trevor-m commented on a change in pull request #8174:
URL: https://github.com/apache/tvm/pull/8174#discussion_r644172454
##########
File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -793,6 +793,92 @@ def _impl(inputs, attr, params, mod):
return _impl
+def convert_combined_nms_with_all_class_nms(
+ batch_size,
+ max_output_boxes_per_batch,
+ num_class,
+ boxes,
+ scores,
+ max_output_boxes_per_class,
+ iou_threshold,
+ score_threshold,
+ max_total_size,
+ clip_boxes,
+):
+ """Converts TF combined_nms using Relay all_class_max_suppression op"""
+ (selected_indices, selected_scores, num_detections,) =
_op.vision.all_class_non_max_suppression(
+ boxes,
+ scores,
+ max_output_boxes_per_class,
+ iou_threshold,
+ score_threshold,
+ output_format="tensorflow",
+ )
+ box_range = _op.arange(
+ _op.const(0, dtype="int64"), _op.const(max_total_size, dtype="int64"),
dtype="int64"
+ )
+ tile_batch_reps = (
+ _op.concatenate([batch_size, 1], axis=0)
Review comment:
I think if batch_size is an instance of relay.Any() we cannot use
batch_size directly here, we need to get the symbolic batch size tensor with
`_op.shape_of`.
Could we add a test which has a dynamic batch dimension? If it's too
difficult, we can defer to later, since the models I have looked at don't use
dynamic batch size for NMS.
##########
File path: python/tvm/topi/transform.py
##########
@@ -483,7 +483,7 @@ def gather(data, axis, indices):
return cpp.gather(data, axis, indices)
-def gather_nd(a, indices):
+def gather_nd(a, indices, batch_dims=0):
Review comment:
Are the gather_nd changes used in this PR?
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