Pt 1.9 breaking fix: __iter__ type hint (#7993)

pl_examples/domain_templates/reinforce_learn_Qnet.py

@@ -34,7 +34,7 @@
 
 import argparse
 from collections import deque, namedtuple, OrderedDict
-from typing import List, Tuple
+from typing import Iterator, List, Tuple
 
 import gym
 import numpy as np
@@ -139,7 +139,7 @@ def __init__(self, buffer: ReplayBuffer, sample_size: int = 200) -> None:
  self.buffer = buffer
  self.sample_size = sample_size
 
- def __iter__(self) -> Tuple:
+ def __iter__(self) -> Iterator:
  states, actions, rewards, dones, new_states = self.buffer.sample(self.sample_size)
  for i in range(len(dones)):
  yield states[i], actions[i], rewards[i], dones[i], new_states[i]

pl_examples/domain_templates/reinforce_learn_ppo.py

@@ -28,7 +28,7 @@
 [3] https://github.com/sid-sundrani/ppo_lightning
 """
 import argparse
-from typing import Callable, Iterable, List, Tuple
+from typing import Callable, Iterator, List, Tuple
 
 import gym
 import torch
@@ -144,7 +144,7 @@ class ExperienceSourceDataset(IterableDataset):
  def __init__(self, generate_batch: Callable):
  self.generate_batch = generate_batch
 
- def __iter__(self) -> Iterable:
+ def __iter__(self) -> Iterator:
  iterator = self.generate_batch()
  return iterator