class_docstr: A class used to set and get weights for Tensorflow networks.
  
  Attributes:
      sess (tf.Session): The tensorflow session used to run assignment.
      variables (Dict[str, tf.Variable]): Extracted variables from the loss
          or additional variables that are passed in.
      placeholders (Dict[str, tf.placeholders]): Placeholders for weights.
      assignment_nodes (Dict[str, tf.Tensor]): Nodes that assign weights.
class_docstr_tok: ["A","class","used","to","set","and","get","weights","for","Tensorflow","networks",".","Attributes",":","sess","(","tf.Session",")",":","The","tensorflow","session","used","to","run","assignment",".","variables","(","Dict","[","str",",","tf.Variable","]",")",":","Extracted","variables","from","the","loss","or","additional","variables","that","are","passed","in",".","placeholders","(","Dict","[","str",",","tf.placeholders","]",")",":","Placeholders","for","weights",".","assignment_nodes","(","Dict","[","str",",","tf.Tensor","]",")",":","Nodes","that","assign","weights","."]
docstr: Returns the total length of all of the flattened variables.
  
  Returns:
      The length of all flattened variables concatenated.
docstr_tok: ["Returns","the","total","length","of","all","of","the","flattened","variables",".","Returns",":","The","length","of","all","flattened","variables","concatenated","."]
code: def get_flat_size(self):
      """Returns the total length of all of the flattened variables.
  
      Returns:
          The length of all flattened variables concatenated.
      """
      return sum(
          np.prod(v.get_shape().as_list())
          for v in self.variables.values()
      )
  
file_path: ray/python/ray/experimental/tf_utils.py
imports: from collections import OrderedDict, deque
  import numpy
  from ray.rllib.utils import force_list
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 2 for calling the TensorFlowVariables obj's underlying member method code with example usage: obj.get_flat_size() and returns: sum