parameters: (self, feed_dict=None, session=None)
return_statement: return SparseTensorValue(indices, values, shape)
docstring: Evaluates this sparse tensor in a `Session`.
  
      Calling this method will execute all preceding operations that
      produce the inputs needed for the operation that produces this
      tensor.
  
      *N.B.* Before invoking `SparseTensor.eval()`, its graph must have been
      launched in a session, and either a default session must be
      available, or `session` must be specified explicitly.
  
      Args:
        feed_dict: A dictionary that maps `Tensor` objects to feed values.
          See [`Session.run()`](../../api_docs/python/client.md#Session.run) for a
          description of the valid feed values.
        session: (Optional.) The `Session` to be used to evaluate this sparse
          tensor. If none, the default session will be used.
  
      Returns:
        A `SparseTensorValue` object.
docstring_summary: Evaluates this sparse tensor in a `Session`.
docstring_tokens: Evaluates this sparse tensor in a Session .
function: def eval(self, feed_dict=None, session=None):
      """Evaluates this sparse tensor in a `Session`.
  
      Calling this method will execute all preceding operations that
      produce the inputs needed for the operation that produces this
      tensor.
  
      *N.B.* Before invoking `SparseTensor.eval()`, its graph must have been
      launched in a session, and either a default session must be
      available, or `session` must be specified explicitly.
  
      Args:
        feed_dict: A dictionary that maps `Tensor` objects to feed values.
          See [`Session.run()`](../../api_docs/python/client.md#Session.run) for a
          description of the valid feed values.
        session: (Optional.) The `Session` to be used to evaluate this sparse
          tensor. If none, the default session will be used.
  
      Returns:
        A `SparseTensorValue` object.
      """
      indices, values, shape = _eval_using_default_session(
          [self.indices, self.values, self.shape], feed_dict, self.graph, session)
      return SparseTensorValue(indices, values, shape)
function_tokens: def eval ( self , feed_dict = None , session = None ) : indices , values , shape = _eval_using_default_session ( [ self . indices , self . values , self . shape ] , feed_dict , self . graph , session ) return SparseTensorValue ( indices , values , shape )