# Path: gym3/types.py
# class ValType:
#     """
#     Tensor or combination of tensors
#     """
# 
#     __eq__ = pod_equals


from typing import Any, Dict, List, Sequence, Tuple
from gym3.types import ValType



class Env:
    """
    An interface for reinforcement learning environments.

    :param ob_space: ValType representing the valid observations generated by the environment
    :param ac_space: ValType representing the valid actions that an agent can take in the environment
    :param num: number of simultaneous episodes
    """


# Path: gym3/types.py
# class ValType:
#     """
#     Tensor or combination of tensors
#     """
# 
#     __eq__ = pod_equals


# Path: gym3/env.py
from typing import Any, Dict, List, Sequence, Tuple
from gym3.types import ValType




class Env:
    """
    An interface for reinforcement learning environments.

    :param ob_space: ValType representing the valid observations generated by the environment
    :param ac_space: ValType representing the valid actions that an agent can take in the environment
    :param num: number of simultaneous episodes
    """


    def __init__(self, ob_space: ValType, ac_space: ValType, num: int):