masahi commented on a change in pull request #8174:
URL: https://github.com/apache/tvm/pull/8174#discussion_r644302217
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File path: python/tvm/relay/frontend/tensorflow.py
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@@ -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:
oops you are right. Actually the existing converter does not seem to
support both dynamic batch and num boxes either:
https://github.com/apache/tvm/blob/6baccc1305b13f18ce8ac5db5fcbbadb8c278454/python/tvm/relay/frontend/tensorflow.py#L827-L828
So I'll just add an assertion to check if batch_size and num_boxes are
integers and raise an error otherwise.
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