def __init__()

in baselines/common/tf_util.py [0:0]

• 10 lines of code
• 8 McCabe index (conditional complexity)

    def __init__(self, inputs, outputs, updates, givens):
        for inpt in inputs:
            if not hasattr(inpt, 'make_feed_dict') and not (type(inpt) is tf.Tensor and len(inpt.op.inputs) == 0):
                assert False, "inputs should all be placeholders, constants, or have a make_feed_dict method"
        self.inputs = inputs
        self.input_names = {inp.name.split("/")[-1].split(":")[0]: inp for inp in inputs}
        updates = updates or []
        self.update_group = tf.group(*updates)
        self.outputs_update = list(outputs) + [self.update_group]
        self.givens = {} if givens is None else givens