具有具有输入参数的环境的 Tf 代理并行 Py 环境

Question

Suppose you have an environment that has input parameters: for example, to create an instance you would use

env_instance = MyEnv(var_1=3, var_2=5, ...)

Now suppose you want to create a parallel_py_environment using the environment "MyEnv"? Since you need input parameters, you cannot use

tf_py_environment.TFPyEnvironment(parallel_py_environment.ParallelPyEnvironment([MyEnv]*int(n_envs)))

Answer 1

The solution is to create a super class:

class MyEnvPar(MyEnv):
    def __init__(self):
        super().__init__(var_1=3, var_2=5)

And then you can use

tf_py_environment.TFPyEnvironment(parallel_py_environment.ParallelPyEnvironment([MyEnvPar]*int(n_envs)))