class_docstr: Generate fake data of given shapes
class_docstr_tok: ["Generate","fake","data","of","given","shapes"]
code: def __iter__(self):
      if self.random:
          for _ in range(self._size):
              val = []
              for k in range(len(self.shapes)):
                  v = (
                      self.rng.rand(*self.shapes[k])
                      * (self.domain[k][1] - self.domain[k][0])
                      + self.domain[k][0]
                  )
                  val.append(v.astype(self.dtype[k]))
              yield val
      else:
          val = []
          for k in range(len(self.shapes)):
              v = (
                  self.rng.rand(*self.shapes[k])
                  * (self.domain[k][1] - self.domain[k][0])
                  + self.domain[k][0]
              )
              val.append(v.astype(self.dtype[k]))
          for _ in range(self._size):
              yield copy.copy(val)
  
imports: import copy
  import numpy
  import six
  from .base import DataFlow, RNGDataFlow
label_desc: Use image node_id 3 for calling the FakeData obj's underlying member method code with example usage: obj.__iter__() without return types