Default 'textcat' pipe not working

[riZZZhik]

Hi, got an issue with using 'textcat' pipe

Initialization:

import spacy

doc = "Apple is looking at buying U.K. startup for $1 billion in 10 days"
nlp = spacy.load('en_core_web_sm')
textcat = nlp.add_pipe('textcat')

Code

tokens = nlp(doc)  # Crashes already on this line
category = textcat(tokens)
print(category)

Error

Traceback (most recent call last):
  File "/Users/rizhik/Desktop/dev/belinsky/test.py", line 7, in <module>
    tokens = nlp(doc)
  File "/opt/homebrew/lib/python3.10/site-packages/spacy/language.py", line 1022, in __call__
    error_handler(name, proc, [doc], e)
  File "/opt/homebrew/lib/python3.10/site-packages/spacy/util.py", line 1617, in raise_error
    raise e
  File "/opt/homebrew/lib/python3.10/site-packages/spacy/language.py", line 1017, in __call__
    doc = proc(doc, **component_cfg.get(name, {}))  # type: ignore[call-arg]
  File "spacy/pipeline/trainable_pipe.pyx", line 56, in spacy.pipeline.trainable_pipe.TrainablePipe.__call__
  File "/opt/homebrew/lib/python3.10/site-packages/spacy/util.py", line 1617, in raise_error
    raise e
  File "spacy/pipeline/trainable_pipe.pyx", line 52, in spacy.pipeline.trainable_pipe.TrainablePipe.__call__
  File "/opt/homebrew/lib/python3.10/site-packages/spacy/pipeline/textcat.py", line 191, in predict
    scores = self.model.predict(docs)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 315, in predict
    return self._func(self, X, is_train=False)[0]
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/chain.py", line 54, in forward
    Y, inc_layer_grad = layer(X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 291, in __call__
    return self._func(self, X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/concatenate.py", line 44, in forward
    Ys, callbacks = zip(*[layer(X, is_train=is_train) for layer in model.layers])
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/concatenate.py", line 44, in <listcomp>
    Ys, callbacks = zip(*[layer(X, is_train=is_train) for layer in model.layers])
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 291, in __call__
    return self._func(self, X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/chain.py", line 54, in forward
    Y, inc_layer_grad = layer(X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 291, in __call__
    return self._func(self, X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/with_cpu.py", line 24, in forward
    cpu_outputs, backprop = model.layers[0].begin_update(_to_cpu(X))
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 309, in begin_update
    return self._func(self, X, is_train=True)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/chain.py", line 54, in forward
    Y, inc_layer_grad = layer(X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 291, in __call__
    return self._func(self, X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/layers/resizable.py", line 27, in forward
    Y, callback = layer(X, is_train=is_train)
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 291, in __call__
    return self._func(self, X, is_train=is_train)
  File "thinc/layers/sparselinear.pyx", line 43, in thinc.layers.sparselinear.forward
  File "thinc/layers/sparselinear.pyx", line 68, in thinc.layers.sparselinear._begin_cpu_update
  File "/opt/homebrew/lib/python3.10/site-packages/thinc/model.py", line 175, in get_dim
    raise ValueError(err)
ValueError: Cannot get dimension 'nO' for model 'sparse_linear': value unset

Info about spaCy

• spaCy version: 3.2.4
• Platform: macOS-12.3.1-arm64-arm-64bit
• Python version: 3.10.2
• Pipelines: en_core_web_sm (3.2.0), ru_core_news_lg (3.2.0), ru_core_news_sm (3.2.0), ru_core_news_md (3.2.0)

[thomashacker]

Hello,
the error is thrown because the added textcat component is not initialized (https://spacy.io/api/textcategorizer#initialize). However, to be able to use the textcat component you need to train it first (https://spacy.io/usage/training).

If you're new to spaCy, I'd recommend the free spaCy online course which covers all the fundamentals of using spaCy and training your own ML components.