| /* |
| * 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" |
| |
| #define ADD_OP(a, b) ((a) + (b)) |
| #define SUB_OP(a, b) ((a) - (b)) |
| #define MUL_OP(a, b) ((a) * (b)) |
| #define INVSQRT_OP(a) rsqrt((a)) |
| #define SQCVT_SAT(a) (a) |
| |
| #if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(ACTIVATION_TYPE) |
| #include "activation_float_helpers.h" |
| |
| /** Apply batch normalization. |
| * |
| * @note It is possible to select the activation function to apply using -DACTIVATION_TYPE e.g. -DACTIVATION_TYPE=relu |
| * @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively |
| * |
| * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/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: same as @p input_ptr |
| * @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: same as @p input_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 input_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[in] beta_ptr Pointer to the beta source tensor. Supported data types: same as @p input_ptr |
| * @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: same as @p input_ptr |
| * @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_nchw(TENSOR3D_DECLARATION(input), |
| #ifndef IN_PLACE |
| TENSOR3D_DECLARATION(output), |
| #endif /* not IN_PLACE */ |
| VECTOR_DECLARATION(mean), |
| VECTOR_DECLARATION(var), |
| #ifndef USE_DEFAULT_BETA |
| VECTOR_DECLARATION(beta), |
| #endif /* USE_DEFAULT_BETA */ |
| #ifndef USE_DEFAULT_GAMMA |
| VECTOR_DECLARATION(gamma), |
| #endif /* USE_DEFAULT_GAMMA */ |
| float epsilon) |
| { |
| Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); |
| #ifdef IN_PLACE |
| Tensor3D out = in; |
| #else /* IN_PLACE */ |
| Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); |
| #endif /* IN_PLACE */ |
| Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); |
| Vector var = CONVERT_TO_VECTOR_STRUCT(var); |
| #ifndef USE_DEFAULT_BETA |
| Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); |
| #endif /* USE_DEFAULT_BETA */ |
| #ifndef USE_DEFAULT_GAMMA |
| Vector gamma = CONVERT_TO_VECTOR_STRUCT(gamma); |
| #endif /* USE_DEFAULT_GAMMA */ |
| |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| data = 0; |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| denominator = 0; |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| numerator = 0; |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| x_bar = 0; |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| res = 0; |
| |
| const int current_slice = get_global_id(2); |
| |
| data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr); |
| denominator = *((__global DATA_TYPE *)(var.ptr + current_slice * var.stride_x)); |
| denominator = INVSQRT_OP(ADD_OP(denominator, ((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(epsilon)))); |
| |
| // Calculate x bar and store results |
| numerator = *((__global DATA_TYPE *)(mean.ptr + current_slice * mean.stride_x)); |
| numerator = SUB_OP(data, numerator); |
| x_bar = MUL_OP(numerator, denominator); |
| |
| #ifndef USE_DEFAULT_GAMMA |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| gamma_vec = *((__global DATA_TYPE *)(gamma.ptr + current_slice * gamma.stride_x)); |
| |
| res = MUL_OP(gamma_vec, x_bar); |
| #else /* USE_DEFAULT_GAMMA */ |
| // gamma is equal to 1, no need to perform multiplications |
| res = x_bar; |
| #endif /* USE_DEFAULT_GAMMA */ |
| |
| #ifndef USE_DEFAULT_BETA |
| VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) |
| beta_vec = *((__global DATA_TYPE *)(beta.ptr + current_slice * beta.stride_x)); |
| // beta is not zero, hence we need to perform the addition |
| res = ADD_OP(res, beta_vec); |
| #endif /* USE_DEFAULT_BETA */ |
| |
| res = ACTIVATION(ACTIVATION_TYPE, DATA_TYPE, VEC_SIZE, res, A_VAL, B_VAL); |
| |
| VSTORE(VEC_SIZE) |
| (res, 0, (__global DATA_TYPE *)out.ptr); |
| } |
| #endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(DATA_TYPE)*/ |