Clean up pyre-fixme/ignore comments that are no longer suppressing errors (meta-pytorch#1554)

Summary: Pull Request resolved: meta-pytorch#1554 Clean up pyre-fixme/ignore comments that are no longer suppressing errors throughout the entire Captum library. Reviewed By: sarahtranfb Differential Revision: D74049476 fbshipit-source-id: bba23dbc91e317cb715b72537e97aa399781c8d0

Author: craymichael

captum/_utils/gradient.py

@@ -682,8 +682,6 @@ def compute_layer_gradients_and_eval(
  " take gradient with respect to multiple outputs."
  )
 
- # pyre-fixme[6]: For 2nd argument expected `Dict[Module, Dict[device,
- # typing.Tuple[Tensor, ...]]]` but got `Module`.
  device_ids = _extract_device_ids(forward_fn, saved_layer, device_ids)
 
  # Identifies correct device ordering based on device ids.
@@ -729,7 +727,6 @@ def compute_layer_gradients_and_eval(
  for layer_tensor in saved_layer[single_layer][device_id]
  )
  saved_grads = torch.autograd.grad(
- # pyre-fixme[6]: For 1st argument expected `Tensor` but got `Module`.
  outputs=torch.unbind(output),
  inputs=grad_inputs,
  **grad_kwargs or {},

captum/_utils/models/linear_model/train.py

@@ -275,7 +275,6 @@ def __init__(self, mean, std, n=None, eps: float = 1e-8) -> None:
  self.mean = mean
  # pyre-fixme[4]: Attribute must be annotated.
  self.std = std
- # pyre-fixme[4]: Attribute must be annotated.
  self.eps = eps
 
  # pyre-fixme[3]: Return type must be annotated.

captum/attr/_core/integrated_gradients.py

@@ -88,8 +88,6 @@ def attribute(
  ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
 
  @typing.overload
- # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
- # arguments of overload defined on line `82`.
  def attribute(
  self,
  inputs: TensorOrTupleOfTensorsGeneric,
@@ -262,14 +260,10 @@ def attribute( # type: ignore
  # converting it into a tuple.
  is_inputs_tuple = _is_tuple(inputs)
 
- # pyre-fixme[9]: inputs has type `TensorOrTupleOfTensorsGeneric`; used as
- # `Tuple[Tensor, ...]`.
  formatted_inputs, formatted_baselines = _format_input_baseline(
  inputs, baselines
  )
 
- # pyre-fixme[6]: For 1st argument expected `Tuple[Tensor, ...]` but got
- # `TensorOrTupleOfTensorsGeneric`.
  _validate_input(formatted_inputs, formatted_baselines, n_steps, method)
 
  if internal_batch_size is not None:

captum/attr/_core/lime.py

@@ -566,7 +566,6 @@ def _evaluate_batch(
  ) -> Tensor:
  model_out = _run_forward(
  self.forward_func,
- # pyre-fixme[6]: For 1st argument expected `Sequence[Variable[TupleOrTens...
  _reduce_list(curr_model_inputs),
  expanded_target,
  expanded_additional_args,

captum/attr/_core/occlusion.py

@@ -323,8 +323,6 @@ 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/attr/_utils/attribution.py

@@ -24,8 +24,6 @@
 from torch.nn import Module
 
 
-# pyre-fixme[13]: Attribute `attribute` is never initialized.
-# pyre-fixme[13]: Attribute `compute_convergence_delta` is never initialized.
 class Attribution:
  r"""
  All attribution algorithms extend this class. It enforces its child classes
@@ -471,7 +469,6 @@ def interpolate(
  return F.interpolate(layer_attribution, interpolate_dims, mode=interpolate_mode)
 
