mirror of https://github.com/THUDM/ChatGLM-6B
Add improved stream output
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import os
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from transformers import AutoTokenizer, AutoModel
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import signal
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import platform
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from stream_utils import SPStreamDecoder
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tokenizer = AutoTokenizer.from_pretrained(
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"THUDM/chatglm-6b", trust_remote_code=True)
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stream_decoder = SPStreamDecoder(tokenizer.sp_tokenizer.text_tokenizer.sp)
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model = AutoModel.from_pretrained(
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"THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
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model = model.eval()
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os_name = platform.system()
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clear_command = 'cls' if os_name == 'Windows' else 'clear'
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stop_stream = False
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def signal_handler(signal, frame):
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global stop_stream
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stop_stream = True
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def main():
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history = []
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global stop_stream
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print("欢迎使用 ChatGLM-6B 模型,输入内容即可进行对话,clear 清空对话历史,stop 终止程序")
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while True:
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query = input("\n用户:")
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if query.strip() == "stop":
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break
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if query.strip() == "clear":
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history = []
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stream_decoder.end()
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stream_decoder.get()
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os.system(clear_command)
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print("欢迎使用 ChatGLM-6B 模型,输入内容即可进行对话,clear 清空对话历史,stop 终止程序")
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continue
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gen_kwargs = {"max_length": 2048, "do_sample": True, "top_p": 0.7,
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"temperature": 0.95, "logits_processor": None}
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if not history:
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prompt = query
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else:
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prompt = "".join([f"[Round {i}]\n问:{q}\n答:{r}\n" for i, (q, r) in enumerate(
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history)] + [f"[Round {len(history)}]\n问:{query}\n答:"])
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inputs = tokenizer([prompt], return_tensors="pt").to(model.device)
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print("\nChatGLM-6B:", end="")
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response = []
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for outputs in model.stream_generate(**inputs, **gen_kwargs):
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stream_decoder.put([int(outputs[0][-1])])
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new_resp = stream_decoder.get().replace("<n>", "\n")
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response.append(new_resp)
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print(new_resp, end="")
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# end of line
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stream_decoder.end()
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new_resp = stream_decoder.get().replace("<n>", "\n")
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response.append(new_resp)
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print(new_resp)
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response = "".join(response)
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history.append((query, response))
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if __name__ == "__main__":
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main()
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@ -0,0 +1,113 @@
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import sentencepiece as spm
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from typing import Tuple
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# python implantation of https://github.com/google/sentencepiece/blob/master/src/sentencepiece_processor.cc
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def DecodeSentencePiece(piece: str, id: int, is_bos_ws: bool, sp: spm.SentencePieceProcessor, add_dummy_prefix=True, remove_extra_whitespaces=False) -> Tuple[str, bool]:
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'''
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Returns decoded piece and a boolean indicating if the function has consumed
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a bos whitespace token (a piece starting with a kSpaceSymbol). This is used
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to strip only the first whitespace token from the decoded sequence for
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add_dummy_prefix.
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'''
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if sp.IsControl(id): # <s>, </s>
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return "", False # invisible symbol.
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elif sp.IsUnknown(id):
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if sp.IdToPiece(id) == piece: # <unk>
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return SPStreamDecoder.DefaultUnknownSymbol, False
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else: # return piece when piece is not <unk>.
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return piece, False
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has_bos_ws = False # whether the token starts with a kSpaceSymbol
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# Consume if the current position is bos and
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# piece starts with kSpaceSymbol.
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if is_bos_ws and (add_dummy_prefix or remove_extra_whitespaces):
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t = piece.removeprefix(SPStreamDecoder.SpaceSymbol)
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has_bos_ws = t != piece
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# if we are removing extra whitespace, we remove all leading whitespace
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if remove_extra_whitespaces:
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has_bos_ws = False
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return piece.replace(SPStreamDecoder.SpaceSymbol, " "), has_bos_ws
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def ProcessBytePieces(pieces: list[str]) -> str:
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'''
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Modified version of original code
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'''
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if len(pieces) == 0:
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return ""
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surfaces = ""
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# Constructs byte sequence.
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bytes_ = bytes([int(piece[1:-1], base=16) for piece in pieces])
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# Set surfaces of `bytes` for each Unicode character.
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while len(bytes_) > 0:
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try:
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surfaces += bytes_.decode('utf-8')
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break
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except UnicodeDecodeError as e:
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# The byte piece at `e.start` is structurally invalid. Map it to
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# REPLACEMENT CHARACTER (U+FFFD).
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surfaces += bytes_[:e.start].decode('utf-8')
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surfaces += SPStreamDecoder.ReplacementCharacter
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bytes_ = bytes_[e.end:]
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continue
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return surfaces
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class SPStreamDecoder:
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SpaceSymbol = chr(0x2581)
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DefaultUnknownSymbol = chr(0x2047)
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ReplacementCharacter = chr(0xFFFD)
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def __init__(self, sp: spm.SentencePieceProcessor, remove_extra_whitespaces=False, add_dummy_prefix=True) -> None:
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self._sp = sp
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self._bos_ws_seen = False
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# 'is_bos_ws': whether we expect a bos ws token to consume.
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self._is_bos_ws = True
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self._nothing_decoded = True
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self._ids = []
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self._decoded = ""
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self.remove_extra_whitespaces = remove_extra_whitespaces
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self.add_dummy_prefix = add_dummy_prefix
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def put(self, ids: list[int]) -> None:
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self._ids += ids
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self._decode(eos=False)
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def end(self) -> None:
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self._decode(eos=True)
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self._bos_ws_seen = False
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self._nothing_decoded = True
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self._ids = []
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def _decode(self, eos=False) -> None:
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pieces = [self._sp.IdToPiece(i) for i in self._ids]
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consumed = 0
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byte_pieces = []
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for i, piece in enumerate(pieces):
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if not self._sp.IsByte(self._ids[i]):
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self._decoded += ProcessBytePieces(byte_pieces)
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consumed += len(byte_pieces)
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if consumed > 0:
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self._nothing_decoded = False
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byte_pieces = []
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# if we have seen a bos_ws token or any non-empty token
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if self._bos_ws_seen or (not self._nothing_decoded):
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self._is_bos_ws = False
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decoded, self._bos_ws_seen = DecodeSentencePiece(
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piece, self._ids[i], self._is_bos_ws, self._sp)
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self._decoded += decoded
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consumed += 1
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if consumed > 0:
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self._nothing_decoded = False
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else:
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byte_pieces.append(piece)
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if eos:
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self._decoded += ProcessBytePieces(byte_pieces)
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else:
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self._ids = self._ids[consumed:]
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def get(self) -> str:
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t = self._decoded
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self._decoded = ""
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return t
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