How to use the colorlog.warning function in colorlog

To help you get started, we’ve selected a few colorlog examples, based on popular ways it is used in public projects.

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github bckim92 / sequential-knowledge-transformer / data / holle.py View on Github external
response = tokenize(example['labels'][0])
                else:
                    response = tokenize(example['eval_labels'][0])
                chosen_topic = tokenize(example['chosen_topic'])

                # Set up knowledge
                checked_knowledge = example['title'] + ' __knowledge__ ' + example['checked_sentence']
                knowledges = [checked_knowledge] + \
                    [k for k in example['knowledge'].rstrip().split('\n')]
                for idx, k in enumerate(knowledges[1:]):
                    if k == checked_knowledge:
                        break
                else:
                    # Sometimes, knowledge does not include checked_sentnece
                    idx = None
                    colorlog.warning("Knowledge does not include checked sentence.")
                if idx is not None:
                    del knowledges[idx + 1]

                # Tokenize knowledge
                knowledge_sentences = [tokenize(k) for k in knowledges]

                new_example = {'context': context,
                               'response': response,
                               'chosen_topic': chosen_topic,
                               'knowledge_sentences': knowledge_sentences,
                               'episode_num': episode_num,
                               'example_num': example_num}
                if 'multi_eval_labels' in example:
                    responses = [tokenize(response) for response in example['multi_eval_labels']]
                    new_example['responses'] = responses
                if 'multi_checked_sentences' in example:
github bckim92 / sequential-knowledge-transformer / data / wizard_of_wikipedia.py View on Github external
response = tokenize(example['labels'][0])
                else:
                    response = tokenize(example['eval_labels'][0])
                chosen_topic = tokenize(example['chosen_topic'])

                # Set up knowledge
                checked_knowledge = example['title'] + ' __knowledge__ ' + example['checked_sentence']
                knowledges = [checked_knowledge] + \
                    [k for k in example['knowledge'].rstrip().split('\n')]
                for idx, k in enumerate(knowledges[1:]):
                    if k == checked_knowledge:
                        break
                else:
                    # Sometimes, knowledge does not include checked_sentnece
                    idx = None
                    colorlog.warning("Knowledge does not include checked sentence.")
                if idx is not None:
                    del knowledges[idx + 1]

                # Tokenize knowledge
                knowledge_sentences = [tokenize(k) for k in knowledges]

                new_example = {'context': context,
                               'response': response,
                               'chosen_topic': chosen_topic,
                               'knowledge_sentences': knowledge_sentences,
                               'episode_num': episode_num,
                               'example_num': example_num}
                new_examples.append(new_example)
            new_episodes.append(new_examples)

        if self._datapath: