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Merge branch 'explosion:master' into master

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Renat Shigapov 2021-09-13 08:43:48 +02:00 committed by GitHub
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2
spacy/ml/models/parser.py
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@ -56,7 +56,7 @@ def build_tb_parser_model(
non-linearity if use_upper=False. non-linearity if use_upper=False.
use_upper (bool): Whether to use an additional hidden layer after the state use_upper (bool): Whether to use an additional hidden layer after the state
vector in order to predict the action scores. It is recommended to set vector in order to predict the action scores. It is recommended to set
this to False for large pretrained models such as transformers, and False this to False for large pretrained models such as transformers, and True
for smaller networks. The upper layer is computed on CPU, which becomes for smaller networks. The upper layer is computed on CPU, which becomes
a bottleneck on larger GPU-based models, where it's also less necessary. a bottleneck on larger GPU-based models, where it's also less necessary.
nO (int or None): The number of actions the model will predict between. nO (int or None): The number of actions the model will predict between.

2
website/docs/usage/processing-pipelines.md
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@ -795,7 +795,7 @@ if there's no state to be passed through – spaCy can just take care of this fo
you. The following two code examples are equivalent: you. The following two code examples are equivalent:
```python ```python
# Statless component with @Language.factory # Stateless component with @Language.factory
@Language.factory("my_component") @Language.factory("my_component")
def create_my_component(): def create_my_component():
def my_component(doc): def my_component(doc):

6
website/meta/universe.json
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@ -3285,15 +3285,17 @@
"slogan": "Forte is a toolkit for building Natural Language Processing pipelines, featuring cross-task interaction, adaptable data-model interfaces and composable pipelines.", "slogan": "Forte is a toolkit for building Natural Language Processing pipelines, featuring cross-task interaction, adaptable data-model interfaces and composable pipelines.",
"description": "Forte provides a platform to assemble state-of-the-art NLP and ML technologies in a highly-composable fashion, including a wide spectrum of tasks ranging from Information Retrieval, Natural Language Understanding to Natural Language Generation.", "description": "Forte provides a platform to assemble state-of-the-art NLP and ML technologies in a highly-composable fashion, including a wide spectrum of tasks ranging from Information Retrieval, Natural Language Understanding to Natural Language Generation.",
"github": "asyml/forte", "github": "asyml/forte",
"pip": "forte.spacy torch", "pip": "forte.spacy stave torch",
"code_example": [ "code_example": [
"from forte.spacy import SpacyProcessor", "from fortex.spacy import SpacyProcessor",
"from forte.processors.stave import StaveProcessor",
"from forte import Pipeline", "from forte import Pipeline",
"from forte.data.readers import StringReader", "from forte.data.readers import StringReader",
"", "",
"pipeline = Pipeline()", "pipeline = Pipeline()",
"pipeline.set_reader(StringReader())", "pipeline.set_reader(StringReader())",
"pipeline.add(SpacyProcessor())", "pipeline.add(SpacyProcessor())",
"pipeline.add(StaveProcessor())",
"pipeline.run('Running SpaCy with Forte!')" "pipeline.run('Running SpaCy with Forte!')"
], ],
"code_language": "python", "code_language": "python",