COMPMID-1277 - Optimizing CLIm2ColKernel for NHWC.
This patch includes:
- Im2Col optimizations for NHWC using a new data layout
- Refactoring of CLIm2ColKernel adding validation method and auto-init
- Removed im2col_reduced from CLIm2ColKernel and created a new kernel CLFlattenLayerKernel
Change-Id: I1620640b6796baa268324b33ae92cdd8de53e27c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/141241
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
diff --git a/src/core/CL/cl_kernels/convolution_layer.cl b/src/core/CL/cl_kernels/convolution_layer.cl
index 9335b04..2b75b45 100644
--- a/src/core/CL/cl_kernels/convolution_layer.cl
+++ b/src/core/CL/cl_kernels/convolution_layer.cl
@@ -53,7 +53,7 @@
* @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_nchw(
+__kernel void reshape_to_columns(
TENSOR3D_DECLARATION(src),
IMAGE_DECLARATION(dst),
#ifdef HAS_BIAS
@@ -109,74 +109,4 @@
}
}
}
-
-/** 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
- *
- * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32
- * @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. Same as @p src_ptr
- * @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] depth The depth of the input tensor
- * @param[in] width The width of the input tensor
- * @param[in] height The height of the input tensor
- * @param[in] total_filters Total number of filters. 4th dimension of the weights matrix
- */
-__kernel void reshape_to_columns_nhwc(
- TENSOR3D_DECLARATION(src),
- IMAGE_DECLARATION(dst),
-#ifdef HAS_BIAS
- VECTOR_DECLARATION(bias),
-#endif /* HAS_BIAS */
- uint depth, uint width, uint height, 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(1) * dst_stride_y + get_global_id(2) * width * dst_stride_y + get_global_id(
- 0) * 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 i = 0; i < total_filters; ++i)
- {
- *((__global DATA_TYPE *)tmp_dst_ptr) = *((__global DATA_TYPE *)tmp_src_ptr);
-
-#ifdef HAS_BIAS
- *((__global DATA_TYPE *)(tmp_dst_ptr + dst_stride_y)) = *((__global DATA_TYPE *)(tmp_bias_ptr));
- tmp_bias_ptr += bias_stride_x;
-#endif /* HAS_BIAS */
- tmp_src_ptr += height * src_stride_z;
- tmp_dst_ptr += dst_stride_x;
- }
- }
- else
- {
- for(uint i = 0; i < total_filters; ++i)
- {
- *((__global DATA_TYPE *)tmp_dst_ptr) = *((__global DATA_TYPE *)tmp_src_ptr);
- tmp_src_ptr += height * src_stride_z;
- tmp_dst_ptr += dst_stride_x;
- }
- }
-}
-#endif // defined(DATA_TYPE) && defined(NUM_GROUPS)
\ No newline at end of file
+#endif // defined(DATA_TYPE)