def sync_from_root(sess, variables, comm=None):
    """
    Send the root node's parameters to every worker.
    Arguments:
      sess: the TensorFlow session.
      variables: all parameter variables including optimizer's
    """
    if comm is None: comm = MPI.COMM_WORLD
    import tensorflow as tf
    values = comm.bcast(sess.run(variables))
    sess.run([tf.assign(var, val)
        for (var, val) in zip(variables, values)])
def sync_from_root(sess, variables, comm=None):
    """
    Send the root node's parameters to every worker.
    Arguments:
      sess: the TensorFlow session.
      variables: all parameter variables including optimizer's
    """
    if comm is None: comm = MPI.COMM_WORLD
    import tensorflow as tf
    values = comm.bcast(sess.run(variables))
    sess.run([tf.assign(var, val)
        for (var, val) in zip(variables, values)])
def sync_from_root ( sess , variables , comm = None ) : if comm is None : comm = MPI . COMM_WORLD import tensorflow as tf values = comm . bcast ( sess . run ( variables ) ) sess . run ( [ tf . assign ( var , val ) for ( var , val ) in zip ( variables , values ) ] )
Send the root node's parameters to every worker.
    Arguments:
      sess: the TensorFlow session.
      variables: all parameter variables including optimizer's
Send the root node s parameters to every worker . Arguments : sess : the TensorFlow session . variables : all parameter variables including optimizer s