code: def load(path, dtype, broadcastable, mmap_mode=None):
      """
      Load an array from an .npy file.
  
      Parameters
      ----------
      path
          A Generic symbolic variable, that will contain a string
      dtype : data-type
          The data type of the array to be read.
      broadcastable
          The broadcastable pattern of the loaded array, for instance,
          (False,) for a vector, (False, True) for a column,
          (False, False) for a matrix.
      mmap_mode
          How the file will be loaded. None means that the
          data will be copied into an array in memory, 'c' means that the file
          will be mapped into virtual memory, so only the parts that are
          needed will be actually read from disk and put into memory.
          Other modes supported by numpy.load ('r', 'r+', 'w+') cannot
          be supported by Theano.
  
      Examples
      --------
      >>> from theano import *
      >>> path = Variable(Generic())
      >>> x = tensor.load(path, 'int64', (False,))
      >>> y = x*2
      >>> fn = function([path], y)
      >>> fn("stored-array.npy")  # doctest: +SKIP
      array([0, 2, 4, 6, 8], dtype=int64)
  
      """
  
      return LoadFromDisk(dtype, broadcastable, mmap_mode)(path)
  
imports: from __future__ import absolute_import, print_function, division
  import numpy
  from theano import gof
  from theano.gof import Constant, Generic, Op
  from theano.gof.sched import key_to_cmp
  from theano.tensor import tensor
  import theano
label_desc: Use image node_id 1 for calling a global function with example usage: load(path, dtype, broadcastable, mmap_mode) and returns: LoadFromDisk