tensorflow_probability/python/positive_semidefinite_kernels/positive_semidefinite_kernel.py
def _flatten_multiplicand_list(kernels):
  """Flatten a list of kernels which may contain _ProductKernel instances.

  Args:
    kernels: Python list of `PositiveSemidefiniteKernel` instances

  Returns:
    Python list containing the elements of kernels, with any _ProductKernel
    instances replaced by their `kernels` property contents.
  """
  flattened = []
  for k in kernels:
    if isinstance(k, _ProductKernel):
      flattened += k.kernels
    else:
      flattened.append(k)
  return flattened
def _flatten_multiplicand_list(kernels):
  flattened = []
  for k in kernels:
    if isinstance(k, _ProductKernel):
      flattened += k.kernels
    else:
      flattened.append(k)
  return flattened
def _flatten_multiplicand_list ( kernels ) : flattened = [ ] for k in kernels : if isinstance ( k , _ProductKernel ) : flattened += k . kernels else : flattened . append ( k ) return flattened
Flatten a list of kernels which may contain _ProductKernel instances.

  Args:
    kernels: Python list of `PositiveSemidefiniteKernel` instances

  Returns:
    Python list containing the elements of kernels, with any _ProductKernel
    instances replaced by their `kernels` property contents.
Flatten a list of kernels which may contain _ProductKernel instances .