How to use the plac.call function in plac

centroid = centroids[k]
        plot_series(centroid, centroid_plot_foldpath, 'centroid', True)
        
        members = X[y == k]
        n_samples = members.shape[0]
        sample_rows = np.arange(n_samples)
        np.random.shuffle(sample_rows)        
        
        members_to_plot = members[sample_rows[:10]]
        for i in xrange(members_to_plot.shape[0]):
            print(k, i)
            plot_series(members_to_plot[i], centroid_plot_foldpath, 'ex-%d' % i)
            
if __name__ == '__main__':
    sys.exit(plac.call(main))

nr_row, nr_dim = header.split()
        nlp.vocab.reset_vectors(width=int(nr_dim))
        for line in file_:
            line = line.rstrip().decode("utf8")
            pieces = line.rsplit(" ", int(nr_dim))
            word = pieces[0]
            vector = numpy.asarray([float(v) for v in pieces[1:]], dtype="f")
            nlp.vocab.set_vector(word, vector)  # add the vectors to the vocab
    # test the vectors and similarity
    text = "class colspan"
    doc = nlp(text)
    print(text, doc[0].similarity(doc[1]))


if __name__ == "__main__":
    plac.call(main)

i.interact(verbose=verbose)
        elif multiline:
            i.multiline(verbose=verbose)
        elif serve:
            i.start_server(serve)
    elif batch:
        run((fname,) + extra, 'execute', verbose)
    elif test:
        run((fname,) + extra, 'doctest', verbose)
        print('run %s plac test(s)' % (len(extra) + 1))
    else:
        baseparser.print_usage()
main.add_help = False

if __name__ == '__main__':
    plac.call(main)

def main():
    plac.call(__main_delegate__)

thread = threading.Thread(target=open_browser, args=[browser, url])
        thread.start()
    else:
        print('open following url by web browser', file=sys.stderr)
        print(url, file=sys.stderr)
    displacy.serve(docs, style, options={'compact': True, 'collapse_punct': False})


def open_browser(browser, url, wait=0.5):
    if wait:
        time.sleep(wait)
    browser.open(url)


if __name__ == '__main__':
    plac.call(main)

logger.info(output)

            process = subprocess.Popen(submit_cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
            output, error = process.communicate()
            if error:
                logger.error(error)
            logger.info(output)

            res = os.chdir(f'{cwd}')
            try_log_error(res,f"Changed to directory: {cwd}")
            print(res)
        except Exception as f:
            logger.error(f)

if __name__ == '__main__':
    import plac; plac.call(main)

trainer.record_train_loss(loss)
            with model.use_params(optimizer.averages):
                dev_acc_avg = model.evaluate(dev_X, dev_Y)
                print('Avg dev.: %.3f' % dev_acc_avg)
            trainer.record_dev_acc(dev_acc_avg)

    with model.use_params(optimizer.averages):
        print('Avg dev.: %.3f' % score_model(model, dev_X, dev_Y))
        print('Avg test.: %.3f' % score_model(model, test_X, test_Y))
        with open('out.pickle', 'wb') as file_:
            pickle.dump(model, file_, -1)


if __name__ == '__main__':
    plac.call(main)

#     # Split on double line breaks
    #     [{"IS_SPACE": True, "TEXT": { "REGEX" : "([\r\t ]?[\n]){2,}" }}, {}],
    #     # Split on hard punctuation
    #     [{"IS_PUNCT": True, "TEXT" : { "IN" : ["!", "?"]}}, {}],
    #     # Split on full stop if not followed by lower case letter or digit
    #     [{"IS_PUNCT": True, "TEXT": "."}, {"SHAPE": { "REGEX" : "^[^xd]" }}]
    # ]
    nlp = spacy.load("fr", disable=['ner', 'parser'])
    custom = RuleSentencizer(nlp, **sent_config)
    nlp.add_pipe(custom)
    doc = nlp(text)
    for sent in doc.sents:
        print("<%s>"%sent.text)

if __name__ == "__main__":
    plac.call(main)

@plac.annotations(
    input_path=(video_splitter.__plac_input_path_doc__),
    output_dir_path=(video_splitter.__plac_output_dir_path_doc__),
    melt=(video_splitter.__plac_melt_doc__),
    melt_command_tail=(video_splitter.__plac_melt_command_tail_doc__),
    recursive=(video_splitter.__plac_recursive_doc__, "flag"),
    version=(video_splitter.__plac_version_doc__, "flag"),
    debug=(video_splitter.__plac_debug_doc__, "flag"),
)
def remove_trailing_frame(input_path, output_dir_path, melt=video_splitter.melt_default, melt_command_tail=video_splitter.melt_command_tail_default, recursive=video_splitter.recursive_default, version=False, debug=False):
    """Removes the trailing frame which has been added by accident in versions of video-splitter below 1.2."""
    videoSplitterRemoveTrailingFrame = VideoSplitterRemoveTrailingFrame(input_path, output_dir_path, melt, melt_command_tail, recursive, version, debug)
    videoSplitterRemoveTrailingFrame.removeTrailingFrame()

if __name__ == "__main__":
    plac.call(remove_trailing_frame)

# example7.py
from datetime import datetime

def main(dsn, *scripts):
    "Run the given scripts on the database"
    for script in scripts:
        print('executing %s' % script)
        # ...

if __name__ == '__main__':
    import plac; plac.call(main)