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())