ValidationError: Value '1.0' could not be converted to Integer

[VikasRajashekar]

how to resolve this error:

I am just running the example code form your tutorial/Readme and I have set it up as you have given instructions.

---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/_internal/config_loader_impl.py in _apply_overrides_to_config(overrides, cfg)
    512                     try:
--> 513                         OmegaConf.update(cfg, key, value, merge=True)
    514                     except (ConfigAttributeError, ConfigKeyError) as ex:

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/omegaconf.py in update(cfg, key, value, merge)
    607                 assert isinstance(node, BaseContainer)
--> 608                 node.merge_with(value)
    609                 return

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/basecontainer.py in merge_with(self, *others)
    330         except Exception as e:
--> 331             self._format_and_raise(key=None, value=None, cause=e)
    332 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/base.py in _format_and_raise(self, key, value, cause, type_override)
    100             cause=cause,
--> 101             type_override=type_override,
    102         )

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/_utils.py in format_and_raise(node, key, value, msg, cause, type_override)
    628             ex.__dict__ = copy.deepcopy(cause.__dict__)
--> 629         _raise(ex, cause)
    630 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/_utils.py in _raise(ex, cause)
    609         ex.__cause__ = None
--> 610     raise ex  # set end OC_CAUSE=1 for full backtrace
    611 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/basecontainer.py in merge_with(self, *others)
    328         try:
--> 329             self._merge_with(*others)
    330         except Exception as e:

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/basecontainer.py in _merge_with(self, *others)
    367                         for item in other:
--> 368                             self.append(item)
    369 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/listconfig.py in append(self, item)
    227         except Exception as e:
--> 228             self._format_and_raise(key=index, value=item, cause=e)
    229             assert False

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/base.py in _format_and_raise(self, key, value, cause, type_override)
    100             cause=cause,
--> 101             type_override=type_override,
    102         )

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/_utils.py in format_and_raise(node, key, value, msg, cause, type_override)
    693 
--> 694     _raise(ex, cause)
    695 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/omegaconf/_utils.py in _raise(ex, cause)
    609         ex.__cause__ = None
--> 610     raise ex  # set end OC_CAUSE=1 for full backtrace
    611 

ValidationError: Value '1.0' could not be converted to Integer
    full_key: optimization.update_freq[0]
    reference_type=List[int]
    object_type=list

The above exception was the direct cause of the following exception:

ConfigCompositionException                Traceback (most recent call last)
<ipython-input-5-7b307de7abc6> in <module>
      7 # Note: WMT'19 models use fastBPE instead of subword_nmt, see instructions below
      8 en2de = torch.hub.load('pytorch/fairseq', 'transformer.wmt16.en-de',
----> 9                        tokenizer='moses', bpe='subword_nmt')
     10 en2de.eval()  # disable dropout
     11 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/torch/hub.py in load(repo_or_dir, model, *args, **kwargs)
    368         repo_or_dir = _get_cache_or_reload(repo_or_dir, force_reload, verbose)
    369 
--> 370     model = _load_local(repo_or_dir, model, *args, **kwargs)
    371     return model
    372 

~/anaconda3/envs/fair2/lib/python3.7/site-packages/torch/hub.py in _load_local(hubconf_dir, model, *args, **kwargs)
    397 
    398     entry = _load_entry_from_hubconf(hub_module, model)
--> 399     model = entry(*args, **kwargs)
    400 
    401     sys.path.remove(hubconf_dir)

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/models/fairseq_model.py in from_pretrained(cls, model_name_or_path, checkpoint_file, data_name_or_path, **kwargs)
    275             data_name_or_path,
    276             archive_map=cls.hub_models(),
--> 277             **kwargs,
    278         )
    279         logger.info(x["args"])

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/hub_utils.py in from_pretrained(model_name_or_path, checkpoint_file, data_name_or_path, archive_map, **kwargs)
     71     models, args, task = checkpoint_utils.load_model_ensemble_and_task(
     72         [os.path.join(model_path, cpt) for cpt in checkpoint_file.split(os.pathsep)],
---> 73         arg_overrides=kwargs,
     74     )
     75 

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/checkpoint_utils.py in load_model_ensemble_and_task(filenames, arg_overrides, task, strict, suffix, num_shards, state)
    289                 raise IOError("Model file not found: {}".format(filename))
    290             if state is None:
--> 291                 state = load_checkpoint_to_cpu(filename, arg_overrides)
    292             if "args" in state and state["args"] is not None:
    293                 cfg = convert_namespace_to_omegaconf(state["args"])

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/checkpoint_utils.py in load_checkpoint_to_cpu(path, arg_overrides)
    235         overwrite_args_by_name(state["cfg"], arg_overrides)
    236 
--> 237     state = _upgrade_state_dict(state)
    238     return state
    239 

