diff options
Diffstat (limited to 'src/core/CL/cl_kernels/instance_normalization.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/instance_normalization.cl | 48 |
1 files changed, 23 insertions, 25 deletions
diff --git a/src/core/CL/cl_kernels/instance_normalization.cl b/src/core/CL/cl_kernels/instance_normalization.cl index de7d57c69e..043012bc51 100644 --- a/src/core/CL/cl_kernels/instance_normalization.cl +++ b/src/core/CL/cl_kernels/instance_normalization.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2019-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -23,7 +23,7 @@ */ #include "helpers.h" -#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) +#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(INTERNAL_DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) /** This function normalizes the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension. * * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 @@ -63,8 +63,8 @@ __kernel void instance_normalization( Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); #endif /* IN_PLACE */ - float sum = 0.f; - float sum_sq = 0.f; + INTERNAL_DATA_TYPE sum = 0.f; + INTERNAL_DATA_TYPE sum_sq = 0.f; #if defined(NHWC) @@ -76,7 +76,7 @@ __kernel void instance_normalization( { for(int i_h = 0; i_h < DIM_Z; ++i_h) { - float data = (float) * ((__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch)); + INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE) * ((__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch)); sum += data; sum_sq += data * data; } @@ -87,9 +87,9 @@ __kernel void instance_normalization( const int batch = get_global_id(2) / DIM_Z; // Current batch const int elements_plane = DIM_X * DIM_Y; - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) part_sum = 0.f; - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) part_sum_sq = 0.f; // Calculate partial sum for(int y = 0; y < DIM_Y; ++y) @@ -98,15 +98,15 @@ __kernel void instance_normalization( for(; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE) { // Load data - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)); + VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) + data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)), VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)); part_sum += data; part_sum_sq += data * data; } // Left-overs loop for(; x < DIM_X; ++x) { - DATA_TYPE data = *((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)); + INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE)(*((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch))); part_sum.s0 += data; part_sum_sq.s0 += data * data; } @@ -127,16 +127,14 @@ __kernel void instance_normalization( part_sum.s0 += part_sum.s1; part_sum_sq.s0 += part_sum_sq.s1; - sum = (float)part_sum.s0; - sum_sq = (float)part_sum_sq.s0; + sum = (INTERNAL_DATA_TYPE)part_sum.s0; + sum_sq = (INTERNAL_DATA_TYPE)part_sum_sq.s0; #endif // defined(NHWC) - const float mean_float = (sum / elements_plane); - const DATA_TYPE mean = (DATA_TYPE)mean_float; - const float var_float = (sum_sq / elements_plane) - (mean_float * mean_float); - const float multip_float = GAMMA / sqrt(var_float + EPSILON); - const DATA_TYPE multip = (DATA_TYPE)multip_float; + const INTERNAL_DATA_TYPE mean = (sum / elements_plane); + const INTERNAL_DATA_TYPE var = (sum_sq / elements_plane) - (mean * mean); + const INTERNAL_DATA_TYPE multip = GAMMA / sqrt(var + EPSILON); #if defined(NHWC) @@ -150,7 +148,7 @@ __kernel void instance_normalization( #else /* !IN_PLACE */ __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, ch, i_w, i_h, batch); #endif /* IN_PLACE */ - *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA; + *(output_address) = (*(input_address) - mean) * multip + (INTERNAL_DATA_TYPE)BETA; } } @@ -167,13 +165,13 @@ __kernel void instance_normalization( __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch); #endif /* IN_PLACE */ - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - data = VLOAD(VEC_SIZE)(0, input_address); + VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) + data = CONVERT(VLOAD(VEC_SIZE)(0, input_address), VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)); - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - res = (data - mean) * multip + (DATA_TYPE)BETA; + VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) + res = (data - mean) * multip + (INTERNAL_DATA_TYPE)BETA; VSTORE(VEC_SIZE) - (res, 0, output_address); + (CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)), 0, output_address); } // Left-overs loop for(; x < DIM_X; ++x) @@ -184,9 +182,9 @@ __kernel void instance_normalization( #else /* !IN_PLACE */ __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch); #endif /* IN_PLACE */ - *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA; + *(output_address) = (*(input_address) - mean) * multip + (INTERNAL_DATA_TYPE)BETA; } } #endif // defined(NHWC) } -#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */ +#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(INTERNAL_DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */ |