revert dp changes, make act and tdmpc batch friendly

lerobot/common/policies/abstract.py

@@ -1,15 +1,20 @@
-from abc import abstractmethod
+from abc import ABC, abstractmethod
 from collections import deque
 
 import torch
 from torch import Tensor, nn
 
 
-class AbstractPolicy(nn.Module):
+class AbstractPolicy(nn.Module, ABC):
+    """Base policy which all policies should be derived from.
+
+    The forward method should generally not be overriden as it plays the role of handling multi-step policies. See its
+    documentation for more information.
+    """
+
     @abstractmethod
     def update(self, replay_buffer, step):
         """One step of the policy's learning algorithm."""
-        pass
 
     def save(self, fp):
         torch.save(self.state_dict(), fp)
@@ -24,7 +29,6 @@ class AbstractPolicy(nn.Module):
 
         Should return a (batch_size, n_action_steps, *) tensor of actions.
         """
-        pass
 
     def forward(self, *args, **kwargs):
         """Inference step that makes multi-step policies compatible with their single-step environments.