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transformer-xray

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(1) MoE/Loop prototype gets a '✱ 1 of N' / '🔁 1 of N' badge — makes the single example expert/layer obvious inside its container; (2) T5LayerFF / DenseActDense / DenseGatedActDense classified as MLP not Block (matched 'Layer' before); (3) scan_kinds.py utility to audit class→kind mappings across architectures

43cf1fd verified about 1 month ago

debug_models.py

2.37 kB
full sync about 1 month ago
scan_kinds.py

2.46 kB
(1) MoE/Loop prototype gets a '✱ 1 of N' / '🔁 1 of N' badge — makes the single example expert/layer obvious inside its container; (2) T5LayerFF / DenseActDense / DenseGatedActDense classified as MLP not Block (matched 'Layer' before); (3) scan_kinds.py utility to audit class→kind mappings across architectures about 1 month ago
test_architectures.py

7.49 kB
(1) test_architectures.py: 17 archs covered with invariants (head detected, loop present, FLOPs > 0, min depth, source extraction). All pass. (2) FLOPs aggregation fixes: read tree dict 'args'+'repeat' fields (not 'config' which only flat nodes have); Linear+Head both compute 2·in·out; Loop multiplies children by repeat. (3) _eval handles getattr(config, 'X', default) — fixes Llama q_proj resolving num_attention_heads * head_dim. (4) HEAD_ATTR_NAMES adds cls, vocab_projector, embed_out for BERT/DeBERTa/DistilBert variants about 1 month ago