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/checkpoint_utils.py in _upgrade_state_dict(state)
    466             state["args"].post_process = state["args"].remove_bpe
    467 
--> 468         state["cfg"] = convert_namespace_to_omegaconf(state["args"])
    469 
    470     if "cfg" in state and state["cfg"] is not None:

~/.cache/torch/hub/pytorch_fairseq_master/fairseq/dataclass/utils.py in convert_namespace_to_omegaconf(args)
    343     with initialize(config_path=config_path):
    344         try:
--> 345             composed_cfg = compose("config", overrides=overrides, strict=False)
    346         except:
    347             logger.error("Error when composing. Overrides: " + str(overrides))

~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/experimental/compose.py in compose(config_name, overrides, strict, return_hydra_config)
     35         strict=strict,
     36         from_shell=False,
---> 37         with_log_configuration=False,
     38     )
     39     assert isinstance(cfg, DictConfig)

~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/_internal/hydra.py in compose_config(self, config_name, overrides, run_mode, strict, with_log_configuration, from_shell)
    510             strict=strict,
    511             run_mode=run_mode,
--> 512             from_shell=from_shell,
    513         )
    514         with open_dict(cfg):

~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/_internal/config_loader_impl.py in load_configuration(self, config_name, overrides, run_mode, strict, from_shell)
    154                 run_mode=run_mode,
    155                 strict=strict,
--> 156                 from_shell=from_shell,
    157             )
    158         except OmegaConfBaseException as e:

~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/_internal/config_loader_impl.py in _load_configuration(self, config_name, overrides, run_mode, strict, from_shell)
    275 
    276         # Apply command line overrides after enabling strict flag
--> 277         ConfigLoaderImpl._apply_overrides_to_config(config_overrides, cfg)
    278 
    279         app_overrides = []

~/anaconda3/envs/fair2/lib/python3.7/site-packages/hydra/_internal/config_loader_impl.py in _apply_overrides_to_config(overrides, cfg)
    520                 raise ConfigCompositionException(
    521                     f"Error merging override {override.input_line}"
--> 522                 ) from ex
    523 
    524     @staticmethod

ConfigCompositionException: Error merging override optimization.update_freq=[1.0]

[sophgit]

Hi, I am having the same error and would also appreciate some help! Thanks :)

[myleott]

Which tutorial/README did you follow? Can you share the exact command you ran, and also mention what version of fairseq you're using (0.10.1, master, ...)?

[ZhaoQianfeng]

I got the same error when I follow the fairseq document tutorial,I download wmt16.en-de.joined-dict.transformer,and follow the instructions.But failded, same error.

[ZhaoQianfeng]

the command I use is:

>MODEL_DIR=wmt16.en-de.joined-dict.transformer
>fairseq-interactive --path $MODEL_DIR/model.pt $MODEL_DIR --beam 5 --source-lang en --target-lang de --tokenizer moses --bpe subword_nmt --bpe-codes $MODEL_DIR/bpecodes

The fairseq version is 1.0.0a0+f13f299

[ZhaoQianfeng]

the command I use is:

>MODEL_DIR=wmt16.en-de.joined-dict.transformer
>fairseq-interactive --path $MODEL_DIR/model.pt $MODEL_DIR --beam 5 --source-lang en --target-lang de --tokenizer moses --bpe subword_nmt --bpe-codes $MODEL_DIR/bpecodes

The fairseq version is 1.0.0a0+f13f299

after I uninstalled master(1.0.0) version and installed v0.10.0, it works fine and no error

[yuchenlin]

having the same error when using the master version and run

torch.hub.load('pytorch/fairseq', 'transformer.wmt14.en-fr',
                                    checkpoint_file='model.pt',
                                    tokenizer='moses', bpe='fastbpe')

but it works with other models such as transformer.wmt19.en-de

[mcao516]

I manually set update_freq to [1] in fairseq/fairseq/checkpoint_utils.py and it works:

def load_checkpoint_to_cpu(path, arg_overrides=None):
    """Loads a checkpoint to CPU (with upgrading for backward compatibility)."""
    with open(PathManager.get_local_path(path), "rb") as f:
        state = torch.load(f, map_location=torch.device("cpu"))

    if "args" in state and state["args"] is not None and arg_overrides is not None:
        args = state["args"]
        for arg_name, arg_val in arg_overrides.items():
            setattr(args, arg_name, arg_val)

    if "cfg" in state and state["cfg"] is not None and arg_overrides is not None:
        overwrite_args_by_name(state["cfg"], arg_overrides)

    state['args'].update_freq = [1]  # manually set to [1]
    state = _upgrade_state_dict(state)
    return state

[stale[bot]]

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