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The number of RDMA QPs DeepEP allocates for the Engram buffer is derived from its max_num_tokens, which in turn comes from max_num_batched_tokens (model_loader.py). Raising the QP count therefore required raising the global batched-token budget, which also inflates the EP/MoE/CP buffers. Add DEEPINFER_ENGRAM_MIN_PREFILLING_TOKENS as a lower bound applied only to the Engram buffer, so a deployment can give Engram more QPs without resizing the other buffers. Default 0 keeps the current behavior. |
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| .. | ||
| __init__.py | ||
| attn.py | ||
| builder.py | ||
| compress.py | ||
| containers.py | ||
| cross_layer.py | ||
| engram_metadata.py | ||
| engram_parameters.py | ||
| engram.py | ||
| hc_blocks.py | ||
| hc_lazy.py | ||
| hc.py | ||
| heads.py | ||
| index_attn.py | ||
| linear.py | ||
| mhc_modeling.py | ||
| mhc_ops.py | ||
| mla_attn.py | ||
| mlp.py | ||
| moe.py | ||
| norm.py | ||
| rope.py | ||
| utils.py | ||
| yoco.py | ||