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Types & classes19 in github.com/Ugness/ELF-pytorch

↓ 5 callersClassRMSNorm
pytorch_lightning/modules/layers.py:35
↓ 4 callersClassSamplingConfig
pytorch_lightning/configs/config.py:10
↓ 3 callersClassELF
pytorch_lightning/modules/model.py:39
↓ 3 callersClassEMA
pytorch_lightning/lightning_module.py:30
↓ 2 callersClassTimestepEmbedder
pytorch_lightning/modules/layers.py:222
↓ 1 callersClassAttention
Self-attention with optional RoPE, head-wise RMSNorm on Q/K, and an optional FlashAttention path.
pytorch_lightning/modules/layers.py:165
↓ 1 callersClassBottleneckTextProj
pytorch_lightning/modules/layers.py:86
↓ 1 callersClassConfig
pytorch_lightning/configs/config.py:28
↓ 1 callersClassELFBlock
pytorch_lightning/modules/model.py:20
↓ 1 callersClassELFDataModule
pytorch_lightning/lightning_module.py:352
↓ 1 callersClassELFLitModule
pytorch_lightning/lightning_module.py:78
↓ 1 callersClassFinalLayer
pytorch_lightning/modules/layers.py:250
↓ 1 callersClassMuon
Muon: Momentum-Orthogonalized by Newton-Schulz. Applies only to 2D matmul-shaped parameters. 1D/embedding/bias parameters should be routed to
pytorch_lightning/utils/muon.py:33
↓ 1 callersClassPerEpochGenEvalCallback
Run 32-step generation + gen_ppl + sample_entropy at every epoch end.
pytorch_lightning/callbacks/gen_eval.py:26
↓ 1 callersClassSwiGLUFFN
pytorch_lightning/modules/layers.py:209
↓ 1 callersClassTextRotaryEmbeddingFast
pytorch_lightning/modules/layers.py:55
ClassEncoderInterface
Frozen text encoder contract for ELF. The ELF transformer needs only three things from an encoder: 1. `d_model` — the hidden size of the la
pytorch_lightning/encoders/base.py:22
ClassMetrics
Generative-PPL + unigram-entropy evaluator (single-process).
pytorch_lightning/utils/metrics_utils.py:20
ClassT5Encoder
Frozen T5 encoder. NO internal op is changed — exact reproduction of HF T5. Notes: * Runs in fp32 (matches ELF JAX). Do not override unless
pytorch_lightning/encoders/t5.py:27