#!/usr/bin/env python3

# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Convert a dataset into the ParlAI text format.

Examples
--------

.. code-block:: shell

  python convert_data_to_fasttext_format.py -t babi:task1k:1 --outfile /tmp/dump
"""

from parlai.core.params import ParlaiParser
from parlai.agents.repeat_label.repeat_label import RepeatLabelAgent
from parlai.core.worlds import create_task
from parlai.utils.misc import TimeLogger
import random
import tempfile


def dump_data(opt):
    # create repeat label agent and assign it to the specified task
    agent = RepeatLabelAgent(opt)
    world = create_task(opt, agent)
    if opt['outfile'] is None:
        outfile = tempfile.mkstemp(
            prefix='{}_{}_'.format(opt['task'], opt['datatype']), suffix='.txt'
        )[1]
    else:
        outfile = opt['outfile']

    if opt['num_examples'] == -1:
        num_examples = world.num_examples()
    else:
        num_examples = opt['num_examples']
    log_timer = TimeLogger()

    print('[ starting to convert.. ]')
    print('[ saving output to {} ]'.format(outfile))
    fw = open(outfile, 'w')
    text = ''
    for _ in range(num_examples):
        world.parley()
        world.acts[0]['labels'] = world.acts[0].get(
            'labels', world.acts[0].pop('eval_labels', None)
        )

        samp = world.acts[0]
        text += samp["text"].replace("\n", " ") + " "
        fw.write("__label__%s %s\n" % (samp["labels"][0].replace(' ', '_'), text))
        if world.acts[0].get('episode_done', False):
            text = ''

        if log_timer.time() > opt['log_every_n_secs']:
            text, _log = log_timer.log(world.total_parleys, world.num_examples())
            print(text)

        if world.epoch_done():
            print('EPOCH DONE')
            break
    fw.close()


def main():
    random.seed(42)
    # Get command line arguments
    parser = ParlaiParser()
    parser.add_argument(
        '-n',
        '--num-examples',
        default=-1,
        type=int,
        help='Total number of exs to convert, -1 to convert \
                                all examples',
    )
    parser.add_argument(
        '-of',
        '--outfile',
        default=None,
        type=str,
        help='Output file where to save, by default will be \
                                created in /tmp',
    )
    parser.add_argument('-ltim', '--log-every-n-secs', type=float, default=2)
    parser.set_defaults(datatype='train:ordered')
    opt = parser.parse_args()
    dump_data(opt)


if __name__ == '__main__':
    main()
