anijain2305 commented on a change in pull request #6127:
URL: https://github.com/apache/incubator-tvm/pull/6127#discussion_r460425929
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File path: python/tvm/relay/frontend/tflite.py
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@@ -2726,7 +2726,13 @@ def convert_quantize(self, op):
assert len(input_tensors) == 1, "input tensors length should be 1"
input_tensor = input_tensors[0]
input_tensor_type_str =
self.get_tensor_type_str(input_tensor.tensor.Type())
- in_expr = self.get_expr(input_tensor.tensor_idx)
+
+ if self.has_expr(input_tensor.tensor_idx):
+ in_expr = self.get_expr(input_tensor.tensor_idx)
+ else:
+ in_value = self.get_tensor_value(input_tensor)
Review comment:
Is it possible to share the model? I am wondering if parsing of
constants is the problem here. We can think of this case just like conv where
weights are converted to relay consts and we add a var for them.
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