COMPMID-1330: Add support for NormalizePlanarYUV operator in CL
Change-Id: Id0754b9e2bc3ef7ff2c4c21c3b89709588c41bd3
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146637
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
diff --git a/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl b/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl
new file mode 100644
index 0000000..dc66524
--- /dev/null
+++ b/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl
@@ -0,0 +1,134 @@
+/*
+ * Copyright (c) 2018 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(VEC_SIZE)
+
+#define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+
+/** Apply normalize_planar_yuv layer on tensors with NCHW format.
+ *
+ * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8
+ * @note The depth of the input tensor should be given as a preprocessor argument using -DNUM_CHANNELS e.g. -DNUM_CHANNELS=8
+ *
+ * @param[in] src_ptr Pointer to the first source tensor. Supported data types: F16/F32
+ * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes)
+ * @param[in] src_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: 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 output_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 output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z output_stride_z * number of elements along Z 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] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p src_ptr
+ * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes)
+ * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor
+ * @param[in] std_ptr Pointer to the std tensor. Supported data types: same as @p src_ptr
+ * @param[in] std_stride_x Stride of the std tensor in X dimension (in bytes)
+ * @param[in] std_step_x std_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] std_offset_first_element_in_bytes The offset of the first element in the var source tensor
+ */
+__kernel void normalize_planar_yuv_layer_nchw(TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst),
+ VECTOR_DECLARATION(mean),
+ VECTOR_DECLARATION(std))
+{
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
+ Vector mean = CONVERT_TO_VECTOR_STRUCT(mean);
+ Vector std = CONVERT_TO_VECTOR_STRUCT(std);
+
+ const uint current_slice = get_global_id(2) % NUM_CHANNELS;
+
+ const DATA_TYPE curr_mean = *((__global DATA_TYPE *)(mean.ptr + current_slice * mean.stride_x));
+ const DATA_TYPE curr_std = *((__global DATA_TYPE *)(std.ptr + current_slice * std.stride_x));
+
+ TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr);
+ TYPE res = (data - curr_mean) / curr_std;
+
+ VSTORE(VEC_SIZE)
+ (res, 0, (__global DATA_TYPE *)dst.ptr);
+}
+
+/** Apply normalize_planar_yuv layer on tensors with NHWC format.
+ *
+ * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8
+ *
+ * @param[in] src_ptr Pointer to the first source tensor. Supported data types: F16/F32
+ * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes)
+ * @param[in] src_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: 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 output_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 output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z output_stride_z * number of elements along Z 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] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p src_ptr
+ * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes)
+ * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor
+ * @param[in] std_ptr Pointer to the std tensor. Supported data types: same as @p src_ptr
+ * @param[in] std_stride_x Stride of the std tensor in X dimension (in bytes)
+ * @param[in] std_step_x std_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] std_offset_first_element_in_bytes The offset of the first element in the var source tensor
+ */
+__kernel void normalize_planar_yuv_layer_nhwc(TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst),
+ VECTOR_DECLARATION(mean),
+ VECTOR_DECLARATION(std))
+{
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
+ Vector mean = CONVERT_TO_VECTOR_STRUCT(mean);
+ Vector std = CONVERT_TO_VECTOR_STRUCT(std);
+
+ const uint current_slice = get_global_id(0);
+
+ const TYPE curr_mean = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(mean.ptr + current_slice * VEC_SIZE * mean.stride_x));
+ const TYPE curr_std = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(std.ptr + current_slice * VEC_SIZE * std.stride_x));
+
+ TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr);
+ TYPE res = (data - curr_mean) / curr_std;
+
+ VSTORE(VEC_SIZE)
+ (res, 0, (__global DATA_TYPE *)dst.ptr);
+}
+#endif // defined(DATA_TYPE) && defined(VEC_SIZE)