class_docstr: List property that contains specified element types.
  
  Parameters
  ----------
  n_elements : int
      Number of elements in the list. The ``None``
      value mean that list can contains any number of
      elements. Defaults to ``None``.
  
  element_type : object or tuple
      Type of the elements within the list.
  
  {BaseProperty.Parameters}
class_docstr_tok: ["List","property","that","contains","specified","element","types",".","Parameters","--","--","--","--","--","n_elements",":","int","Number","of","elements","in","the","list",".","The","``","None","``","value","mean","that","list","can","contains","any","number","of","elements",".","Defaults","to","``","None","``",".","element_type",":","object","or","tuple","Type","of","the","elements","within","the","list",".","{","BaseProperty.Parameters","}"]
code: def validate(self, value):
      super(TypedListProperty, self).validate(value)
  
      if self.n_elements is not None and len(value) != self.n_elements:
          raise ValueError(
              "Expected list with {} variables".format(self.n_elements)
          )
  
      if not all(isinstance(v, self.element_type) for v in value):
          element_type = as_tuple(self.element_type)
          type_names = (type_.__name__ for type_ in element_type)
          element_type_name = ", ".join(type_names)
  
          raise TypeError(
              "The `{}` parameter received invalid element types "
              "in list/tuple. Expected element types: {}, Value: {}"
              "".format(self.name, element_type_name, value)
          )
  
imports: import numbers
  import inspect
  import numpy
  import tensorflow
  from neupy import init
  from neupy.utils import as_tuple
  from neupy.core.docs import SharedDocs
label_desc: Use image node_id 2 for calling the TypedListProperty obj's underlying member method code with example usage: obj.validate(value) without return types