e94a6641dccda6dd7f8ad86fad82e62388548777,keras/initializers/initializers_v2.py,RandomNormal,__call__,#RandomNormal#Any#Any#,297

Before Change

        `tf.keras.backend.set_floatx(float_dtype)`)
      **kwargs: Additional keyword arguments.
    
    return super(RandomNormal, self).__call__(
        shape, dtype=_get_dtype(dtype), **kwargs)


@keras_export("keras.initializers.TruncatedNormal",
              "keras.initializers.truncated_normal",

After Change

    dtype = _assert_float_dtype(_get_dtype(dtype))
    if _PARTITION_SHAPE in kwargs:
      shape = kwargs[_PARTITION_SHAPE]
    return self._random_generator.random_normal(shape, self.mean, self.stddev,
                                                dtype)

  def get_config(self):
    return {
        "mean": self.mean,

Instances