class_docstr: Cast observations to float32, which is commonly used for NNs.
  
  Args:
      env: Env to wrap.
  
  Attributes:
      original_observation: Observation before casting.
code: def __init__(self, env):
      super().__init__(env, np.float32)
  
file_path: pfrl/pfrl/wrappers/cast_observation.py
imports: import gym
  import numpy
label_desc: Use image node_id 1 to create a new CastObservationToFloat32 object from inherited base classes: CastObservation with example: obj = CastObservationToFloat32(env)