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9167fadab9
transformers/docs/source/en/internal/modeling_utils.md
Pavel Iakubovskii 9167fadab9
Introduce GradientCheckpointingLayer (#37223) 
* GradientCheckpointingLayer

* trigger

* Move GC layer to a separate file

* Update import

* Expose and document GC layer

* Fix dummy

* Apply to llama-based models

* Update modulars

* Update a few more models for consistency

* Update glm4

* Update Janus
2025-04-22 11:33:31 +01:00

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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 and classes it provides for modeling.

Most of those are only useful if you are studying the code of the models in the library.

Layers

autodoc GradientCheckpointingLayer

Attention Functions

autodoc AttentionInterface - register

Rotary Position Embedding Functions

autodoc dynamic_rope_update

Pytorch custom modules

autodoc pytorch_utils.Conv1D

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.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