def mutate_and_reset()

in models/attentive_nas_dynamic_model.py [0:0]

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

    def mutate_and_reset(self, cfg, prob=0.1, keep_resolution=False):
        cfg = copy.deepcopy(cfg)
        pick_another = lambda x, candidates: x if len(candidates) == 1 else random.choice([v for v in candidates if v != x])
        # sample a resolution
        r = random.random()
        if r < prob and not keep_resolution:
            cfg['resolution'] = pick_another(cfg['resolution'], self.cfg_candidates['resolution'])

        # sample channels, depth, kernel_size, expand_ratio
        for k in ['width', 'depth', 'kernel_size', 'expand_ratio']:
            for _i, _v in enumerate(cfg[k]):
                r = random.random()
                if r < prob:
                    cfg[k][_i] = pick_another(cfg[k][_i], int2list(self.cfg_candidates[k][_i]))

        self.set_active_subnet(
            cfg['resolution'], cfg['width'], cfg['depth'], cfg['kernel_size'], cfg['expand_ratio']
        )
        return cfg