Ignore errors from new pytype version (#107)

DLR-RM · Jul 16, 2020 · 208890d · 208890d
1 parent 3cf6e97
commit 208890d
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Showing 3 changed files with 5 additions and 3 deletions.
diff --git a/docs/misc/changelog.rst b/docs/misc/changelog.rst
@@ -37,6 +37,7 @@ Others:
 - Split the ``collect_rollout()`` method for off-policy algorithms
 - Added ``_on_step()`` for off-policy base class
 - Optimized replay buffer size by removing the need of ``next_observations`` numpy array
+- Ignored errors from newer pytype version
 
 Documentation:
 ^^^^^^^^^^^^^^

diff --git a/stable_baselines3/common/base_class.py b/stable_baselines3/common/base_class.py
@@ -330,7 +330,8 @@ def load(cls, load_path: str, env: Optional[GymEnv] = None, **kwargs) -> 'BaseAl
             env = data["env"]
 
         # noinspection PyArgumentList
-        model = cls(policy=data["policy_class"], env=env, device='auto', _init_setup_model=False)
+        model = cls(policy=data["policy_class"], env=env,
+                    device='auto', _init_setup_model=False)  # pytype: disable=not-instantiable,wrong-keyword-args
 
         # load parameters
         model.__dict__.update(data)
@@ -350,7 +351,7 @@ def load(cls, load_path: str, env: Optional[GymEnv] = None, **kwargs) -> 'BaseAl
         # Sample gSDE exploration matrix, so it uses the right device
         # see issue #44
         if model.use_sde:
-            model.policy.reset_noise()
+            model.policy.reset_noise()  # pytype: disable=attribute-error
         return model
 
     def set_random_seed(self, seed: Optional[int] = None) -> None:

diff --git a/stable_baselines3/common/policies.py b/stable_baselines3/common/policies.py
@@ -126,7 +126,7 @@ def load(cls, path: str, device: Union[th.device, str] = 'auto') -> 'BaseModel':
         device = get_device(device)
         saved_variables = th.load(path, map_location=device)
         # Create policy object
-        model = cls(**saved_variables['data'])
+        model = cls(**saved_variables['data'])  # pytype: disable=not-instantiable
         # Load weights
         model.load_state_dict(saved_variables['state_dict'])
         model.to(device)