tensorflow_probability/python/internal/prefer_static.py
def cond(pred, true_fn=None, false_fn=None, name=None):
  """Return either `true_fn()` if predicate `pred` is true else `false_fn()`.

  If `pred` is a bool or has a constant value, we return either `true_fn()`
  or `false_fn()`, otherwise we use `tf.cond` to dynamically route to both.

  Arguments:
    pred: A scalar determining whether to return the result of `true_fn` or
      `false_fn`.
    true_fn: The callable to be performed if pred is true.
    false_fn: The callable to be performed if pred is false.
    name: Optional name prefix when using `tf.cond`.

  Returns:
    Tensors returned by the call to either `true_fn` or `false_fn`.

  Raises:
    TypeError: If `true_fn` or `false_fn` is not callable.
  """
  if not callable(true_fn):
    raise TypeError('`true_fn` must be callable.')
  if not callable(false_fn):
    raise TypeError('`false_fn` must be callable.')

  pred_value = _get_static_predicate(pred)
  if pred_value is not None:
    if pred_value:
      return true_fn()
    else:
      return false_fn()
  else:
    return tf.cond(pred=pred, true_fn=true_fn, false_fn=false_fn, name=name)
def cond(pred, true_fn=None, false_fn=None, name=None):
  """Return either `true_fn()` if predicate `pred` is true else `false_fn()`.

  If `pred` is a bool or has a constant value, we return either `true_fn()`
  or `false_fn()`, otherwise we use `tf.cond` to dynamically route to both.

  Arguments:
    pred: A scalar determining whether to return the result of `true_fn` or
      `false_fn`.
    true_fn: The callable to be performed if pred is true.
    false_fn: The callable to be performed if pred is false.
    name: Optional name prefix when using `tf.cond`.

  Returns:
    Tensors returned by the call to either `true_fn` or `false_fn`.

  Raises:
    TypeError: If `true_fn` or `false_fn` is not callable.
  """
  if not callable(true_fn):
    raise TypeError('`true_fn` must be callable.')
  if not callable(false_fn):
    raise TypeError('`false_fn` must be callable.')

  pred_value = _get_static_predicate(pred)
  if pred_value is not None:
    if pred_value:
      return true_fn()
    else:
      return false_fn()
  else:
    return tf.cond(pred=pred, true_fn=true_fn, false_fn=false_fn, name=name)
def cond ( pred , true_fn = None , false_fn = None , name = None ) : if not callable ( true_fn ) : raise TypeError ( '`true_fn` must be callable.' ) if not callable ( false_fn ) : raise TypeError ( '`false_fn` must be callable.' ) pred_value = _get_static_predicate ( pred ) if pred_value is not None : if pred_value : return true_fn ( ) else : return false_fn ( ) else : return tf . cond ( pred = pred , true_fn = true_fn , false_fn = false_fn , name = name )
Return either `true_fn()` if predicate `pred` is true else `false_fn()`.

  If `pred` is a bool or has a constant value, we return either `true_fn()`
  or `false_fn()`, otherwise we use `tf.cond` to dynamically route to both.

  Arguments:
    pred: A scalar determining whether to return the result of `true_fn` or
      `false_fn`.
    true_fn: The callable to be performed if pred is true.
    false_fn: The callable to be performed if pred is false.
    name: Optional name prefix when using `tf.cond`.

  Returns:
    Tensors returned by the call to either `true_fn` or `false_fn`.

  Raises:
    TypeError: If `true_fn` or `false_fn` is not callable.
Return either true_fn () if predicate pred is true else false_fn () .