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Tidy up docstrings
This commit is contained in:
Ines Montani
parent
c45ed32c74
commit
852e1f105c
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@ -195,6 +195,7 @@ class Language(object):
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self._meta = value
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# Conveniences to access pipeline components
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# Shouldn't be used anymore!
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@property
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def tensorizer(self):
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return self.get_pipe("tensorizer")
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@ -228,6 +229,8 @@ class Language(object):
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name (unicode): Name of pipeline component to get.
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RETURNS (callable): The pipeline component.
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DOCS: https://spacy.io/api/language#get_pipe
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"""
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for pipe_name, component in self.pipeline:
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if pipe_name == name:
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@ -240,6 +243,8 @@ class Language(object):
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name (unicode): Factory name to look up in `Language.factories`.
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config (dict): Configuration parameters to initialise component.
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RETURNS (callable): Pipeline component.
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DOCS: https://spacy.io/api/language#create_pipe
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"""
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if name not in self.factories:
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if name == "sbd":
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@ -266,9 +271,7 @@ class Language(object):
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first (bool): Insert component first / not first in the pipeline.
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last (bool): Insert component last / not last in the pipeline.
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EXAMPLE:
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>>> nlp.add_pipe(component, before='ner')
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>>> nlp.add_pipe(component, name='custom_name', last=True)
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DOCS: https://spacy.io/api/language#add_pipe
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"""
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if not hasattr(component, "__call__"):
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msg = Errors.E003.format(component=repr(component), name=name)
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@ -310,6 +313,8 @@ class Language(object):
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name (unicode): Name of the component.
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RETURNS (bool): Whether a component of the name exists in the pipeline.
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DOCS: https://spacy.io/api/language#has_pipe
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"""
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return name in self.pipe_names
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@ -318,6 +323,8 @@ class Language(object):
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name (unicode): Name of the component to replace.
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component (callable): Pipeline component.
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DOCS: https://spacy.io/api/language#replace_pipe
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"""
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if name not in self.pipe_names:
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raise ValueError(Errors.E001.format(name=name, opts=self.pipe_names))
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@ -328,6 +335,8 @@ class Language(object):
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old_name (unicode): Name of the component to rename.
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new_name (unicode): New name of the component.
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DOCS: https://spacy.io/api/language#rename_pipe
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"""
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if old_name not in self.pipe_names:
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raise ValueError(Errors.E001.format(name=old_name, opts=self.pipe_names))
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@ -341,6 +350,8 @@ class Language(object):
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name (unicode): Name of the component to remove.
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RETURNS (tuple): A `(name, component)` tuple of the removed component.
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DOCS: https://spacy.io/api/language#remove_pipe
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"""
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if name not in self.pipe_names:
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raise ValueError(Errors.E001.format(name=name, opts=self.pipe_names))
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@ -357,10 +368,7 @@ class Language(object):
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for specific components.
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RETURNS (Doc): A container for accessing the annotations.
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EXAMPLE:
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>>> tokens = nlp('An example sentence. Another example sentence.')
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>>> tokens[0].text, tokens[0].head.tag_
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('An', 'NN')
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DOCS: https://spacy.io/api/language#call
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"""
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if len(text) > self.max_length:
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raise ValueError(
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@ -385,17 +393,7 @@ class Language(object):
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of the block. Otherwise, a DisabledPipes object is returned, that has
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a `.restore()` method you can use to undo your changes.
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EXAMPLE:
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>>> nlp.add_pipe('parser')
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>>> nlp.add_pipe('tagger')
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>>> with nlp.disable_pipes('parser', 'tagger'):
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>>> assert not nlp.has_pipe('parser')
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>>> assert nlp.has_pipe('parser')
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>>> disabled = nlp.disable_pipes('parser')
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>>> assert len(disabled) == 1
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>>> assert not nlp.has_pipe('parser')
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>>> disabled.restore()
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>>> assert nlp.has_pipe('parser')
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DOCS: https://spacy.io/api/language#disable_pipes
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"""
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return DisabledPipes(self, *names)
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@ -411,11 +409,7 @@ class Language(object):
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sgd (callable): An optimizer.
