Replace view by reshape to support unclear operations

Toni-SM · Sep 30, 2024 · f30e9f7 · f30e9f7
1 parent fe57d20
commit f30e9f7
Showing 1 changed file with 12 additions and 12 deletions.
diff --git a/skrl/utils/spaces/torch/__init__.py b/skrl/utils/spaces/torch/__init__.py
@@ -33,29 +33,29 @@ def tensorize_space(space: spaces.Space, x: Any, device: Optional[Union[str, tor
     # Box
     if isinstance(space, spaces.Box):
         if isinstance(x, torch.Tensor):
-            return x.view(-1, *space.shape)
+            return x.reshape(-1, *space.shape)
         elif isinstance(x, np.ndarray):
-            return torch.tensor(x, device=device, dtype=torch.float32).view(-1, *space.shape)
+            return torch.tensor(x, device=device, dtype=torch.float32).reshape(-1, *space.shape)
         else:
             raise ValueError(f"Unsupported type ({type(x)}) for the given space ({space})")
     # Discrete
     elif isinstance(space, spaces.Discrete):
         if isinstance(x, torch.Tensor):
-            return x.view(-1, 1)
+            return x.reshape(-1, 1)
         elif isinstance(x, np.ndarray):
-            return torch.tensor(x, device=device, dtype=torch.int32).view(-1, 1)
+            return torch.tensor(x, device=device, dtype=torch.int32).reshape(-1, 1)
         elif isinstance(x, np.number) or type(x) in [int, float]:
-            return torch.tensor([x], device=device, dtype=torch.int32).view(-1, 1)
+            return torch.tensor([x], device=device, dtype=torch.int32).reshape(-1, 1)
         else:
             raise ValueError(f"Unsupported type ({type(x)}) for the given space ({space})")
     # MultiDiscrete
     elif isinstance(space, spaces.MultiDiscrete):
         if isinstance(x, torch.Tensor):
-            return x.view(-1, *space.shape)
+            return x.reshape(-1, *space.shape)
         elif isinstance(x, np.ndarray):
-            return torch.tensor(x, device=device, dtype=torch.int32).view(-1, *space.shape)
+            return torch.tensor(x, device=device, dtype=torch.int32).reshape(-1, *space.shape)
         elif type(x) in [list, tuple]:
-            return torch.tensor([x], device=device, dtype=torch.int32).view(-1, *space.shape)
+            return torch.tensor([x], device=device, dtype=torch.int32).reshape(-1, *space.shape)
         else:
             raise ValueError(f"Unsupported type ({type(x)}) for the given space ({space})")
     # composite spaces
@@ -79,7 +79,7 @@ def flatten_tensorized_space(x: Any) -> torch.Tensor:
     # fundamental spaces
     # Box / Discrete / MultiDiscrete
     if isinstance(x, torch.Tensor):
-        return x.view(x.shape[0], -1) if x.ndim > 1 else x.view(1, -1)
+        return x.reshape(x.shape[0], -1) if x.ndim > 1 else x.reshape(1, -1)
     # composite spaces
     # Dict
     elif isinstance(x, dict):
@@ -102,13 +102,13 @@ def unflatten_tensorized_space(space: Union[spaces.Space, Sequence[int], int], x
     # fundamental spaces
     # Box
     if isinstance(space, spaces.Box):
-        return x.view(-1, *space.shape)
+        return x.reshape(-1, *space.shape)
     # Discrete
     elif isinstance(space, spaces.Discrete):
-        return x.view(-1, 1)
+        return x.reshape(-1, 1)
     # MultiDiscrete
     elif isinstance(space, spaces.MultiDiscrete):
-        return x.view(-1, *space.shape)
+        return x.reshape(-1, *space.shape)
     # composite spaces
     # Dict
     elif isinstance(space, spaces.Dict):