Add pyre fixme for downstream type errors from D65753120

captum/attr/_core/dataloader_attr.py

@@ -87,6 +87,8 @@ def _perturb_inputs(
         else:
             baseline = baselines[attr_inp_count]
 
+            # pyre-fixme[58]: `*` is not supported for operand types `object` and
+            #  `Tensor`.
             perturbed_inp = inp * pert_mask + baseline * (1 - pert_mask)
             perturbed_inputs.append(perturbed_inp)
 

captum/attr/_core/feature_ablation.py

@@ -807,7 +807,10 @@ def _construct_ablated_input(
         ).long()
         current_mask = current_mask.to(expanded_input.device)
         ablated_tensor = (
-            expanded_input * (1 - current_mask).to(expanded_input.dtype)
+            expanded_input
+            * (1 - current_mask).to(expanded_input.dtype)
+            # pyre-fixme[58]: `*` is not supported for operand types `Union[None, float,
+            #  Tensor]` and `Tensor`.
         ) + (baseline * current_mask.to(expanded_input.dtype))
         return ablated_tensor, current_mask
 

captum/attr/_core/occlusion.py

@@ -322,6 +322,8 @@ def _construct_ablated_input(
                 torch.ones(1, dtype=torch.long, device=expanded_input.device)
                 - input_mask
             ).to(expanded_input.dtype)
+            # pyre-fixme[58]: `*` is not supported for operand types `Union[None, float,
+            #  Tensor]` and `Tensor`.
         ) + (baseline * input_mask.to(expanded_input.dtype))
         return ablated_tensor, input_mask
 

captum/metrics/_core/infidelity.py

@@ -619,6 +619,8 @@ def _next_infidelity_tensors(
         inputs_fwd = torch.repeat_interleave(
             inputs_fwd, current_n_perturb_samples, dim=0
         )
+        # pyre-fixme[58]: `-` is not supported for operand types `Tensor` and
+        #  `Union[Future[Tensor], Tensor]`.
         perturbed_fwd_diffs = inputs_fwd - inputs_perturbed_fwd
         attributions_expanded = tuple(
             torch.repeat_interleave(attribution, current_n_perturb_samples, dim=0)

captum/module/gaussian_stochastic_gates.py

@@ -133,6 +133,8 @@ def _get_gate_active_probs(self) -> Tensor:
             probs (Tensor): probabilities tensor of the gates are active
                 in shape(n_gates)
         """
+        # pyre-fixme[58]: `/` is not supported for operand types `Parameter` and
+        #  `Optional[float]`.
         x = self.mu / self.std
         return 0.5 * (1 + torch.erf(x / math.sqrt(2)))
 

tests/attr/test_input_x_gradient.py

@@ -117,6 +117,8 @@ def _input_x_gradient_classification_assert(self, nt_type: str = "vanilla") -> N
             attributions = input_x_grad.attribute(input, target)
             output = model(input)[:, target]
             output.backward()
+            # pyre-fixme[58]: `*` is not supported for operand types
+            #  `Optional[Tensor]` and `Tensor`.
             expected = input.grad * input
             assertTensorAlmostEqual(self, attributions, expected, 0.00001, "max")
         else: