icemelon9 commented on a change in pull request #4312: [TOPI][Relay][OP]
Dynamic NMS and strided_slice
URL: https://github.com/apache/incubator-tvm/pull/4312#discussion_r345394342
##########
File path: topi/python/topi/vision/nms.py
##########
@@ -366,17 +551,33 @@ def non_max_suppression(data, valid_count,
max_output_size=-1,
score_shape = (batch_size, num_anchors)
score_tensor = tvm.compute(score_shape, lambda i, j: data[i, j,
score_axis])
sort_tensor = argsort(score_tensor, valid_count=valid_count, axis=1,
is_ascend=False)
- out, box_indices = hybrid_nms(data, sort_tensor, valid_count,
- tvm.const(max_output_size, dtype="int32"),
- tvm.const(iou_threshold, dtype=data.dtype),
- tvm.const(force_suppress, dtype="bool"),
- tvm.const(top_k, dtype="int32"),
- tvm.const(coord_start, dtype="int32"),
- tvm.const(id_index, dtype="int32"),
- tvm.const(score_index, dtype="int32"),
- zero=tvm.const(0, dtype=data.dtype),
- one=tvm.const(1, dtype=data.dtype))
- if not return_indices and invalid_to_bottom:
- out = hybrid_rearrange_out(out, one=tvm.const(1, dtype=data.dtype))
-
- return box_indices if return_indices else out
+
+ if return_indices:
+ # return a tuple with two tensor, one is the computed valid indices of
boxes, appending -1 as invalid boxes
+ # the other one is the number of valid boxes
+ out, box_indices = hybrid_dynamic_nms(data,
+ sort_tensor,
+ tvm.const(max_output_size,
dtype="int32"),
+ tvm.const(score_threshold,
dtype=data.dtype),
+ tvm.const(iou_threshold,
dtype=data.dtype),
+ tvm.const(score_index,
dtype="int32"),
+ zero=tvm.const(0,
dtype=data.dtype),
+ one=tvm.const(1,
dtype=data.dtype))
+ box_indices, out_shape = hybrid_rearrange_idx(box_indices)
+ return [box_indices, out_shape]
Review comment:
Use tuple here
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