Reorganize the kernels into nhwc, nchw and common folders
The Following kernels have been split into nchw/nhwc kernels files:
- batchnormalization_layer
- batch_to_space
- channel_shuffle
- depth_to_space
- dequantization_layer
- im2col
- normalization_layer
- normalize_planar_yuv_layer
- normalize_planar_yuv_layer_quantized
- pooling_layer
- pooling_layer_quantized
- remap
- reorg_layer
- scale
- scale_quantized
- space_to_batch
- space_to_depth
- upsample_layer
- winograd_filter_transform
- winograd_input_transform
- winograd_output_transform
The following kernels have been moved to nchw folder:
- direct_convolution1x1
- direct_convolution3x3
- direct_convolution5x5
- direct_convolution_quantized
- prior_box_layer
The following kernels have been moved to nhwc folder:
- direct_convolution
- dwc_native_fp_nhwc
- dwc_native_quantized_nhwc
The following kernels have been removed:
- sobel_filter
While the rest kerenls have been moved to the common folder.
Partially resolves COMPMID-4453
Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: Ic327ac935687ec351c610c65a3c6357f364a5a58
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5919
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/nchw/normalization_layer.cl b/src/core/CL/cl_kernels/nchw/normalization_layer.cl
new file mode 100644
index 0000000..0fef98e
--- /dev/null
+++ b/src/core/CL/cl_kernels/nchw/normalization_layer.cl
@@ -0,0 +1,175 @@
+/*
+ * 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"
+#include "tile_helpers.h"
+
+#define MUL_OP(x, y) ((x) * (y))
+#define ADD_OP(x, y) ((x) + (y))
+#define DIV_OP(x, y) ((x) / (y))
+#define POW_OP(x, y) pow((x), (y))
+#define SQCVT_SAT(a) (a)
+
+#if defined(NUM_SLICES)
+/** 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_nchw(TENSOR3D_DECLARATION(input),
+ TENSOR3D_DECLARATION(output))
+{
+ Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
+ const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
+
+ const int current_slice = get_global_id(2);
+ const int left_slice = max(-(int)RADIUS, -current_slice);
+ const int right_slice = min((int)RADIUS, (int)NUM_SLICES - 1 - current_slice);
+
+ for(int i = left_slice; i <= right_slice; i++)
+ {
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i));
+ 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_pixel = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized);
+
+ VSTORE(VEC_SIZE)
+ (normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+}
+#endif /* defined(NUM_SLICES) */
+
+#if defined(WIDTH_SIZE)
+/** 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)
+ * @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 first 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 first source 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_in_map_nchw(TENSOR3D_DECLARATION(input),
+ TENSOR3D_DECLARATION(output))
+{
+ Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+ 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 current_col = get_global_id(0) << 2;
+ const int left_pos = max(-(int)RADIUS, -3 - current_col);
+ const int right_pos = min((int)RADIUS, (int)WIDTH_SIZE - 1 - current_col);
+
+#if defined(IN_MAP_2D)
+ const int current_row = get_global_id(1);
+ const int first_row = max(-(int)RADIUS, -current_row);
+ const int last_row = min((int)RADIUS, (int)get_global_size(1) - 1 - current_row);
+#endif /* defined(IN_MAP_2D) */
+
+#if defined(IN_MAP_2D)
+ for(int j = first_row; j <= last_row; ++j)
+ {
+#endif /* defined(IN_MAP_2D) */
+ for(int i = left_pos; i <= right_pos; ++i)
+ {
+#if defined(IN_MAP_2D)
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ 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 = 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));
+ }
+#if defined(IN_MAP_2D)
+ }
+#endif /* defined(IN_MAP_2D) */
+
+ 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_pixel = DIV_OP(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized);
+
+ VSTORE(VEC_SIZE)
+ (normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
+}
+#endif // defined(WIDTH_SIZE)
\ No newline at end of file