Prepare for "Fix type-safety of torch.nn.Module instances": wave 2

Summary: See D52890934

Reviewed By: malfet, r-barnes

Differential Revision: D66245100

fbshipit-source-id: 019058106ac7eaacf29c1c55912922ea55894d23

Author: ezyang

captum/_utils/transformers_typing.py

@@ -116,4 +116,5 @@ def supports_caching(model: nn.Module) -> bool:
         # Cache is mandatory
         return True
     # Fallback on _supports_cache_class attribute
+    # pyre-fixme[7]: Expected `bool` but got `Union[Module, Tensor]`.
     return getattr(model, "_supports_cache_class", False)

captum/attr/_core/deep_lift.py

@@ -407,6 +407,7 @@ def _forward_pre_hook(
         set necessary hooks on inputs there.
         """
         inputs = _format_tensor_into_tuples(inputs)
+        # pyre-fixme[16]: `Module` has no attribute `input`.
         module.input = inputs[0].clone().detach()
 
     def _forward_hook(
@@ -420,6 +421,7 @@ def _forward_hook(
         outputs of a neuron
         """
         outputs = _format_tensor_into_tuples(outputs)
+        # pyre-fixme[16]: `Module` has no attribute `output`.
         module.output = outputs[0].clone().detach()
 
     def _backward_hook(
@@ -536,6 +538,8 @@ def forward_hook(
         ):
             return [
                 self.model.module.register_forward_pre_hook(pre_hook),  # type: ignore
+                # pyre-fixme[16]: Item `Tensor` of `Tensor | Module` has no
+                #  attribute `register_forward_hook`.
                 self.model.module.register_forward_hook(forward_hook),
             ]  # type: ignore
         else:

captum/attr/_core/llm_attr.py

@@ -404,6 +404,7 @@ def _get_target_tokens(
                 gen_args = DEFAULT_GEN_ARGS
 
             model_inp = self._format_model_input(inp.to_model_input())
+            # pyre-fixme[29]: `Union[Module, Tensor]` is not a function.
             output_tokens = self.model.generate(model_inp, **gen_args)
             target_tokens = output_tokens[0][model_inp.size(1) :]
         else:
@@ -558,9 +559,11 @@ def _forward_func(
                         outputs.past_key_values = DynamicCache.from_legacy_cache(
                             outputs.past_key_values
                         )
+                    # pyre-fixme[29]: `Union[Module, Tensor]` is not a function.
                     model_kwargs = self.model._update_model_kwargs_for_generation(
                         outputs, model_kwargs
                     )
+                # pyre-fixme[29]: `Union[Module, Tensor]` is not a function.
                 model_inputs = self.model.prepare_inputs_for_generation(
                     model_inp, **model_kwargs
                 )

captum/insights/attr_vis/app.py

@@ -407,6 +407,8 @@ def _calculate_vis_output(
             else self.models
         )
         results = []
+        # pyre-fixme[6]: For 1st argument expected `Iterable[_T]` but got
+        #  `Union[List[Any], Module]`.
         for model_index, model in enumerate(models_used):
             # Get list of model visualizations for each input
             actual_label_output = None

tests/attr/layer/test_layer_gradient_x_activation.py

@@ -174,6 +174,8 @@ def _layer_activation_test_assert(
                 self, attributions, expected_activation, delta=0.01
             )
         else:
+            # pyre-fixme[6]: For 1st argument expected
+            #  `pyre_extensions.PyreReadOnly[Sized]` but got `ModuleOrModuleList`.
             for i in range(len(target_layer)):
                 assertTensorTuplesAlmostEqual(
                     self, attributions[i], expected_activation[i], delta=0.01
@@ -196,6 +198,8 @@ def _layer_activation_test_assert(
                 delta=0.01,
             )
         else:
+            # pyre-fixme[6]: For 1st argument expected
+            #  `pyre_extensions.PyreReadOnly[Sized]` but got `ModuleOrModuleList`.
             for i in range(len(target_layer)):
                 assertTensorTuplesAlmostEqual(
                     self,