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/common/convolution_layer.cl b/src/core/CL/cl_kernels/common/convolution_layer.cl
new file mode 100644
index 0000000..be76929
--- /dev/null
+++ b/src/core/CL/cl_kernels/common/convolution_layer.cl
@@ -0,0 +1,112 @@
+/*
+ * 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"
+
+#if defined(DATA_TYPE) && defined(NUM_GROUPS)
+/** This kernel reshapes the tensor's low three dimensions to single column
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
+ * @note The number of groups should be given as a preprocessor argument using -DNUM_GROUPS=number. e.g. -DNUM_GROUPS=2
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: All
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in] bias_ptr Pointer to the bias tensor. Supported data types: F16/F32, for quantized types this must be nullptr
+ * @param[in] bias_stride_x Stride of the bias tensor in X dimension (in bytes)
+ * @param[in] bias_step_x bias_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] bias_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[in] width The width of the input tensor
+ * @param[in] height The height of the input tensor
+ * @param[in] depth The depth of the input tensor
+ * @param[in] total_filters Total number of filters. 4th dimension of the weights matrix
+ * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ */
+__kernel void reshape_to_columns(
+ TENSOR3D_DECLARATION(src),
+ IMAGE_DECLARATION(dst),
+#ifdef HAS_BIAS
+ VECTOR_DECLARATION(bias),
+#endif /* HAS_BIAS */
+ uint width, uint height, uint depth, uint total_filters, uint dst_stride_z)
+{
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ bool is_last_thread = (get_global_id(0) == (get_global_size(0) - 1) && get_global_id(1) == (get_global_size(1) - 1) && get_global_id(2) == (get_global_size(2) - 1));
+
+ __global uchar *tmp_src_ptr = src.ptr;
+ __global uchar *tmp_dst_ptr = dst_ptr + dst_offset_first_element_in_bytes + get_global_id(0) * dst_stride_y + get_global_id(1) * width * dst_stride_y + get_global_id(
+ 2) * width * height * dst_stride_y;
+#ifdef HAS_BIAS
+ __global uchar *tmp_bias_ptr = bias_ptr + bias_offset_first_element_in_bytes;
+#endif /* HAS_BIAS */
+
+ if(is_last_thread)
+ {
+ for(uint g = 0; g < NUM_GROUPS; ++g)
+ {
+ __global uchar *curr_group_dst = tmp_dst_ptr;
+
+ for(uint i = 0; i < total_filters / NUM_GROUPS; ++i)
+ {
+ *((__global DATA_TYPE *)curr_group_dst) = *((__global DATA_TYPE *)tmp_src_ptr);
+
+#ifdef HAS_BIAS
+ *((__global DATA_TYPE *)(curr_group_dst + dst_stride_y)) = *((__global DATA_TYPE *)(tmp_bias_ptr));
+ tmp_bias_ptr += bias_stride_x;
+#endif /* HAS_BIAS */
+ tmp_src_ptr += depth * src_stride_z;
+ curr_group_dst += dst_stride_x;
+ }
+
+ tmp_dst_ptr += dst_stride_z;
+ }
+ }
+ else
+ {
+ for(uint g = 0; g < NUM_GROUPS; ++g)
+ {
+ __global uchar *curr_group_dst = tmp_dst_ptr;
+
+ for(uint i = 0; i < total_filters / NUM_GROUPS; ++i)
+ {
+ *((__global DATA_TYPE *)curr_group_dst) = *((__global DATA_TYPE *)tmp_src_ptr);
+ tmp_src_ptr += depth * src_stride_z;
+ curr_group_dst += dst_stride_x;
+ }
+
+ tmp_dst_ptr += dst_stride_z;
+ }
+ }
+}
+#endif // defined(DATA_TYPE)