def _run_test_repeat(self, tmpdir: str, fake_input: FakeInput): outfile = os.path.join(tmpdir, 'log.jsonl') pp = interactive.setup_args() opt = pp.parse_args(['-m', 'repeat_query', '--outfile', outfile]) interactive.interactive(opt) log = conversations.Conversations(outfile) self.assertEqual(len(log), fake_input.max_episodes) for entry in log: self.assertEqual(len(entry), 2 * fake_input.max_turns)
#!/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. """ Basic example which allows local human keyboard input to talk to a trained model. For documentation, see parlai.scripts.interactive. """ from parlai.scripts.interactive import setup_args, interactive import random if __name__ == '__main__': random.seed(42) parser = setup_args() opt = parser.parse_args() interactive(opt, print_parser=parser)
from parlai.core.build_data import download_models from parlai.core.params import ParlaiParser from parlai.scripts.interactive import interactive from projects.personachat.persona_seq2seq import PersonachatSeqseqAgentBasic '''Interact with pre-trained model Generative model trained on personachat using persona 'self' Run from ParlAI directory ''' if __name__ == '__main__': parser = ParlaiParser(add_model_args=True) parser.add_argument('-d', '--display-examples', type='bool', default=False) PersonachatSeqseqAgentBasic.add_cmdline_args(parser) parser.set_defaults( dict_file='models:personachat/profile_memory/fulldict.dict', interactive_mode=True, task='parlai.agents.local_human.local_human:LocalHumanAgent', model= 'projects.personachat.persona_seq2seq:PersonachatSeqseqAgentBasic', model_file= 'models:personachat/seq2seq_personachat/seq2seq_no_dropout0.2_lstm_1024_1e-3' ) opt = parser.parse_args() opt['model_type'] = 'seq2seq_personachat' # for builder # build all profile memory models fnames = ['seq2seq_no_dropout0.2_lstm_1024_1e-3', 'fulldict.dict'] download_models(opt, fnames, 'personachat') interactive(opt)
def test_repeat(self): pp = interactive.setup_args() opt = pp.parse_args( ['-m', 'repeat_query', '-t', 'convai2', '-dt', 'valid'], print_args=False) interactive.interactive(opt)
def test_repeat(self): pp = interactive.setup_args() opt = pp.parse_args(['-m', 'repeat_query'], print_args=False) interactive.interactive(opt)
#!/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. from parlai.scripts.interactive import setup_args, interactive import random if __name__ == '__main__': random.seed(42) parser = setup_args() parser.set_params(batchsize=1, beam_size=20, beam_min_n_best=10) print('\n' + '*' * 80) print( 'WARNING: This dialogue model is a research project that was trained on a' ) print( 'large amount of open-domain Twitter data. It may generate offensive content.' ) print('*' * 80 + '\n') interactive(parser.parse_args(print_args=False), print_parser=parser)
#!/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. from parlai.scripts.interactive import setup_args, interactive import random if __name__ == '__main__': random.seed(42) parser = setup_args() parser.set_params(batchsize=1, beam_size=20, beam_min_n_best=10) print('\n' + '*' * 80) print( 'WARNING: This dialogue model is a research project that was trained on a' ) print( 'large amount of open-domain Twitter data. It may generate offensive content.' ) print('*' * 80 + '\n') interactive(parser.parse_args())