Enable Pyrefly in fbcode/vision/fair

Summary:
Automated migration to enable Pyrefly type checking for `fbcode/vision/fair`.

- Added `python.set_pyrefly(True)` to PACKAGE file
- Suppressed pre-existing type errors

Pyrefly is Meta's next-generation Python type checker, replacing Pyre.

If you encounter issues, you can revert the PACKAGE change by removing
the `python.set_pyrefly(True)` line.
#pyreupgrade

Differential Revision: D107142434

fbshipit-source-id: 25929bb3d5a310d00dab11a46c5395df94357feb

projects/implicitron_trainer/experiment.py

@@ -193,6 +193,7 @@ 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,
         )
 
@@ -212,6 +213,7 @@ 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

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

projects/implicitron_trainer/impl/training_loop.py

@@ -199,6 +199,7 @@ 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,
@@ -215,6 +216,7 @@ 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

@@ -14,6 +14,7 @@ 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

@@ -75,6 +75,7 @@ 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,
@@ -135,6 +136,7 @@ def visualize_reconstruction(
                 "device": device,
                 **render_flyaround_kwargs,
             }
+            # pyrefly: ignore [bad-argument-type]
             render_flyaround(**render_kwargs)