mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-30 11:28:58 +01:00
104 lines
2.5 KiB
Python
104 lines
2.5 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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from transformers import is_torch_xpu_available
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import modules.shared as shared
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class StopNowException(Exception):
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pass
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class _StopEverythingStoppingCriteria(transformers.StoppingCriteria):
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def __init__(self):
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transformers.StoppingCriteria.__init__(self)
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def __call__(self, input_ids: torch.LongTensor, _scores: torch.FloatTensor) -> bool:
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return shared.stop_everything
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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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Adapted from: https://stackoverflow.com/a/9969000
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"""
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def __init__(self, func, args=None, kwargs=None, 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.args = args or []
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self.kwargs = kwargs or {}
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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 StopNowException
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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, *args, **self.kwargs)
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except StopNowException:
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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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if is_torch_xpu_available():
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torch.xpu.empty_cache()
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else:
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torch.cuda.empty_cache()
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