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translator = from_pretrained(tag='mm-all-iter1')
| [src] dictionary: 40897 types | [tgt] dictionary: 40897 types /content/ilmulti/ilmulti/translator/translator.py:37: UserWarning: utils.load_ensemble_for_inference is deprecated. Please use checkpoint_utils.load_model_ensemble instead. self.models, model_args = fairseq.utils.load_ensemble_for_inference(model_paths, self.task, model_arg_overrides=eval(args.model_overrides)) --------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-22-f8e48d2129df> in <module>() ----> 1 translator = from_pretrained(tag='mm-to-en-iter1') 7 frames /content/ilmulti/ilmulti/translator/pretrained.py in from_pretrained(tag, use_cuda) 60 from .mt_engine import MTEngine 61 ---> 62 translator = build_translator(config['model'], use_cuda=use_cuda) 63 segmenter = build_segmenter(config['segmenter']) 64 tokenizer = build_tokenizer(config['tokenizer']) /content/ilmulti/ilmulti/translator/translator.py in build_translator(model, use_cuda) 169 args.enhance(**keyword_arguments) 170 --> 171 fseq_translator = FairseqTranslator(args, use_cuda=use_cuda) 172 return fseq_translator 173 /content/ilmulti/ilmulti/translator/translator.py in __init__(self, args, use_cuda) 35 # print('| loading model(s) from {}'.format(args.path)) 36 model_paths = args.path.split(':') ---> 37 self.models, model_args = fairseq.utils.load_ensemble_for_inference(model_paths, self.task, model_arg_overrides=eval(args.model_overrides)) 38 self.tgt_dict = self.task.target_dictionary 39 /usr/local/lib/python3.6/dist-packages/fairseq/utils.py in load_ensemble_for_inference(filenames, task, model_arg_overrides) 28 ) 29 return checkpoint_utils.load_model_ensemble( ---> 30 filenames, arg_overrides=model_arg_overrides, task=task, 31 ) 32 /usr/local/lib/python3.6/dist-packages/fairseq/checkpoint_utils.py in load_model_ensemble(filenames, arg_overrides, task) 154 task (fairseq.tasks.FairseqTask, optional): task to use for loading 155 """ --> 156 ensemble, args, _task = _load_model_ensemble(filenames, arg_overrides, task) 157 return ensemble, args 158 /usr/local/lib/python3.6/dist-packages/fairseq/checkpoint_utils.py in _load_model_ensemble(filenames, arg_overrides, task) 165 if not os.path.exists(filename): 166 raise IOError('Model file not found: {}'.format(filename)) --> 167 state = load_checkpoint_to_cpu(filename, arg_overrides) 168 169 args = state['args'] /usr/local/lib/python3.6/dist-packages/fairseq/checkpoint_utils.py in load_checkpoint_to_cpu(path, arg_overrides) 141 for arg_name, arg_val in arg_overrides.items(): 142 setattr(args, arg_name, arg_val) --> 143 state = _upgrade_state_dict(state) 144 return state 145 /usr/local/lib/python3.6/dist-packages/fairseq/checkpoint_utils.py in _upgrade_state_dict(state) 319 320 # set any missing default values in the task, model or other registries --> 321 set_defaults(tasks.TASK_REGISTRY[state['args'].task]) 322 set_defaults(models.ARCH_MODEL_REGISTRY[state['args'].arch]) 323 for registry_name, REGISTRY in registry.REGISTRIES.items(): KeyError: 'shared-multilingual-translation'
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Okay, do a bunch of package changes (fairseq==0.8.0 to a fork). I have managed a final self-contained colab-notebook implementation. https://colab.research.google.com/drive/1KOvjawhzPXOQ6RLlFBFeInkuuR0QAWTK?usp=sharing
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translator = from_pretrained(tag='mm-all-iter1')
The text was updated successfully, but these errors were encountered: