tensorflow_probability/python/distributions/joint_distribution_sequential.py
def _get_required_args(fn):
  """Returns the distribution's required args."""
  argspec = tf_inspect.getfullargspec(fn)
  args = argspec.args
  if tf_inspect.isclass(fn):
    args = args[1:]  # Remove the `self` arg.
  if argspec.defaults:
    # Remove the args which have defaults. By convention we only feed
    # *required args*. This means some distributions must always be wrapped
    # with a `lambda`, e.g., `lambda logits: tfd.Bernoulli(logits=logits)`
    # or `lambda probs: tfd.Bernoulli(probs=probs)`.
    args = args[:-len(argspec.defaults)]
  return tuple(args)
def _get_required_args(fn):
  argspec = tf_inspect.getfullargspec(fn)
  args = argspec.args
  if tf_inspect.isclass(fn):
    args = args[1:]  # Remove the `self` arg.
  if argspec.defaults:
    # Remove the args which have defaults. By convention we only feed
    # *required args*. This means some distributions must always be wrapped
    # with a `lambda`, e.g., `lambda logits: tfd.Bernoulli(logits=logits)`
    # or `lambda probs: tfd.Bernoulli(probs=probs)`.
    args = args[:-len(argspec.defaults)]
  return tuple(args)
def _get_required_args ( fn ) : argspec = tf_inspect . getfullargspec ( fn ) args = argspec . args if tf_inspect . isclass ( fn ) : args = args [ 1 : ] # Remove the `self` arg. if argspec . defaults : # Remove the args which have defaults. By convention we only feed # *required args*. This means some distributions must always be wrapped # with a `lambda`, e.g., `lambda logits: tfd.Bernoulli(logits=logits)` # or `lambda probs: tfd.Bernoulli(probs=probs)`. args = args [ : - len ( argspec . defaults ) ] return tuple ( args )
Returns the distribution's required args.
Returns the distribution s required args .