Loading fairseq/options.py +3 −3 Changes for fairseq/options.py: 3 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -85,11 +85,11 @@ def add_generation_args(parser): help='beam size') group.add_argument('--nbest', default=1, type=int, metavar='N', help='number of hypotheses to output') group.add_argument('--max-len-a', default=0, type=int, metavar='N', help=('generate sequence of maximum length ax + b, ' group.add_argument('--max-len-a', default=0, type=float, metavar='N', help=('generate sequences of maximum length ax + b, ' 'where x is the source length')) group.add_argument('--max-len-b', default=200, type=int, metavar='N', help=('generate sequence of maximum length ax + b, ' help=('generate sequences of maximum length ax + b, ' 'where x is the source length')) group.add_argument('--remove-bpe', nargs='?', const='@@ ', default=None, help='remove BPE tokens before scoring') Loading fairseq/sequence_generator.py +2 −2 Changes for fairseq/sequence_generator.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class SequenceGenerator(object): self.positions = self.positions.cuda() return self def generate_batched_itr(self, data_itr, maxlen_a=0, maxlen_b=200, def generate_batched_itr(self, data_itr, maxlen_a=0.0, maxlen_b=200, cuda_device=None, timer=None): """Iterate over a batched dataset and yield individual translations. Loading @@ -69,7 +69,7 @@ class SequenceGenerator(object): if timer is not None: timer.start() hypos = self.generate(input['src_tokens'], input['src_positions'], maxlen=(maxlen_a*srclen + maxlen_b)) maxlen=int(maxlen_a*srclen + maxlen_b)) if timer is not None: timer.stop(s['ntokens']) for i, id in enumerate(s['id']): Loading Loading
fairseq/options.py +3 −3 Changes for fairseq/options.py: 3 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -85,11 +85,11 @@ def add_generation_args(parser): help='beam size') group.add_argument('--nbest', default=1, type=int, metavar='N', help='number of hypotheses to output') group.add_argument('--max-len-a', default=0, type=int, metavar='N', help=('generate sequence of maximum length ax + b, ' group.add_argument('--max-len-a', default=0, type=float, metavar='N', help=('generate sequences of maximum length ax + b, ' 'where x is the source length')) group.add_argument('--max-len-b', default=200, type=int, metavar='N', help=('generate sequence of maximum length ax + b, ' help=('generate sequences of maximum length ax + b, ' 'where x is the source length')) group.add_argument('--remove-bpe', nargs='?', const='@@ ', default=None, help='remove BPE tokens before scoring') Loading
fairseq/sequence_generator.py +2 −2 Changes for fairseq/sequence_generator.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class SequenceGenerator(object): self.positions = self.positions.cuda() return self def generate_batched_itr(self, data_itr, maxlen_a=0, maxlen_b=200, def generate_batched_itr(self, data_itr, maxlen_a=0.0, maxlen_b=200, cuda_device=None, timer=None): """Iterate over a batched dataset and yield individual translations. Loading @@ -69,7 +69,7 @@ class SequenceGenerator(object): if timer is not None: timer.start() hypos = self.generate(input['src_tokens'], input['src_positions'], maxlen=(maxlen_a*srclen + maxlen_b)) maxlen=int(maxlen_a*srclen + maxlen_b)) if timer is not None: timer.stop(s['ntokens']) for i, id in enumerate(s['id']): Loading