36 lines
1.0 KiB
Python
36 lines
1.0 KiB
Python
import logging
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import re
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import torch
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logger = logging.getLogger(__name__)
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def get_layer_id(weight_name):
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# example weight name: model.layers.10.self_attn.qkv_proj.weight
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match = re.search(r"layers\.(\d+)\.", weight_name)
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if match:
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return int(match.group(1))
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return None
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class PPMissingLayer(torch.nn.Identity):
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# Adapted from
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# https://github.com/vllm-project/vllm/blob/18ed3132d2bfe1df9a74729457b69243955221e8/vllm/model_executor/models/utils.py#L468C1-L486C1
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"""
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A placeholder layer for missing layers in a pipeline parallel model.
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"""
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def __init__(self, *args, **kwargs):
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super().__init__()
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self.return_tuple = kwargs.get("return_tuple", False)
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def forward(self, *args, **kwargs):
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"""
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Return the first arg from args or the first value from kwargs.
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Wraps the input in a tuple if `self.return_tuple` is True.
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"""
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input = args[0] if args else next(iter(kwargs.values()))
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return (input,) if self.return_tuple else input
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