tensorflow_probability/python/mcmc/internal/util.py
def safe_sum(x, alt_value=-np.inf, name=None):
  """Elementwise adds list members, replacing non-finite results with alt_value.

  Typically the `alt_value` is chosen so the `MetropolisHastings`
  `TransitionKernel` always rejects the proposal.

  Args:
    x: Python `list` of `Tensors` to elementwise add.
    alt_value: Python scalar used to replace any elementwise sums which would
      otherwise be non-finite.
    name: Python `str` name prefixed to Ops created by this function.
      Default value: `None` (i.e., "safe_sum").

  Returns:
    safe_sum: `Tensor` representing the elementwise sum of list of `Tensor`s
      `x` or `alt_value` where sums are non-finite.

  Raises:
    TypeError: if `x` is not list-like.
    ValueError: if `x` is empty.
  """
  with tf.compat.v1.name_scope(name, 'safe_sum', [x, alt_value]):
    if not is_list_like(x):
      raise TypeError('Expected list input.')
    if not x:
      raise ValueError('Input should not be empty.')
    in_shape = x[0].shape
    x = tf.stack(x, axis=-1)
    x = tf.reduce_sum(input_tensor=x, axis=-1)
    alt_value = np.array(alt_value, x.dtype.as_numpy_dtype)
    alt_fill = tf.fill(tf.shape(input=x), value=alt_value)
    x = tf.where(tf.math.is_finite(x), x, alt_fill)
    x.set_shape(x.shape.merge_with(in_shape))
    return x
def safe_sum(x, alt_value=-np.inf, name=None):
  with tf.compat.v1.name_scope(name, 'safe_sum', [x, alt_value]):
    if not is_list_like(x):
      raise TypeError('Expected list input.')
    if not x:
      raise ValueError('Input should not be empty.')
    in_shape = x[0].shape
    x = tf.stack(x, axis=-1)
    x = tf.reduce_sum(input_tensor=x, axis=-1)
    alt_value = np.array(alt_value, x.dtype.as_numpy_dtype)
    alt_fill = tf.fill(tf.shape(input=x), value=alt_value)
    x = tf.where(tf.math.is_finite(x), x, alt_fill)
    x.set_shape(x.shape.merge_with(in_shape))
    return x
def safe_sum ( x , alt_value = - np . inf , name = None ) : with tf . compat . v1 . name_scope ( name , 'safe_sum' , [ x , alt_value ] ) : if not is_list_like ( x ) : raise TypeError ( 'Expected list input.' ) if not x : raise ValueError ( 'Input should not be empty.' ) in_shape = x [ 0 ] . shape x = tf . stack ( x , axis = - 1 ) x = tf . reduce_sum ( input_tensor = x , axis = - 1 ) alt_value = np . array ( alt_value , x . dtype . as_numpy_dtype ) alt_fill = tf . fill ( tf . shape ( input = x ) , value = alt_value ) x = tf . where ( tf . math . is_finite ( x ) , x , alt_fill ) x . set_shape ( x . shape . merge_with ( in_shape ) ) return x
Elementwise adds list members, replacing non-finite results with alt_value.

  Typically the `alt_value` is chosen so the `MetropolisHastings`
  `TransitionKernel` always rejects the proposal.

  Args:
    x: Python `list` of `Tensors` to elementwise add.
    alt_value: Python scalar used to replace any elementwise sums which would
      otherwise be non-finite.
    name: Python `str` name prefixed to Ops created by this function.
      Default value: `None` (i.e., "safe_sum").

  Returns:
    safe_sum: `Tensor` representing the elementwise sum of list of `Tensor`s
      `x` or `alt_value` where sums are non-finite.

  Raises:
    TypeError: if `x` is not list-like.
    ValueError: if `x` is empty.
Elementwise adds list members replacing non - finite results with alt_value .