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	remove redundant __call__ method in pipes.TextCategorizer (#4305)
* remove redundant __call__ method in pipes.TextCategorizer Because the parent __call__ method behaves in the same way. * fix: Pipe.__call__ arg * fix: invalid arg in Pipe.__call__ * modified: spacy/tests/regression/test_issue4278.py (#4278) * deleted: Pipfile
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					@ -69,7 +69,7 @@ class Pipe(object):
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        predictions = self.predict([doc])
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					        predictions = self.predict([doc])
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        if isinstance(predictions, tuple) and len(predictions) == 2:
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					        if isinstance(predictions, tuple) and len(predictions) == 2:
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            scores, tensors = predictions
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					            scores, tensors = predictions
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            self.set_annotations([doc], scores, tensor=tensors)
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					            self.set_annotations([doc], scores, tensors=tensors)
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        else:
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					        else:
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            self.set_annotations([doc], predictions)
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					            self.set_annotations([doc], predictions)
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        return doc
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					        return doc
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					@ -90,7 +90,7 @@ class Pipe(object):
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            predictions = self.predict(docs)
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					            predictions = self.predict(docs)
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            if isinstance(predictions, tuple) and len(tuple) == 2:
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					            if isinstance(predictions, tuple) and len(tuple) == 2:
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                scores, tensors = predictions
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					                scores, tensors = predictions
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                self.set_annotations(docs, scores, tensor=tensors)
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					                self.set_annotations(docs, scores, tensors=tensors)
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            else:
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					            else:
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                self.set_annotations(docs, predictions)
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					                self.set_annotations(docs, predictions)
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            yield from docs
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					            yield from docs
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					@ -932,11 +932,6 @@ class TextCategorizer(Pipe):
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    def labels(self, value):
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					    def labels(self, value):
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        self.cfg["labels"] = tuple(value)
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					        self.cfg["labels"] = tuple(value)
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    def __call__(self, doc):
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        scores, tensors = self.predict([doc])
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        self.set_annotations([doc], scores, tensors=tensors)
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        return doc
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    def pipe(self, stream, batch_size=128, n_threads=-1):
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					    def pipe(self, stream, batch_size=128, n_threads=-1):
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        for docs in util.minibatch(stream, size=batch_size):
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					        for docs in util.minibatch(stream, size=batch_size):
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            docs = list(docs)
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					            docs = list(docs)
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					@ -13,7 +13,7 @@ class DummyPipe(Pipe):
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    def predict(self, docs):
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					    def predict(self, docs):
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        return ([1, 2, 3], [4, 5, 6])
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					        return ([1, 2, 3], [4, 5, 6])
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    def set_annotations(self, docs, scores, tensor=None):
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					    def set_annotations(self, docs, scores, tensors=None):
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        return docs
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					        return docs
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