 
-# pyre-fixme[13]: Attribute `attribute` is never initialized.
 # pyre-fixme[24]: Generic type `InternalAttribution` expects 1 type parameter.
 class NeuronAttribution(InternalAttribution):
  r"""

captum/attr/_utils/lrp_rules.py

@@ -68,7 +68,6 @@ def _backward_hook_input(grad):
  device = grad.device
  # pyre-fixme[16]: `PropagationRule` has no attribute `_has_single_input`.
  if self._has_single_input:
- # pyre-fixme[16]: `PropagationRule` has no attribute `relevance_input`.
  self.relevance_input[device] = relevance.data
  else:
  cast(List[Tensor], self.relevance_input[device]).append(relevance.data)
@@ -82,14 +81,12 @@ def _backward_hook_input(grad):
 
  # pyre-fixme[3]: Return type must be annotated.
  def _create_backward_hook_output(self, outputs: torch.Tensor):
- # pyre-fixme[53]: Captured variable `outputs` is not annotated.
  # pyre-fixme[3]: Return type must be annotated.
  # pyre-fixme[2]: Parameter must be annotated.
  def _backward_hook_output(grad):
  sign = torch.sign(outputs)
  sign[sign == 0] = 1
  relevance = grad / (outputs + sign * self.STABILITY_FACTOR)
- # pyre-fixme[16]: `PropagationRule` has no attribute `relevance_output`.
  self.relevance_output[grad.device] = grad.data
  return relevance
 
@@ -138,7 +135,6 @@ class EpsilonRule(PropagationRule):
  """
 
  def __init__(self, epsilon: float = 1e-9) -> None:
- # pyre-fixme[4]: Attribute must be annotated.
  self.STABILITY_FACTOR = epsilon
 
  # pyre-fixme[2]: Parameter must be annotated.
@@ -159,9 +155,7 @@ class GammaRule(PropagationRule):
  """
 
  def __init__(self, gamma: float = 0.25, set_bias_to_zero: bool = False) -> None:
- # pyre-fixme[4]: Attribute must be annotated.
  self.gamma = gamma
- # pyre-fixme[4]: Attribute must be annotated.
  self.set_bias_to_zero = set_bias_to_zero
 
  # pyre-fixme[2]: Parameter must be annotated.
@@ -188,7 +182,6 @@ class Alpha1_Beta0_Rule(PropagationRule):
  """
 
  def __init__(self, set_bias_to_zero: bool = False) -> None:
- # pyre-fixme[4]: Attribute must be annotated.
  self.set_bias_to_zero = set_bias_to_zero
 
  # pyre-fixme[2]: Parameter must be annotated.
@@ -215,7 +208,6 @@ def _create_backward_hook_input(self, inputs):
  # pyre-fixme[3]: Return type must be annotated.
  # pyre-fixme[2]: Parameter must be annotated.
  def _backward_hook_input(grad):
- # pyre-fixme[16]: `IdentityRule` has no attribute `relevance_output`.
  return self.relevance_output[grad.device]
 
  return _backward_hook_input

captum/concept/_core/concept.py

@@ -58,7 +58,6 @@ def __repr__(self) -> str:
  return "Concept(%r, %r)" % (self.id, self.name)
 
 
-# pyre-fixme[13]: Attribute `interpret` is never initialized.
 class ConceptInterpreter:
  r"""
  An abstract class that exposes an abstract interpret method

captum/insights/example.py

@@ -3,7 +3,6 @@
 # pyre-strict
 import warnings
 
-# pyre-fixme[21]: Could not find name `Net` in `captum.insights.attr_vis.example`.
 from captum.insights.attr_vis.example import * # noqa
 
 warnings.warn(

captum/robust/_core/fgsm.py

@@ -156,8 +156,6 @@ def perturb(
  is returned. If a tuple is provided for inputs, a tuple of
  corresponding sized tensors is returned.
  """
- # pyre-fixme[6]: For 1st argument expected `Tensor` but got
- # `TensorOrTupleOfTensorsGeneric`.
  is_inputs_tuple = _is_tuple(inputs)
  # pyre-fixme[35]: Target cannot be annotated.
  inputs: Tuple[Tensor, ...] = _format_tensor_into_tuples(inputs)