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authorManuel Bottini <manuel.bottini@arm.com>2021-04-08 12:50:12 +0100
committerManuel Bottini <manuel.bottini@arm.com>2021-04-14 10:37:16 +0000
commit21c28957f9c6fe1a28ef934e711bb7474b8d65ee (patch)
tree220293c48b9705ed8a9a828825503442f414672d /src/core/CL/cl_kernels/normalization_layer.cl
parent91b7f7423a97f0ae713a13182f289621dad17c43 (diff)
downloadComputeLibrary-21c28957f9c6fe1a28ef934e711bb7474b8d65ee.tar.gz
Remove OpenCL padding: CLNormalizationLayerKernel
Only for NHWC data layout Resolves: COMPMID-3910 Change-Id: Ie2d71482b3e3b55ac155e9af152032a5de8bbd50 Signed-off-by: Manuel Bottini <manuel.bottini@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5388 Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/normalization_layer.cl')
-rw-r--r--src/core/CL/cl_kernels/normalization_layer.cl145
1 files changed, 105 insertions, 40 deletions
diff --git a/src/core/CL/cl_kernels/normalization_layer.cl b/src/core/CL/cl_kernels/normalization_layer.cl
index ff4dc8ec38..4569208824 100644
--- a/src/core/CL/cl_kernels/normalization_layer.cl
+++ b/src/core/CL/cl_kernels/normalization_layer.cl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -22,6 +22,7 @@
* SOFTWARE.
*/
#include "helpers.h"
+#include "tile_helpers.h"
#define MUL_OP(x, y) ((x) * (y))
#define ADD_OP(x, y) ((x) + (y))
@@ -29,9 +30,6 @@
#define POW_OP(x, y) pow((x), (y))
#define SQCVT_SAT(a) (a)
-#define LOAD_OP(offset, ptr) vload4(offset, ptr)
-#define STORE_OP(data, offset, ptr) vstore4(data, offset, ptr)
-
#if defined(NUM_SLICES)
/** Apply cross-map normalization.
*
@@ -58,8 +56,8 @@
* @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
*/
-__kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
- TENSOR3D_DECLARATION(output))
+__kernel void normalization_layer_cross_map_nchw(TENSOR3D_DECLARATION(input),
+ TENSOR3D_DECLARATION(output))
{
Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
@@ -80,7 +78,7 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
for(int i = left_slice; i <= right_slice; i++)
{
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i));
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i));
acc = ADD_OP(acc, MUL_OP(values, values));
}
@@ -88,19 +86,84 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
+ normalized_pixel = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized);
- STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+ VSTORE(VEC_SIZE)
+ (normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
}
#endif /* defined(NUM_SLICES) */
#if defined(WIDTH_SIZE)
+/** Apply cross-map normalization.
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
+ * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
+ * @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192
+ * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
+ *
+ * @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
+ */
+__kernel void normalization_layer_cross_map_nhwc(TENSOR3D_DECLARATION(input),
+ TENSOR3D_DECLARATION(output))
+{
+ // Offset computation
+ const uint x_offs = GET_SPATIAL_IDX(0, VEC_SIZE, VEC_SIZE_LEFTOVER);
+
+ // Address computation
+ __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + get_global_id(1) * input_stride_y + get_global_id(2) * input_stride_z;
+ __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y + get_global_id(2) * output_stride_z;
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ acc = 0;
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ coeff_v = SQCVT_SAT(COEFF);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ beta_v = SQCVT_SAT(BETA);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ kappa_v = SQCVT_SAT(KAPPA);
+
+ const int left_slice = max((int)0, (int)x_offs - (int)RADIUS);
+ const int right_slice = min((int)WIDTH_SIZE - 1, (int)x_offs + (int)RADIUS);
+
+ for(int i = left_slice; i <= right_slice; ++i)
+ {
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + i * sizeof(DATA_TYPE)));
+ acc = ADD_OP(acc, MUL_OP(values, values));
+ }
+
+ acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ normalized = POW_OP(acc, beta_v);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ normalized_pixel0 = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + x_offs * sizeof(DATA_TYPE))), normalized);
+
+ STORE_VECTOR_SELECT(normalized_pixel, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0);
+}
+
/** Apply in-map normalization when tensors are in the NCHW data layout format.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
* @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
* @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
