165         samples = []
175                     samples.append(self.table[pos][i])
176                     if len(samples) == sample_size:
180             if pos == index or len(samples) == sample_size:
182         assert len(samples) <= sample_size
183         return samples
511     def prioritize_samples(self, samples, auxilliary_info):  argument
524     def prioritize_samples(self, samples, auxilliary_info):  argument
526             samples,
536     def prioritize_samples(self, samples, auxilliary_info):  argument
538             samples,
548     def prioritize_samples(self, samples, auxilliary_info):  argument
549         return sorted(samples, cmp=lambda e1, e2: e1.value.num_hits - e2.value.num_hits)
588     def prioritize_samples(self, samples, auxilliary_info):  argument
591         return sorted(samples, cmp=lambda e1, e2: self.compare(e1, e2, now))
641     def prioritize_samples(self, samples, auxilliary_info):  argument
647             samples,
948             samples = self.table.random_sample(kSampleSize)
949             samples = self.policies[policy_index].prioritize_samples(
950                 samples,
953             for hash_entry in samples:
1030         samples = [
1033         selected_policy = max(range(len(self.policies)), key=lambda x: samples[x])