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RETURNS (dict): Results from the update.
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EXAMPLE:
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>>> with nlp.begin_training(gold) as (trainer, optimizer):
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>>> for epoch in trainer.epochs(gold):
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>>> for docs, golds in epoch:
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>>> state = nlp.update(docs, golds, sgd=optimizer)
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DOCS: https://spacy.io/api/language#update
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"""
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if len(docs) != len(golds):
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raise IndexError(Errors.E009.format(n_docs=len(docs), n_golds=len(golds)))
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@ -425,7 +419,6 @@ class Language(object):
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if self._optimizer is None:
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self._optimizer = create_default_optimizer(Model.ops)
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sgd = self._optimizer
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# Allow dict of args to GoldParse, instead of GoldParse objects.
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gold_objs = []
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doc_objs = []
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@ -446,7 +439,6 @@ class Language(object):
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get_grads.alpha = sgd.alpha
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get_grads.b1 = sgd.b1
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get_grads.b2 = sgd.b2
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pipes = list(self.pipeline)
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random.shuffle(pipes)
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if component_cfg is None:
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@ -481,6 +473,7 @@ class Language(object):
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>>> raw_batch = [nlp.make_doc(text) for text in next(raw_text_batches)]
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>>> nlp.rehearse(raw_batch)
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"""
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# TODO: document
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if len(docs) == 0:
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return
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if sgd is None:
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@ -503,7 +496,6 @@ class Language(object):
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get_grads.alpha = sgd.alpha
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get_grads.b1 = sgd.b1
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get_grads.b2 = sgd.b2
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for name, proc in pipes:
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if not hasattr(proc, "rehearse"):
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continue
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@ -511,7 +503,6 @@ class Language(object):
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proc.rehearse(docs, sgd=get_grads, losses=losses, **config.get(name, {}))
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for key, (W, dW) in grads.items():
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sgd(W, dW, key=key)
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return losses
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def preprocess_gold(self, docs_golds):
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@ -534,7 +525,9 @@ class Language(object):
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get_gold_tuples (function): Function returning gold data
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component_cfg (dict): Config parameters for specific components.
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**cfg: Config parameters.
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RETURNS: An optimizer
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RETURNS: An optimizer.
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DOCS: https://spacy.io/api/language#begin_training
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"""
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if get_gold_tuples is None:
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get_gold_tuples = lambda: []
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@ -660,23 +653,19 @@ class Language(object):
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"""Process texts as a stream, and yield `Doc` objects in order.
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texts (iterator): A sequence of texts to process.
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as_tuples (bool):
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If set to True, inputs should be a sequence of
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as_tuples (bool): If set to True, inputs should be a sequence of
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(text, context) tuples. Output will then be a sequence of
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(doc, context) tuples. Defaults to False.
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n_threads (int): Currently inactive.
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batch_size (int): The number of texts to buffer.
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disable (list): Names of the pipeline components to disable.
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cleanup (bool): If True, unneeded strings are freed,
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to control memory use. Experimental.
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component_cfg (dict): An optional dictionary with extra keyword arguments
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for specific components.
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cleanup (bool): If True, unneeded strings are freed to control memory
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use. Experimental.
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component_cfg (dict): An optional dictionary with extra keyword
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arguments for specific components.
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YIELDS (Doc): Documents in the order of the original text.
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EXAMPLE:
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>>> texts = [u'One document.', u'...', u'Lots of documents']
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>>> for doc in nlp.pipe(texts, batch_size=50, n_threads=4):
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>>> assert doc.is_parsed
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DOCS: https://spacy.io/api/language#pipe
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"""
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if as_tuples:
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text_context1, text_context2 = itertools.tee(texts)
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