vdkhoi commented on code in PR #11183:
URL: https://github.com/apache/tvm/pull/11183#discussion_r867490976
##########
python/tvm/relay/frontend/tflite.py:
##########
@@ -2710,6 +2743,145 @@ def convert_unpack(self, op):
return squeezed
+ def convert_unidirectional_sequence_lstm(self, op):
+ """Long Short Term Memory for TFLite implementation."""
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ "TFlite quantized UNIDIRECTIONALSEQUENCELSTM operator is not
supported yet."
+ )
+
+ input_tensors = self.get_input_tensors(op)
+ assert len(input_tensors) >= 20, "input tensors length should be >= 20"
Review Comment:
As I mentioned above, from our understanding about tflite format, the number
of vectors which can be stored in flatbuffer designed by tflite is 20 tensors.
If you generate a tflite model without specifying other weights except input
tensor, the ignored weights will be assigned by default values (0) and store in
model file as inputs. Of course, in this code we just support some recent
tflite versions. If you can find some models which support different numbers of
inputs and the references from tflite documentation to instruct how to process
it, we deeply thank you and extend out support for that kind of model.
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