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python/torch_mlir/repro.py: Fix when arguments are passed in as tuple #130

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Jul 24, 2023
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python/torch_mlir/repro.py: Fix when arguments are passed in as tuple #130

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19 changes: 10 additions & 9 deletions python/torch_mlir/repro.py
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Original file line number Diff line number Diff line change
Expand Up @@ -165,12 +165,12 @@ def _reduce_inputs(inps, are_inputs_good):
@torch.no_grad()
def reproduce(
model: torch.nn.Module,
inputs,
model_args,
model_kwargs=None,
output_type="torch",
dtype=None,
expected_error: Optional[str] = None,
verbose=False,
**model_kwargs,
):
"""
Reduces the given model while ensuring that the error message seen by passing
Expand All @@ -182,15 +182,14 @@ def reproduce(
error message. You can also pass it explicitly via the expected_error
parameter.
"""

inputs = map_kwargs_into_args(model, inputs, model_kwargs)

model, _ = prepare_model(model, *inputs, dtype=dtype)
if model_kwargs is not None:
model_args = map_kwargs_into_args(model, model_args, model_kwargs)
model, _ = prepare_model(model, *model_args, dtype=dtype)
fx_g = make_fx(
model,
decomposition_table=_get_decomposition_table())(*inputs)
decomposition_table=_get_decomposition_table())(*model_args)

error = _obtain_errror(fx_g, inputs, output_type=output_type)
error = _obtain_errror(fx_g, model_args, output_type=output_type)
if error == "":
print("ERROR: torch_mlir.compile passes, nothing to reproduce")
return
Expand Down Expand Up @@ -219,4 +218,6 @@ def show_reproducer(fx_g: fx.GraphModule, inps: List[torch.Tensor]):
inps = _reduce_inputs(inps, lambda inputs: module_fails(fx_g, inputs))
_dump_reproducer(fx_g, inps, output_type, dtype)

minifier(fx_g, inputs, module_fails, dump_state=show_reproducer)
# Tuples are not supported by minifier
model_args = list(model_args)
minifier(fx_g, model_args, module_fails, dump_state=show_reproducer)