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| # Custom Layers and Utilities | |
| This page lists all the custom layers used by the library, as well as the utility functions it provides for modeling. | |
| Most of those are only useful if you are studying the code of the models in the library. | |
| ## Pytorch custom modules | |
| [[autodoc]] pytorch_utils.Conv1D | |
| [[autodoc]] modeling_utils.PoolerStartLogits | |
| - forward | |
| [[autodoc]] modeling_utils.PoolerEndLogits | |
| - forward | |
| [[autodoc]] modeling_utils.PoolerAnswerClass | |
| - forward | |
| [[autodoc]] modeling_utils.SquadHeadOutput | |
| [[autodoc]] modeling_utils.SQuADHead | |
| - forward | |
| [[autodoc]] modeling_utils.SequenceSummary | |
| - forward | |
| ## PyTorch Helper Functions | |
| [[autodoc]] pytorch_utils.apply_chunking_to_forward | |
| [[autodoc]] pytorch_utils.find_pruneable_heads_and_indices | |
| [[autodoc]] pytorch_utils.prune_layer | |
| [[autodoc]] pytorch_utils.prune_conv1d_layer | |
| [[autodoc]] pytorch_utils.prune_linear_layer | |
| ## TensorFlow custom layers | |
| [[autodoc]] modeling_tf_utils.TFConv1D | |
| [[autodoc]] modeling_tf_utils.TFSharedEmbeddings | |
| - call | |
| [[autodoc]] modeling_tf_utils.TFSequenceSummary | |
| ## TensorFlow loss functions | |
| [[autodoc]] modeling_tf_utils.TFCausalLanguageModelingLoss | |
| [[autodoc]] modeling_tf_utils.TFMaskedLanguageModelingLoss | |
| [[autodoc]] modeling_tf_utils.TFMultipleChoiceLoss | |
| [[autodoc]] modeling_tf_utils.TFQuestionAnsweringLoss | |
| [[autodoc]] modeling_tf_utils.TFSequenceClassificationLoss | |
| [[autodoc]] modeling_tf_utils.TFTokenClassificationLoss | |
| ## TensorFlow Helper Functions | |
| [[autodoc]] modeling_tf_utils.get_initializer | |
| [[autodoc]] modeling_tf_utils.keras_serializable | |
| [[autodoc]] modeling_tf_utils.shape_list | |