| /* |
| * Copyright (c) 2017-2019 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, res, A_VAL, B_VAL); |
| |
| VSTORE(VEC_SIZE) |
| (res, 0, (__global DATA_TYPE *)out.ptr); |
| } |
| |
| /** Apply batch normalization on tensors with NHWC format. |
| * |
| * @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_nhwc(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(0); |
| |
| data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr); |
| denominator = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(var.ptr + current_slice * VEC_SIZE * 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 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(mean.ptr + current_slice * VEC_SIZE * 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 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(gamma.ptr + current_slice * VEC_SIZE * 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 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(beta.ptr + current_slice * VEC_SIZE * 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, 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)*/ |
| |
| #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) |
