Aharrypotter commented on code in PR #19814:
URL: https://github.com/apache/tvm/pull/19814#discussion_r3427549698
##########
python/tvm/relax/frontend/tflite/tflite_frontend.py:
##########
@@ -5009,7 +5009,22 @@ def convert_reverse_sequence(self, op):
batch_axis = options.BatchDim()
seq_axis = options.SeqDim()
- return relax.op.reverse_sequence(in_expr, length_expr, seq_axis,
batch_axis)
+ if batch_axis != 0:
+ raise tvm.error.OpNotImplemented(
+ "TFLite REVERSE_SEQUENCE with non-zero batch_dim is not
supported yet."
+ )
+
+ output_tensors = self.get_output_tensors(op)
+ assert len(output_tensors) == 1, "output tensors length should be 1"
+ output_tensor = output_tensors[0]
+ output_shape = to_int_list(self.get_tensor_shape(output_tensor))
+ output_dtype = self.get_tensor_type_str(output_tensor.tensor.Type())
+
+ return relax.op.call_dps_packed(
+ "topi.reverse_sequence",
+ (in_expr, length_expr, seq_axis),
+ out_sinfo=relax.TensorStructInfo(output_shape, output_dtype),
+ )
Review Comment:
Thanks for the careful check. I looked at the current packed registration in
`src/topi/transform.cc`, and `topi.reverse_sequence` is registered as a
3-argument packed function:
```cpp
.def_packed("topi.reverse_sequence",
[](ffi::PackedArgs args, ffi::Any* rv) {
*rv = reverse_sequence(args[0].cast<te::Tensor>(),
args[1].cast<te::Tensor>(),
args[2].cast<int>());
})
```
So passing `(data, seq_lengths, seq_axis, batch_axis)` from Relax would not
match
the current packed API. The frontend already rejects `batch_dim != 0` before
the
call, and the 3-argument packed wrapper therefore intentionally uses TOPI's
default `batch_axis=0`.
I think the current 3-argument call and the matching Expected IR are the
safer
form for this PR. If we want to support non-zero `batch_dim` later, the right
follow-up would be to first extend the `topi.reverse_sequence` packed
registration to consume `args[3]`, and then update the TFLite frontend and
test
expectation to pass `batch_axis` explicitly.
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