mshr-h commented on code in PR #17864:
URL: https://github.com/apache/tvm/pull/17864#discussion_r2052162278
##########
tests/python/relax/test_frontend_from_exported_program.py:
##########
@@ -4377,5 +4377,26 @@ def main(
verify_model(Narrow(), example_args, {}, Expected)
+def test_eye():
+ class Eye(Module):
+ def forward(self, input):
+ return torch.eye(3, 5, dtype=torch.float32)
Review Comment:
Need a testcase where only `n` is given.
##########
python/tvm/relax/frontend/torch/base_fx_graph_translator.py:
##########
@@ -1416,6 +1416,19 @@ def _empty_like(self, node: fx.Node) -> relax.Var:
x = self.env[node.args[0]]
return self.block_builder.emit(relax.op.zeros_like(x))
+ def _eye(self, node: fx.Node) -> relax.Var:
+ args = self.retrieve_args(node)
+ if len(args) == 1:
+ n = args[0]
+ m = n
+ elif len(args) == 2:
+ n = args[0]
+ m = args[1]
+ else:
Review Comment:
I don't think we need to take care of this condition because the pytorch
exporter does that.
So we can assume that the graph in the exported program doesn't contain
wrong nodes.
Probably this is enough?
```python
n = args[0]
m = args[1] if len(args) > 1 else n
```
cc @Hzfengsy
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