Loading fairseq/utils.py +8 −0 Changes for fairseq/utils.py: 8 added lines, 0 removed lines. Original line number Diff line number Diff line Loading @@ -127,6 +127,7 @@ def load_ensemble_for_inference(filenames, src_dict, dst_dict): torch.load(filename, map_location=lambda s, l: default_restore_location(s, 'cpu')) ) args = states[0]['args'] args = _upgrade_args(args) # build ensemble ensemble = [] Loading @@ -137,6 +138,13 @@ def load_ensemble_for_inference(filenames, src_dict, dst_dict): return ensemble def _upgrade_args(args): if not hasattr(args, 'max_source_positions'): args.max_source_positions = args.max_positions args.max_target_positions = args.max_positions return args def prepare_sample(sample, volatile=False, cuda_device=None): """Wrap input tensors in Variable class.""" Loading Loading
fairseq/utils.py +8 −0 Changes for fairseq/utils.py: 8 added lines, 0 removed lines. Original line number Diff line number Diff line Loading @@ -127,6 +127,7 @@ def load_ensemble_for_inference(filenames, src_dict, dst_dict): torch.load(filename, map_location=lambda s, l: default_restore_location(s, 'cpu')) ) args = states[0]['args'] args = _upgrade_args(args) # build ensemble ensemble = [] Loading @@ -137,6 +138,13 @@ def load_ensemble_for_inference(filenames, src_dict, dst_dict): return ensemble def _upgrade_args(args): if not hasattr(args, 'max_source_positions'): args.max_source_positions = args.max_positions args.max_target_positions = args.max_positions return args def prepare_sample(sample, volatile=False, cuda_device=None): """Wrap input tensors in Variable class.""" Loading