec = 0; const int current_slice = get_global_id(2); _in = vload4(0, (__global float *)in.ptr); denominator = *((__global float *)(var.ptr + current_slice * var.stride_x)); denominator = rsqrt(denominator + epsilon); // Calculate x bar and store results numerator = *((__global float *)(mean.ptr + current_slice * mean.stride_x)); numerator = _in - numerator; x_bar = numerator * denominator; gamma_vec = *((__global float *)(gamma.ptr + current_slice * beta.stride_x)); beta_vec = *((__global float *)(beta.ptr + current_slice * beta.stride_x)); vstore4(gamma_vec * x_bar + beta_vec, 0, (__global float *)out.ptr); }