def main(): parser = setup_args() parser.set_defaults( model='projects.personachat.kvmemnn.kvmemnn:Kvmemnn', model_file='models:convai2/kvmemnn/model', numthreads=40, ) opt = parser.parse_args(print_args=False) # build all profile memory models fnames = ['kvmemnn.tgz'] opt['model_type'] = 'kvmemnn' # for builder download_models(opt, fnames, 'convai2') return eval_hits(opt, print_parser=parser)
def main(): parser = setup_args() parser.set_params( model='legacy:seq2seq:0', model_file='models:convai2/seq2seq/convai2_self_seq2seq_model', dict_file='models:convai2/seq2seq/convai2_self_seq2seq_model.dict', dict_lower=True, rank_candidates=True, batchsize=32, ) opt = parser.parse_args(print_args=False) if (opt.get('model_file', '').find('convai2/seq2seq/convai2_self_seq2seq_model') != -1): opt['model_type'] = 'seq2seq' fnames = [ 'convai2_self_seq2seq_model.tgz', 'convai2_self_seq2seq_model.dict', 'convai2_self_seq2seq_model.opt' ] download_models(opt, fnames, 'convai2', version='v3.0') return eval_hits(opt, 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. """Evaluate pre-trained model trained for hits@1 metric Key-Value Memory Net model trained on convai2:self """ from parlai.core.build_data import download_models from projects.convai2.eval_hits import setup_args, eval_hits if __name__ == '__main__': parser = setup_args() parser.set_defaults( model='projects.personachat.kvmemnn.kvmemnn:Kvmemnn', model_file='models:convai2/kvmemnn/model', numthreads=40, ) opt = parser.parse_args(print_args=False) # build all profile memory models fnames = ['kvmemnn.tgz'] opt['model_type'] = 'kvmemnn' # for builder download_models(opt, fnames, 'convai2') eval_hits(opt, print_parser=parser)