class_docstr: Symbolic `Type` representing a numpy.ndarray value.
  
  Initialize self.dtype and self.broadcastable.
  
  Parameters
  ----------
  dtype: str
      Corresponding to numpy dtype (e.g., 'int64')
      The value (ndarray) associated to a `Variable` of this `Type` will
      have this dtype.
  broadcastable: tuple, list, or array of boolean values
      This argument serves two purposes. First, the True elements of this
      list indicate the dimensions where the shape of an associated value
      must be 1. Secondly, the length of this list is the number of
      dimensions that an associated value must have. See
      doc:`broadcasting` for an explanation of how this list is used.
  name : str
      Optional name for this type.
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docstr: Return the information needed to compute the memory size of ``obj``.
  
  The memory size is only the data, so this excludes the container.
  For an ndarray, this is the data, but not the ndarray object and
  other data structures such as shape and strides.
  
  ``get_shape_info()`` and ``get_size()`` work in tandem for the memory
  profiler.
  
  ``get_shape_info()`` is called during the execution of the function.
  So it is better that it is not too slow.
  
  ``get_size()`` will be called on the output of this function
  when printing the memory profile.
  
  Parameters
  ----------
  obj
      The object that this Type represents during execution.
  
  Returns
  -------
  object
      Python object that ``self.get_size()`` understands.
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code: def get_shape_info(self, obj):
      """
      Return the information needed to compute the memory size of ``obj``.
  
      The memory size is only the data, so this excludes the container.
      For an ndarray, this is the data, but not the ndarray object and
      other data structures such as shape and strides.
  
      ``get_shape_info()`` and ``get_size()`` work in tandem for the memory
      profiler.
  
      ``get_shape_info()`` is called during the execution of the function.
      So it is better that it is not too slow.
  
      ``get_size()`` will be called on the output of this function
      when printing the memory profile.
  
      Parameters
      ----------
      obj
          The object that this Type represents during execution.
  
      Returns
      -------
      object
          Python object that ``self.get_size()`` understands.
  
      """
      return obj.shape
  
imports: from __future__ import absolute_import, print_function, division
  import logging
  import warnings
  import numpy
  import theano
  from theano import config
  from theano.gof import hashtype, Type, Variable
  from theano import scalar
label_desc: Use image node_id 30 for calling the TensorType obj's underlying member method code with example usage: obj.get_shape_info(obj) and returns: obj