* @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
+ * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER is; x_dimension % VEC_SIZE. e.g. -DVEC_SIZE_LEFTOVER=1
*
* @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)
@@ -126,13 +189,13 @@ __kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
+ acc = 0;
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
+ coeff_v = SQCVT_SAT(COEFF);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
+ beta_v = SQCVT_SAT(BETA);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
+ kappa_v = SQCVT_SAT(KAPPA);
const int current_col = get_global_id(0) << 2;
const int left_pos = max(-(int)RADIUS, -3 - current_col);
@@ -152,10 +215,10 @@ __kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
{
#if defined(IN_MAP_2D)
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, j, 0));
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, j, 0));
#else /* defined(IN_MAP_2D) */
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, 0, 0));
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, 0, 0));
#endif /* defined(IN_MAP_2D) */
acc = ADD_OP(acc, MUL_OP(values, values));
}
@@ -167,13 +230,14 @@ __kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
+ normalized_pixel = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized);
- STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+ VSTORE(VEC_SIZE)
+ (normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
}
#endif // defined(WIDTH_SIZE)
-#if defined(NUM_SLICES)
+#if defined(NUM_SLICES) && defined(DIM1_SIZE)
/** Apply in-map normalization when tensors are in the NHWC data layout format.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
@@ -202,42 +266,43 @@ __kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
__kernel void normalization_layer_in_map_nhwc(TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
- Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
- Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+ // Offset computation
+ const uint x_offs = GET_SPATIAL_IDX(0, VEC_SIZE, VEC_SIZE_LEFTOVER);
+ const int current_cols = get_global_id(1);
+ const int current_rows = get_global_id(2);
+
+ // Address computation
+ __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE);
+ __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + current_cols * output_stride_y + current_rows * output_stride_z;
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
+ acc = 0;
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
+ coeff_v = SQCVT_SAT(COEFF);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
+ beta_v = SQCVT_SAT(BETA);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
+ kappa_v = SQCVT_SAT(KAPPA);
- const int current_cols = get_global_id(1);
- const int first_col = max(-(int)RADIUS, -current_cols);
- const int last_col = min((int)RADIUS, (int)get_global_size(1) - 1 - current_cols);
+ const int first_col = max(0, current_cols - (int)RADIUS);
+ const int last_col = min((int)DIM1_SIZE - 1, current_cols + (int)RADIUS);
#if defined(IN_MAP_2D)
- const int current_rows = get_global_id(2);
- const int first_row = max(-(int)RADIUS, -current_rows);
- const int last_row = min((int)RADIUS, (int)NUM_SLICES - 1 - current_rows);
+ const int first_row = max(0, current_rows - (int)RADIUS);
+ const int last_row = min((int)NUM_SLICES - 1, current_rows + (int)RADIUS);
#endif /* defined(IN_MAP_2D) */
#if defined(IN_MAP_2D)
for(int j = first_row; j <= last_row; ++j)
{
+#else // defined(IN_MAP_2D)
+ const int j = current_rows;
#endif /* defined(IN_MAP_2D) */
for(int i = first_col; i <= last_col; ++i)
{
-#if defined(IN_MAP_2D)
- VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, j));
-#else /* defined(IN_MAP_2D) */
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, 0));
-#endif /* defined(IN_MAP_2D) */
- acc = ADD_OP(acc, MUL_OP(values, values));
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + i * input_stride_y + j * input_stride_z));
+ acc = ADD_OP(acc, MUL_OP(values, values));
}
#if defined(IN_MAP_2D)
}
@@ -247,8 +312,8 @@ __kernel void normalization_layer_in_map_nhwc(TENSOR3D_DECLARATION(input),
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
- normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
+ normalized_pixel0 = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + current_cols * output_stride_y + current_rows * output_stride_z)), normalized);
- STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+ STORE_VECTOR_SELECT(normalized_pixel, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0);
}
-#endif /* defined(NUM_SLICES) */
+#endif // defined(NUM_SLICES) && defined(DIM1_SIZE) \ No newline at end of file