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Simplify the _check_loss_fn() logic #1243

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Simplify the _check_loss_fn() logic #1243

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24 changes: 5 additions & 19 deletions captum/influence/_utils/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -444,7 +444,7 @@ def _check_loss_fn(
influence_instance: Union["TracInCPBase", "InfluenceFunctionBase"],
loss_fn: Optional[Union[Module, Callable]],
loss_fn_name: str,
sample_wise_grads_per_batch: Optional[bool] = None,
sample_wise_grads_per_batch: bool = True,
) -> str:
"""
This checks whether `loss_fn` satisfies the requirements assumed of all
Expand All @@ -469,16 +469,13 @@ def _check_loss_fn(
# attribute.
if hasattr(loss_fn, "reduction"):
reduction = loss_fn.reduction # type: ignore
if sample_wise_grads_per_batch is None:
if sample_wise_grads_per_batch:
assert reduction in [
"sum",
"mean",
], 'reduction for `loss_fn` must be "sum" or "mean"'
reduction_type = str(reduction)
elif sample_wise_grads_per_batch:
assert reduction in ["sum", "mean"], (
], (
'reduction for `loss_fn` must be "sum" or "mean" when '
"`sample_wise_grads_per_batch` is True"
"`sample_wise_grads_per_batch` is True (i.e. the default value) "
)
reduction_type = str(reduction)
else:
Expand All @@ -490,18 +487,7 @@ def _check_loss_fn(
# if we are unable to access the reduction used by `loss_fn`, we warn
# the user about the assumptions we are making regarding the reduction
# used by `loss_fn`
if sample_wise_grads_per_batch is None:
warnings.warn(
f'Since `{loss_fn_name}` has no "reduction" attribute, the '
f'implementation assumes that `{loss_fn_name}` is a "reduction" loss '
"function that reduces the per-example losses by taking their *sum*. "
f"If `{loss_fn_name}` instead reduces the per-example losses by "
f"taking their mean, please set the reduction attribute of "
f'`{loss_fn_name}` to "mean", i.e. '
f'`{loss_fn_name}.reduction = "mean"`.'
)
reduction_type = "sum"
elif sample_wise_grads_per_batch:
if sample_wise_grads_per_batch:
warnings.warn(
f"Since `{loss_fn_name}`` has no 'reduction' attribute, and "
"`sample_wise_grads_per_batch` is True, the implementation assumes "
Expand Down