[E150] The language of the nlp object and the vocab should be the same, but found 'id' and 'en' respectively.

[monWork]

Hi
I am trying to assemble a pipeline with transformers and pre-trained model and a factory component. But running into E150 error.
Assemble pipeline worked fine with en_core_web_lg but want to use transformers instead.
python -m spacy assemble configs/rel_neg_ner_trf.cfg training/rel_neg_ner/ --code scripts/rel_neg_ner_component.py --paths.${vars.neg_news} ../neg_news/training/model-best --paths.spans_key ${vars.spans_key} --verbose

neg_news component is transformer spancat model

Config

[paths]
train = null
dev = null
vectors = "en_core_web_trf"
init_tok2vec = null
neg_news = null
spans_key = "sc"

[system]
gpu_allocator = "pytorch"
seed = 0

[nlp]
lang = "en"
pipeline = ["transformer", "tagger", "parser", "attribute_ruler", "lemmatizer", "ner","neg_news", "rel_neg_ner"]
batch_size = 128
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}

[components]

[components.transformer]
source = "en_core_web_trf"
component = "transformer"

[components.tagger]
source = "en_core_web_trf"
component = "tagger"

[components.parser]
source = "en_core_web_trf"
component = "parser"

[components.attribute_ruler]
source = "en_core_web_trf"
component = "attribute_ruler"

[components.lemmatizer]
source = "en_core_web_trf"
component = "lemmatizer"

[components.ner]
source = "en_core_web_trf"
component = "ner"

[components.neg_news]
source = ${paths.neg_news}
component = "spancat"
span_key = ${paths.spans_key}

[components.rel_neg_ner]
factory = "rel_neg_ner"
span_key = ${paths.spans_key}



[pretraining]

[initialize]
vectors = ${paths.vectors}
init_tok2vec = ${paths.init_tok2vec}
vocab_data = null
lookups = null
before_init = null
after_init = null

[initialize.components]

[initialize.tokenizer]

[initialize.components.spancat]

[david-engelmann]

Do you have spacy-transformers installed?

[monWork]

Yes, spacy[cuda113,transformers,lookups]==3.4.0 is what i have on my environment

[monWork]

================================ rel-neg-ner ================================
Running command: 'C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\python.exe' -m spacy assemble configs/rel_neg_ner.cfg training/rel_neg_ner/ --code scripts/rel_neg_ner_component.py --paths.neg_news ../neg_news/training/model-best --paths.spans_key sc --verbose
[2022-11-04 11:13:52,186] [DEBUG] Config overrides from CLI: ['paths.neg_news', 'paths.spans_key']

=========================== Initializing pipeline ===========================
Traceback (most recent call last):
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\runpy.py", line 194, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\__main__.py", line 4, in <module>
    setup_cli()
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\cli\_util.py", line 71, in setup_cli
    command(prog_name=COMMAND)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\click\core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\click\core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\click\core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\click\core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\click\core.py", line 760, in invoke    return __callback(*args, **kwargs)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\typer\main.py", line 532, in wrapper
    return callback(**use_params)  # type: ignore
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\cli\assemble.py", line 45, in assemble_cli
    nlp = load_model_from_config(config, auto_fill=True)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\util.py", line 554, in load_model_from_config
    nlp = lang_cls.from_config(
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\language.py", line 1839, in from_config
    source_nlps[model] = util.load_model(
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\util.py", line 434, in load_model
    return load_model_from_path(Path(name), **kwargs)  # type: ignore[arg-type]
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\util.py", line 506, in load_model_from_path
    nlp = load_model_from_config(
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\util.py", line 554, in load_model_from_config
    nlp = lang_cls.from_config(
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\language.py", line 1788, in from_config
    nlp = lang_cls(vocab=vocab, create_tokenizer=create_tokenizer, meta=meta)
  File "C:\Users\pilanisp\AppData\Local\miniforge3\envs\tas_models\lib\site-packages\spacy\language.py", line 180, in __init__
    raise ValueError(Errors.E150.format(nlp=self.lang, vocab=vocab.lang))
ValueError: [E150] The language of the `nlp` object and the `vocab` should be the same, but found 'id' and 'en' respectively.```

[ljvmiranda921]

Hi @monWork ,

It seems that you used the demo id grit config, but didn't change the language in some of your components. You might need to retrain your spancat models (neg_news) with en and ensure that the languages are consistent all throughout so that tokenization is the same.

[monWork]

@ljvmiranda921 Thanks for the reply, I found out that error earlier and retrained my spancat model and its working, but still appreciate your response. Thanks