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Ensure eval diff and mask tensor are on the same device #1542

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Ensure eval diff and mask tensor are on the same device #1542

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19 changes: 14 additions & 5 deletions captum/attr/_core/shapley_value.py
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Original file line number Diff line number Diff line change
Expand Up @@ -397,15 +397,19 @@ def attribute(
if show_progress:
attr_progress.update()
if agg_output_mode:
eval_diff = modified_eval - prev_results
eval_diff = (modified_eval - prev_results).to(
inputs_tuple[0].device
)
prev_results = modified_eval
else:
# when perturb_per_eval > 1, every num_examples stands for
# one perturb. Since the perturbs are from a consecutive
# perumuation, each diff of a perturb is its eval minus
# the eval of the previous perturb
all_eval = torch.cat((prev_results, modified_eval), dim=0)
eval_diff = all_eval[num_examples:] - all_eval[:-num_examples]
eval_diff = (
all_eval[num_examples:] - all_eval[:-num_examples]
).to(inputs_tuple[0].device)
prev_results = all_eval[-num_examples:]

for j in range(len(total_attrib)):
Expand Down Expand Up @@ -689,7 +693,7 @@ def _evalFutToPrevResultsTuple(
agg_output_mode,
) = prev_results_tuple
if agg_output_mode:
eval_diff = modified_eval - prev_results
eval_diff = (modified_eval - prev_results).to(inputs_tuple[0].device)
prev_results = modified_eval
else:
# when perturb_per_eval > 1, every num_examples stands for
Expand All @@ -698,7 +702,9 @@ def _evalFutToPrevResultsTuple(
# the eval of the previous perturb

all_eval = torch.cat((prev_results, modified_eval), dim=0)
eval_diff = all_eval[num_examples:] - all_eval[:-num_examples]
eval_diff = (all_eval[num_examples:] - all_eval[:-num_examples]).to(
inputs_tuple[0].device
)
prev_results = all_eval[-num_examples:]

for j in range(len(total_attrib)):
Expand Down Expand Up @@ -799,7 +805,10 @@ def _perturbation_generator(
)
current_tensors_list.append(current_tensors)
current_mask_list.append(
tuple(mask == feature_permutation[i] for mask in input_masks)
tuple(
(mask == feature_permutation[i]).to(inputs[0].device)
for mask in input_masks
)
)
if len(current_tensors_list) == perturbations_per_eval:
combined_inputs = tuple(
Expand Down