class_docstr: Initializer that generates tensors with a uniform distribution.
  
  The generated values follow a uniform distribution in the range
  ``[minval, maxval)``.
class_docstr_tok: ["Initializer","that","generates","tensors","with","a","uniform","distribution",".","The","generated","values","follow","a","uniform","distribution","in","the","range","``","[","minval",",","maxval",")","``","."]
code: def __call__(self, shape: types.ShapeLike, dtype: tf.DType):
      dtype = _as_numerical_dtype(dtype)
      return tf.random.uniform(
          shape=shape,
          minval=self.minval,
          maxval=self.maxval,
          dtype=dtype,
          seed=self.seed,
      )
  
imports: import abc
  import collections
  from typing import Iterable, Mapping, Optional, Union
  import numpy
  from sonnet.src import types
  import tensorflow
label_desc: Use image node_id 2 for calling the RandomUniform obj's underlying member method code with example usage: obj.__call__(shape, dtype) and returns: tf