flambe.nlp.classification
¶
Package Contents¶
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class
flambe.nlp.classification.
SSTDataset
(binary: bool = True, phrases: bool = False, cache: bool = True, transform: Dict[str, Union[Field, Dict]] = None)[source]¶ Bases:
flambe.dataset.TabularDataset
The official SST-1 dataset.
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URL
= https://raw.githubusercontent.com/harvardnlp/sent-conv-torch/master/data/¶
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classmethod
_load_file
(cls, path: str, sep: Optional[str] = 't', header: Optional[str] = None, columns: Optional[Union[List[str], List[int]]] = None, encoding: Optional[str] = 'utf-8')¶ Load data from the given path.
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class
flambe.nlp.classification.
TRECDataset
(cache: bool = True, transform: Dict[str, Union[Field, Dict]] = None)[source]¶ Bases:
flambe.dataset.TabularDataset
The official TREC dataset.
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URL
= https://raw.githubusercontent.com/harvardnlp/sent-conv-torch/master/data/¶
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classmethod
_load_file
(cls, path: str, sep: Optional[str] = 't', header: Optional[str] = None, columns: Optional[Union[List[str], List[int]]] = None, encoding: Optional[str] = 'latin-1')¶ Load data from the given path.
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class
flambe.nlp.classification.
NewsGroupDataset
(cache: bool = False, transform: Dict[str, Union[Field, Dict]] = None)[source]¶ Bases:
flambe.dataset.TabularDataset
The official 20 news group dataset.
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class
flambe.nlp.classification.
TextClassifier
(embedder: Embedder, output_layer: Module, dropout: float = 0)[source]¶ Bases:
flambe.nn.Module
Implements a standard classifier.
The classifier is composed of an encoder module, followed by a fully connected output layer, with a dropout layer in between.
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drop
¶ the dropout layer
Type: nn.Dropout
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forward
(self, data: Tensor, target: Optional[Tensor] = None)¶ Run a forward pass through the network.
Parameters: - data (Tensor) – The input data
- target (Tensor, optional) – The input targets, optional
Returns: The output predictions, and optionally the targets
Return type: Union[Tensor, Tuple[Tensor, Tensor]
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