COMPMID-1677: Change ROIPooling layer interface to accept ROIs as tensors
Change-Id: If16b572a4d906187b77f32133a72a44316fa74e4
Reviewed-on: https://review.mlplatform.org/490
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/core/CL/cl_kernels/roi_pooling_layer.cl b/src/core/CL/cl_kernels/roi_pooling_layer.cl
index 042b102..0cf296c 100644
--- a/src/core/CL/cl_kernels/roi_pooling_layer.cl
+++ b/src/core/CL/cl_kernels/roi_pooling_layer.cl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -105,10 +105,12 @@
* @param[in] input_stride_z Stride of the 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 pooled region of the source image as specifed by ROI
- * @param[in] rois_ptr Pointer to the rois array. Layout: {x, y, width, height, batch_indx}
- * @param[in] rois_stride_x Stride of the rois array in X dimension (in bytes)
- * @param[in] rois_step_x rois_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the rois array
+ * @param[in] rois_ptr Pointer to the ROIs tensor. Layout: { batch_index, x1, y1, x2, y2 }. Supported data types: same as @p input_ptr
+ * @param[in] rois_stride_x Stride of the ROIs tensor in X dimension (in bytes)
+ * @param[in] rois_step_x Step of the ROIs tensor in X dimension (in bytes)
+ * @param[in] rois_stride_y Stride of the ROIs tensor in Y dimension (in bytes)
+ * @param[in] rois_step_y Step of the ROIs tensor in Y dimension (in bytes)
+ * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the ROIs tensor
* @param[out] output_ptr Pointer to the destination image. Supported data types: F16, F32
* @param[in] output_stride_x Stride of the destination image in X dimension (in bytes)
* @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
@@ -122,13 +124,13 @@
*/
__kernel void roi_pooling_layer(
TENSOR3D_DECLARATION(input),
- VECTOR_DECLARATION(rois),
+ IMAGE_DECLARATION(rois),
TENSOR3D_DECLARATION(output),
unsigned int input_stride_w, unsigned int output_stride_w)
{
// Get pixels pointer
Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(input);
- Vector rois = CONVERT_TO_VECTOR_STRUCT_NO_STEP(rois);
+ Image rois = CONVERT_TO_IMAGE_STRUCT_NO_STEP(rois);
Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output);
const int px = get_global_id(0);
@@ -136,12 +138,12 @@
const int pw = get_global_id(2);
// Load roi parameters
- // roi is laid out as follows:
- // { x, y, width, height, batch_index }
- const ushort4 roi = vload4(0, (__global ushort *)vector_offset(&rois, pw));
- const ushort roi_batch = *((__global ushort *)vector_offset(&rois, pw) + 4);
- const int2 roi_anchor = convert_int2_sat(round(convert_float2(roi.s01) * (float)SPATIAL_SCALE));
- const int2 roi_dims = convert_int2_sat(fmax(round(convert_float2(roi.s23) * (float)SPATIAL_SCALE), 1.f));
+ // roi is laid out as follows { batch_index, x1, y1, x2, y2 }
+ const ushort roi_batch = (ushort) * ((__global DATA_TYPE *)offset(&rois, 0, pw));
+ const VEC_DATA_TYPE(DATA_TYPE, 4)
+ roi = vload4(0, (__global DATA_TYPE *)offset(&rois, 1, pw));
+ const int2 roi_anchor = convert_int2_sat(round(convert_float2(roi.s01) * (float)SPATIAL_SCALE));
+ const int2 roi_dims = convert_int2_sat(fmax(round(convert_float2(roi.s23 - roi.s01) * (float)SPATIAL_SCALE), 1.f));
// Calculate pooled region start and end
const float2 spatial_indx = (float2)(px, py);