Function rec_eval

hyperopt/pyll/base.py:766–925

expr - pyll Apply instance to be evaluated memo - optional dictionary of values to use for particular nodes deepcopy_inputs - deepcopy inputs to every node prior to calling that node's function on those inputs. If this leads to a different return value, then some funct

(
    expr,
    deepcopy_inputs=False,
    memo=None,
    max_program_len=None,
    memo_gc=True,
    print_trace=False,
    print_node_on_error=True,
)

def rec_eval(
    expr,
    deepcopy_inputs=False,
    memo=None,
    max_program_len=None,
    memo_gc=True,
    print_trace=False,
    print_node_on_error=True,
):
    """
    expr - pyll Apply instance to be evaluated

    memo - optional dictionary of values to use for particular nodes

    deepcopy_inputs - deepcopy inputs to every node prior to calling that
        node's function on those inputs. If this leads to a different return
        value, then some function (XXX add more complete DebugMode
        functionality) in your graph is modifying its inputs and causing
        mis-calculation. XXX: This is not a fully-functional DebugMode because
        if the offender happens on account of the toposort order to be the last
        user of said input, then it will not be detected as a potential
        problem.

    """
    if max_program_len == None:
        max_program_len = DEFAULT_MAX_PROGRAM_LEN

    if deepcopy_inputs not in (0, 1, False, True):
        # -- I've been calling rec_eval(expr, memo) by accident a few times
        #    this error would have been appreciated.
        raise ValueError("deepcopy_inputs should be bool", deepcopy_inputs)

    node = as_apply(expr)
    topnode = node

    if memo is None:
        memo = {}
    else:
        memo = dict(memo)

    # -- hack for speed
    #    since the inputs are constant during rec_eval
    #    but not constant in general
    node_inputs = {}
    node_list = []
    dfs(node, node_list, seqset=node_inputs)

    # TODO: optimize dfs to not recurse past the items in memo
    #       this is especially important for evaluating Lambdas
    #       which cause rec_eval to recurse
    #
    # N.B. that Lambdas may expand the graph during the evaluation
    #      so that this iteration may be an incomplete
    if memo_gc:
        clients = {}
        for aa in node_list:
            clients.setdefault(aa, set())
            for ii in node_inputs[aa]: