Aharrypotter commented on code in PR #19814:
URL: https://github.com/apache/tvm/pull/19814#discussion_r3432683927
##########
tests/python/relax/test_frontend_tflite.py:
##########
@@ -1456,6 +1456,29 @@ def main(x: R.Tensor((2, 3), dtype="float32")) ->
R.Tensor((2, 3), dtype="float3
verify(ReverseV2, Expected)
+def test_reverse_sequence():
+ mod = _load_model_from_buffer(_build_tflite_reverse_sequence_model())
+
+ @I.ir_module
+ class Expected:
+ @R.function
+ def main(
+ tvmgen_tensor_0: R.Tensor((2, 4, 3), dtype="float32"),
+ tvmgen_tensor_1: R.Tensor((2,), dtype="int32"),
+ ) -> R.Tensor((2, 4, 3), dtype="float32"):
+ R.func_attr({"num_input": 2})
+ with R.dataflow():
+ gv: R.Tensor((2, 4, 3), dtype="float32") = R.call_dps_packed(
+ "topi.reverse_sequence",
+ (tvmgen_tensor_0, tvmgen_tensor_1, 1),
+ out_sinfo=R.Tensor((2, 4, 3), dtype="float32"),
+ )
Review Comment:
Same as above. The current `topi.reverse_sequence` packed registration only
consumes three arguments, and this PR already rejects non-zero `batch_dim`, so
the Expected IR intentionally matches the current 3-argument packed API.
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