tensorflow_probability/python/positive_semidefinite_kernels/matern.py
def _init_params(self, amplitude, length_scale, validate_args):
    """Shared init logic for `amplitude` and `length_scale` params.

    Args:
      amplitude: `Tensor` (or convertible) or `None` to convert, validate.
      length_scale: `Tensor` (or convertible) or `None` to convert, validate.
      validate_args: If `True`, parameters are checked for validity despite
        possibly degrading runtime performance

    Returns:
      dtype: The common `DType` of the parameters.
    """
    dtype = util.maybe_get_common_dtype(
        [amplitude, length_scale])
    if amplitude is not None:
      amplitude = tf.convert_to_tensor(
          value=amplitude, name='amplitude', dtype=dtype)
    self._amplitude = _validate_arg_if_not_none(
        amplitude, tf.compat.v1.assert_positive, validate_args)
    if length_scale is not None:
      length_scale = tf.convert_to_tensor(
          value=length_scale, name='length_scale', dtype=dtype)
    self._length_scale = _validate_arg_if_not_none(
        length_scale, tf.compat.v1.assert_positive, validate_args)
    return dtype
def _init_params(self, amplitude, length_scale, validate_args):
    dtype = util.maybe_get_common_dtype(
        [amplitude, length_scale])
    if amplitude is not None:
      amplitude = tf.convert_to_tensor(
          value=amplitude, name='amplitude', dtype=dtype)
    self._amplitude = _validate_arg_if_not_none(
        amplitude, tf.compat.v1.assert_positive, validate_args)
    if length_scale is not None:
      length_scale = tf.convert_to_tensor(
          value=length_scale, name='length_scale', dtype=dtype)
    self._length_scale = _validate_arg_if_not_none(
        length_scale, tf.compat.v1.assert_positive, validate_args)
    return dtype
def _init_params ( self , amplitude , length_scale , validate_args ) : dtype = util . maybe_get_common_dtype ( [ amplitude , length_scale ] ) if amplitude is not None : amplitude = tf . convert_to_tensor ( value = amplitude , name = 'amplitude' , dtype = dtype ) self . _amplitude = _validate_arg_if_not_none ( amplitude , tf . compat . v1 . assert_positive , validate_args ) if length_scale is not None : length_scale = tf . convert_to_tensor ( value = length_scale , name = 'length_scale' , dtype = dtype ) self . _length_scale = _validate_arg_if_not_none ( length_scale , tf . compat . v1 . assert_positive , validate_args ) return dtype
Shared init logic for `amplitude` and `length_scale` params.

    Args:
      amplitude: `Tensor` (or convertible) or `None` to convert, validate.
      length_scale: `Tensor` (or convertible) or `None` to convert, validate.
      validate_args: If `True`, parameters are checked for validity despite
        possibly degrading runtime performance

    Returns:
      dtype: The common `DType` of the parameters.
Shared init logic for amplitude and length_scale params .