Not able to run textcat.pipe() after loading TextCategorizer from disk

Issue

I’m trying to load a self-trained TextCategorizer model, and run it for an already pre-processed documents (e.g. by using textcat.pipe(docs)) I started with this tutorial: https://github.com/explosion/spaCy/blob/master/examples/training/train_textcat.py

The training and evaluation works just fine, but when I try to reload the pipeline/model I get stuck. I can not store the model, only the pipeline (workaround: disable the other components). This shouldn’t be an issue, I just load it and then select the textcat pipeline. But when I try to apply it on documents, I receive the error:

  File "<..>\Python37\lib\site-packages\thinc\api.py", line 295, in begin_update
    X, bp_layer = layer.begin_update(layer.ops.flatten(seqs_in, pad=pad), drop=drop)
  File "ops.pyx", line 150, in thinc.neural.ops.Ops.flatten
  File "<__array_function__ internals>", line 6, in concatenate
ValueError: need at least one array to concatenate

My class where I try to load the trained TextCategorizer:

class SentenceSplitter:

    def __init__(self, path):
        self.loaded_pipeline = spacy.load(path)
        self.categorizer = self.loaded_pipeline.get_pipe(TextCategorizer.name)

    def __cal__(doc):
        for sentence in doc.sents:
            self.categorizer.pipe([sentence.as_doc()])  # This is not possible/fails

More or less (e.g. the model is created and not loaded), the exact same thing is done during training and there it works. Any ideas?

Environment

• spaCy version: 2.2.4
• Platform: Windows-10-10.0.19041-SP0
• Python version: 3.7.9

[afftek]

Hi @aftek, do I understand it correctly that you’re still experiencing a (different) issue with the ensemble architecture? If so - could you post a minimal code snippet that reproduces the error?

yes, I do have issues with ensemble - same error message, not sure what the issue itself is. I will try to find the minimal code which fails and post it as soon as I have it.

[svlandeg]

Ooooh, apologies!