tensorflow_probability/python/glm/fisher_scoring.py
def num_cols(x):
  """Returns number of cols in a given `Tensor`."""
  if tf.compat.dimension_value(x.shape[-1]) is not None:
    return tf.compat.dimension_value(x.shape[-1])
  return tf.shape(input=x)[-1]
def num_cols(x):
  """Returns number of cols in a given `Tensor`."""
  if tf.compat.dimension_value(x.shape[-1]) is not None:
    return tf.compat.dimension_value(x.shape[-1])
  return tf.shape(input=x)[-1]
def num_cols ( x ) : if tf . compat . dimension_value ( x . shape [ - 1 ] ) is not None : return tf . compat . dimension_value ( x . shape [ - 1 ] ) return tf . shape ( input = x ) [ - 1 ]
Returns number of cols in a given `Tensor`.
Returns number of cols in a given Tensor .