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https://github.com/huggingface/text-generation-inference.git
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formatting
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9a0262f38c
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@ -23,17 +23,17 @@ from text_generation_server.utils.logits_process import (
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class NextTokenChooser:
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def __init__(
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self,
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watermark=False,
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temperature=1.0,
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repetition_penalty=1.0,
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top_k=None,
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top_p=None,
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typical_p=None,
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do_sample=False,
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seed=0,
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device="cpu",
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logit_bias={},
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self,
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watermark=False,
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temperature=1.0,
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repetition_penalty=1.0,
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top_k=None,
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top_p=None,
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typical_p=None,
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do_sample=False,
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seed=0,
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device="cpu",
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logit_bias={},
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):
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self.watermark_processor = (
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WatermarkLogitsProcessor(device=device) if watermark else None
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@ -97,7 +97,9 @@ class NextTokenChooser:
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do_sample=pb.do_sample,
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seed=pb.seed,
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device=device,
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logit_bias=dict([(tuple(tokenizer.encode(bias.string, add_special_tokens=False).input_ids[0]), bias.bias) for bias in pb.logit_bias]),
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logit_bias=dict(
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[(tuple(tokenizer.encode(bias.string, add_special_tokens=False).input_ids[0]), bias.bias) for bias in
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pb.logit_bias]),
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)
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@ -199,7 +201,7 @@ class HeterogeneousNextTokenChooser:
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self.sequence_bias_logits_processor = (
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HeterogeneousProcessorWrapper({
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i: SequenceBiasLogitsProcessor(
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bias
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bias
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)
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for i, bias in enumerate(logit_bias)
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if any([bias[k] != 0.0 for k in bias])
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@ -299,7 +301,9 @@ bias
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seeds=[pb_.seed for pb_ in pb],
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device=device,
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dtype=dtype,
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logit_bias=[dict([(tuple(tokenizer.encode(bias.string, add_special_tokens=False).input_ids[0]), bias.bias) for bias in pb_.logit_bias]) for pb_ in pb],
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logit_bias=[dict(
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[(tuple(tokenizer.encode(bias.string, add_special_tokens=False).input_ids[0]), bias.bias) for bias in
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pb_.logit_bias]) for pb_ in pb],
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)
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