53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
import torch
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import json
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from typing import Tuple, Optional
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from text_generation_server.layers.tensor_parallel import TensorParallelHead
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from text_generation_server.layers.medusa import MedusaHeadV1, MedusaHeadV2
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from text_generation_server.layers.mlp import MLPSpeculatorHead
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class SpeculativeHead(torch.nn.Module):
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def __init__(self, lm_head, speculator):
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super().__init__()
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self.head = lm_head
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self.speculator = speculator
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@staticmethod
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def load(config, prefix: str, weights):
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speculator = config.speculator
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if speculator:
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speculator_path = config.speculator["path"]
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speculator_config = str(speculator_path / "config.json")
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with open(speculator_config, "r") as f:
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speculator_config = json.load(f)
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config.speculator_config = speculator_config
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try:
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architecture = speculator_config["architectures"][0]
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if architecture == "MLPSpeculatorPreTrainedModel":
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speculator = MLPSpeculatorHead.load(config, prefix, weights)
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else:
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speculator = None
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except KeyError:
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try:
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speculator = MedusaHeadV1.load(config, prefix, weights)
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except:
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speculator = MedusaHeadV2(config, prefix, weights)
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lm_head = None
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else:
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lm_head = TensorParallelHead.load(config, prefix, weights)
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speculator = None
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return SpeculativeHead(lm_head, speculator)
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def forward(
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self, input: torch.Tensor
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) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
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if self.speculator is not None:
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return self.speculator(input)
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assert self.head is not None
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logits = self.head(input)
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return logits, None
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