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Diffstat (limited to 'src/core/CL/cl_kernels/nchw/batchnormalization_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nchw/batchnormalization_layer.cl | 147 |
1 files changed, 147 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nchw/batchnormalization_layer.cl b/src/core/CL/cl_kernels/nchw/batchnormalization_layer.cl new file mode 100644 index 0000000000..2d466661b3 --- /dev/null +++ b/src/core/CL/cl_kernels/nchw/batchnormalization_layer.cl @@ -0,0 +1,147 @@ +/* + * 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)*/
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