Python MLPDecoder.Config Examples

Example #1

 class Config(ConfigBase):
     representation: SeqRepresentation.Config = SeqRepresentation.Config()
     output_layer: ClassificationOutputLayer.Config = (
         ClassificationOutputLayer.Config())
     decoder: MLPDecoder.Config = MLPDecoder.Config()

Example #2

File: pair_classification_model.py Project: thientu/pytext

 class Config(BaseModel.Config):
     decoder: MLPDecoder.Config = MLPDecoder.Config()
     output_layer: ClassificationOutputLayer.Config = (
         ClassificationOutputLayer.Config()
     )
     encode_relations: bool = True

Example #3

File: pair_classification_model.py Project: facebookresearch/pytext

 class Config(BaseModel.Config):
     decoder: MLPDecoder.Config = MLPDecoder.Config()
     output_layer: Union[
         ClassificationOutputLayer.Config, PairwiseCosineDistanceOutputLayer.Config
     ] = ClassificationOutputLayer.Config()
     encode_relations: bool = True

Example #4

File: pair_classification_model.py Project: tmeng7777/pytext

 class Config(ConfigBase):
     representation: PairRepresentation.Config = PairRepresentation.Config()
     decoder: MLPDecoder.Config = MLPDecoder.Config()
     # TODO: will need to support different output layer for contrastive loss
     output_layer: ClassificationOutputLayer.Config = (
         ClassificationOutputLayer.Config())

Example #5

File: mlp_decoder_test.py Project: facebookresearch/pytext

            def __init__(self, in_dim, out_dim, temp):
                super().__init__()

                self.mlp = MLPDecoder.from_config(
                    MLPDecoder.Config(bias=False, temperature=temp), in_dim, out_dim
                )