Revert D107142434: Enable Pyrefly in fbcode/vision/fair

Differential Revision:
D107142434

Original commit changeset: 25929bb3d5a3

Original Phabricator Diff: D107142434

fbshipit-source-id: 0aecaeba28d7d8db8f9273406a080e41aa77c4a7

projects/implicitron_trainer/experiment.py

@@ -193,7 +193,6 @@ class Experiment(Configurable):
             last_epoch=start_epoch,
             model=model,
             resume=self.model_factory.resume,
-            # pyrefly: ignore [missing-attribute]
             resume_epoch=self.model_factory.resume_epoch,
         )
 
@@ -213,7 +212,6 @@ class Experiment(Configurable):
 
         # Enter the main training loop.
         self.training_loop.run(
-            # pyrefly: ignore [bad-argument-type]
             train_loader=train_loader,
             val_loader=val_loader,
             test_loader=test_loader,

projects/implicitron_trainer/impl/optimizer_factory.py

@@ -173,7 +173,6 @@ class ImplicitronOptimizerFactory(OptimizerFactoryBase):
             scheduler = torch.optim.lr_scheduler.LambdaLR(
                 optimizer,
                 lambda epoch: self.gamma ** (epoch / self.exponential_lr_step_size),
-                # pyrefly: ignore [unexpected-keyword]
                 verbose=False,
             )
         elif self.lr_policy.casefold() == "LinearExponential".casefold():
@@ -192,11 +191,7 @@ class ImplicitronOptimizerFactory(OptimizerFactoryBase):
 
             # pyre-fixme[28]: Unexpected keyword argument `verbose`.
             scheduler = torch.optim.lr_scheduler.LambdaLR(
-                # pyrefly: ignore [unexpected-keyword]
-                optimizer,
-                _get_lr,
-                # pyrefly: ignore [unexpected-keyword]
-                verbose=False,
+                optimizer, _get_lr, verbose=False
             )
         else:
             raise ValueError("no such lr policy %s" % self.lr_policy)

projects/implicitron_trainer/impl/training_loop.py

@@ -199,7 +199,6 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
                     and self.test_interval > 0
                     and epoch % self.test_interval == 0
                 ):
-                    # pyrefly: ignore [missing-attribute]
                     self.evaluator.run(
                         device=device,
                         dataloader=test_loader,
@@ -216,7 +215,6 @@ class ImplicitronTrainingLoop(TrainingLoopBase):
 
         if self.test_when_finished:
             if test_loader is not None:
-                # pyrefly: ignore [missing-attribute]
                 self.evaluator.run(
                     device=device,
                     dump_to_json=True,

projects/implicitron_trainer/impl/utils.py

@@ -14,7 +14,6 @@ import torch
 
 
 def seed_all_random_engines(seed: int) -> None:
-    # pyrefly: ignore [bad-argument-type]
     np.random.seed(seed)
     torch.manual_seed(seed)
     random.seed(seed)

projects/implicitron_trainer/visualize_reconstruction.py

@@ -75,7 +75,6 @@ def visualize_reconstruction(
 
     # Set the random seeds
     torch.manual_seed(0)
-    # pyrefly: ignore [bad-argument-type]
     np.random.seed(0)
 
     # Get the config from the experiment_directory,
@@ -136,7 +135,6 @@ def visualize_reconstruction(
                 "device": device,
                 **render_flyaround_kwargs,
             }
-            # pyrefly: ignore [bad-argument-type]
             render_flyaround(**render_kwargs)