def __init__(self, initializers, sizes, validate_args=False):
    """Creates the `BlockwiseInitializer`.

    Arguments:
      initializers: `list` of Keras initializers, e.g., `"glorot_uniform"` or
        `tf.keras.initializers.Constant(0.5413)`.
      sizes: `list` of `int` scalars representing the number of elements
        associated with each initializer in `initializers`.
      validate_args: Python `bool` indicating we should do (possibly expensive)
        graph-time assertions, if necessary.
    """
    self._initializers = initializers
    self._sizes = sizes
    self._validate_args = validate_args
def __init__ ( self , initializers , sizes , validate_args = False ) : self . _initializers = initializers self . _sizes = sizes self . _validate_args = validate_args
Creates the `BlockwiseInitializer`.

    Arguments:
      initializers: `list` of Keras initializers, e.g., `"glorot_uniform"` or
        `tf.keras.initializers.Constant(0.5413)`.
      sizes: `list` of `int` scalars representing the number of elements
        associated with each initializer in `initializers`.
      validate_args: Python `bool` indicating we should do (possibly expensive)
        graph-time assertions, if necessary.