Add __eq__ and __str__ to ActionSpec

ml-agents-envs/mlagents_envs/base_env.py

     num_continuous_actions: int
     discrete_branch_sizes: Tuple[int, ...]
 
+    def __eq__(self, other):
+        return (
+            self.continuous_size == other.continuous_size
+            and self.discrete_branches == other.discrete_branches
+        )
+
+    def __str__(self):
+        return f"Continuous: {self.continuous_size}, Discrete: {self.discrete_branches}"
+
     # For backwards compatibility
     def is_discrete(self) -> bool:
         """

ml-agents/mlagents/trainers/demo_loader.py

     demo_buffer = make_demo_buffer(info_action_pair, behavior_spec, sequence_length)
     if expected_behavior_spec:
         # check action dimensions in demonstration match
-        if (
-            behavior_spec.action_spec.continuous_size
-            != expected_behavior_spec.action_spec.continuous_size
-        ):
+        if behavior_spec.action_spec != expected_behavior_spec.action_spec:
-                "The continuous action dimensions {} in demonstration do not match the policy's {}.".format(
-                    behavior_spec.action_spec.continuous_size,
-                    expected_behavior_spec.action_spec.continuous_size,
-                )
-            )
-
-        if (
-            behavior_spec.action_spec.discrete_branches
-            != expected_behavior_spec.action_spec.discrete_branches
-        ):
-            raise RuntimeError(
-                "The discrete action dimensions {} in demonstration do not match the policy's {}.".format(
-                    behavior_spec.action_spec.discrete_branches,
-                    expected_behavior_spec.action_spec.discrete_branches,
+                "The action spaces {} in demonstration do not match the policy's {}.".format(
+                    behavior_spec.action_spec, expected_behavior_spec.action_spec
                 )
             )
         # check observations match