class_docstr: This class computes the loss function for A2C with continuous action spaces.
  
  Note
  ----
  This class requires tensorflow-probability to be installed.
class_docstr_tok: ["This","class","computes","the","loss","function","for","A2C","with","continuous","action","spaces",".","Note","--","--","This","class","requires","tensorflow-probability","to","be","installed","."]
code: def __init__(
      self,
      value_weight,
      entropy_weight,
      mean_index,
      std_index,
      value_index,
  ):
      try:
          import tensorflow_probability as tfp  # noqa: F401
      except ModuleNotFoundError:
          raise ValueError(
              "This class requires tensorflow-probability to be installed."
          )
      self.value_weight = value_weight
      self.entropy_weight = entropy_weight
      self.mean_index = mean_index
      self.std_index = std_index
      self.value_index = value_index
  
imports: import time
  from collections.abc import Sequence
  import numpy
  import tensorflow
  from deepchem.models import KerasModel
  from deepchem.models.optimizers import Adam
label_desc: Use image node_id 1 to create a new A2CLossContinuous object from inherited base classes: object with example: obj = A2CLossContinuous(value_weight, entropy_weight, mean_index, std_index, value_index)