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- Layer-major KV / state layout so per-layer views are contiguous graph inputs (the executor copied non-contiguous inputs every call). - One compiled entry per (class, method), rank as a registered buffer, no layer_idx guard: every layer reuses the same graphs and loaded NEFFs. - fp8 weight rescale on the host (numpy LUT, ~2 min instead of 35+ min of eager per-shape compiles); engram sf packing on the host. - int16 ue8m0 packing in fp32 (int32 interleaved slices narrowed to int16 crash neuronx-cc, NCC_IBCG902). - Token embedding and the text model's vision tower stay in host memory on Neuron (2.5 GiB of HBM a rank). - offline example: --max_num_seqs. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> |
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| .. | ||
| asc | ||
| cuda | ||
| neuron | ||
| __init__.py | ||
| cache_common.py | ||
| candidate_blocks.py | ||
| common.py | ||
| compress.py | ||
| compute_seqlens_k_zos.py | ||
| conftest.py | ||
| dflash_copy.py | ||
| dflash.py | ||
| flash_mla_utils.py | ||
| fused_sample.py | ||
| fused_transform.py | ||
| gather_engram_tokens_zos.py | ||
| gather_input_ids_zos.py | ||
| gather.py | ||
| get_kv_index.py | ||
| image_embed_ops.py | ||
| kv_index_cat.py | ||
| load_paged_kv_cache.py | ||
| norm.py | ||
| ops.py | ||
| outlier_detection.py | ||
| prepare_cp_mirror.py | ||
| prepare_v4_decode_metadata.py | ||
| random_sampling.py | ||
| sampler.py | ||
| schedule_mtp_varlen.py | ||
| state_cache.py | ||
| store_kv_cache.py | ||
| store_mtp_info.py | ||
| structure_output.py | ||
| sum_smaller_probs.py | ||
| swa_index.py | ||