mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-23 00:18:20 +01:00
103 lines
2.8 KiB
Python
103 lines
2.8 KiB
Python
import gc
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import traceback
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from queue import Queue
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from threading import Thread
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import torch
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import transformers
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import modules.shared as shared
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# Copied from https://github.com/PygmalionAI/gradio-ui/
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class _SentinelTokenStoppingCriteria(transformers.StoppingCriteria):
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def __init__(self, sentinel_token_ids: list, starting_idx: int):
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transformers.StoppingCriteria.__init__(self)
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self.sentinel_token_ids = sentinel_token_ids
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self.starting_idx = starting_idx
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def __call__(self, input_ids: torch.LongTensor, _scores: torch.FloatTensor) -> bool:
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for sample in input_ids:
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trimmed_sample = sample[self.starting_idx:]
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for i in range(len(self.sentinel_token_ids)):
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# Can't unfold, output is still too tiny. Skip.
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if trimmed_sample.shape[-1] < self.sentinel_token_ids[i].shape[-1]:
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continue
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for window in trimmed_sample.unfold(0, self.sentinel_token_ids[i].shape[-1], 1):
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if torch.all(torch.eq(self.sentinel_token_ids[i][0], window)):
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return True
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return False
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class Stream(transformers.StoppingCriteria):
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def __init__(self, callback_func=None):
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self.callback_func = callback_func
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def __call__(self, input_ids, scores) -> bool:
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if self.callback_func is not None:
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self.callback_func(input_ids[0])
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return False
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class Iteratorize:
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"""
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Transforms a function that takes a callback
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into a lazy iterator (generator).
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"""
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def __init__(self, func, kwargs={}, callback=None):
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self.mfunc=func
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self.c_callback=callback
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self.q = Queue()
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self.sentinel = object()
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self.kwargs = kwargs
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self.stop_now = False
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def _callback(val):
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if self.stop_now or shared.stop_everything:
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raise ValueError
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self.q.put(val)
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def gentask():
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try:
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ret = self.mfunc(callback=_callback, **self.kwargs)
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except ValueError:
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pass
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except:
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traceback.print_exc()
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pass
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clear_torch_cache()
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self.q.put(self.sentinel)
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if self.c_callback:
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self.c_callback(ret)
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self.thread = Thread(target=gentask)
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self.thread.start()
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def __iter__(self):
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return self
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def __next__(self):
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obj = self.q.get(True,None)
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if obj is self.sentinel:
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raise StopIteration
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else:
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return obj
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def __del__(self):
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clear_torch_cache()
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc_val, exc_tb):
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self.stop_now = True
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clear_torch_cache()
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def clear_torch_cache():
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gc.collect()
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if not shared.args.cpu:
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torch.cuda.empty_cache()
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