FrozenGene commented on a change in pull request #4543: [FRONTEND][TFLITE] Add
support for TFLite_Detection_PostProcess
URL: https://github.com/apache/incubator-tvm/pull/4543#discussion_r372971382
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File path: python/tvm/relay/frontend/tflite.py
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@@ -1662,6 +1667,112 @@ def convert_transpose_conv(self, op):
return out
+ def convert_detection_postprocess(self, op):
+ """Convert TFLite_Detection_PostProcess"""
+ _option_names = [
+ "w_scale",
+ "max_detections",
+ "_output_quantized",
+ "detections_per_class",
+ "x_scale",
+ "nms_score_threshold",
+ "num_classes",
+ "max_classes_per_detection",
+ "use_regular_nms",
+ "y_scale",
+ "h_scale",
+ "_support_output_type_float_in_quantized_op",
+ "nms_iou_threshold"
+ ]
+
+ custom_options = get_custom_options(op, _option_names)
+ if custom_options["use_regular_nms"]:
+ raise tvm.error.OpAttributeUnImplemented(
+ "use_regular_nms=True is not yet supported for operator {}."
+ .format("TFLite_Detection_PostProcess")
+ )
+
+ inputs = self.get_input_tensors(op)
Review comment:
Does it make sense adding one assert `assert len(inputs) == 3`
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