def init_op()

in lm_human_preferences/language/trained_models.py [0:0]

• 23 lines of code
• 9 McCabe index (conditional complexity)

    def init_op(self, params, new_scope):
        assert params
        params = dict(**params)
        checkpoint = self.checkpoint()
        available = tf.train.list_variables(checkpoint)
        unchanged = {}

        for name, shape in available:
            our_name = name
            if self.scope:
                if name.startswith(self.scope):
                    our_name = name[len(self.scope):].lstrip('/')
                else:
                    continue
            # Annoying hack since some code uses 'scope/model' as the scope and other code uses just 'scope'
            our_name = '%s/%s' % (new_scope, our_name)
            if our_name not in params:
                # NOTE: this happens for global_step and optimizer variables
                # (e.g. beta1_power, beta2_power, blah/Adam, blah/Adam_1)
                # print(f'{name} is missing for scope {new_scope}')
                continue
            var = params[our_name]
            del params[our_name]
            assert var.shape == shape, 'Shape mismatch: %s.shape = %s != %s' % (var.op.name, var.shape, shape)
            unchanged[name] = var
        for name in params.keys():
            print(f'Param {name} is missing from checkpoint {checkpoint}')
        tf.train.init_from_checkpoint(checkpoint, unchanged)