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from typing import Optional
from collections import deque
from queue import Queue
import copy
class History:
def __init__(self, tokenizer, history):
'''
init from a list of dict
'''
# use deque to meet some special situation
self.input_history = deque()
self.tokenizer = tokenizer
if history:
self._transfer_from_list(history)
def _transfer_from_list(self, history):
for message in history:
content = message.get("content")
message.update(self.tokenizer(content))
self.input_history.append(message)
def append(self, message):
content = message.get("content")
message.update(self.tokenizer(content))
self.input_history.append(message)
def append_left(self, message):
content = message.get("content")
message.update(self.tokenizer(content))
self.input_history.appendleft(message)
def pop(self):
x = self.input_history.pop()
return x
def pop_left(self):
x = self.pop_left()
return x
def update(self, content: str):
x = self.input_history.pop()
self.append({"role": x["role"], "content": content})
def __len__(self):
return self.input_history.__len__()
def __str__(self):
return self.input_history.__str__()
def __copy__(self):
new_instance = type(self)(self.tokenizer, [])
new_instance.input_history = copy.copy(self.input_history)
return new_instance
def __deepcopy__(self, memodict={}):
new_instance = type(self)(self.tokenizer, [])
new_instance.input_history = copy.deepcopy(self.input_history)
return new_instance
class TelechatIterTextStreamer:
"""
With reference to the TextIterStreamers in transformers, we have rewritten this class
"""
def __init__(
self, tokenizer, history: History = None, skip_prompt: bool = False, timeout: Optional[float] = None,
**decode_kwargs
):
self.tokenizer = tokenizer
self.history = history
self.skip_prompt = skip_prompt
self.timeout = timeout
self.decode_kwargs = decode_kwargs
self.text_queue = Queue()
self.token_cache = []
self.cache_time = 0
self.text_until = ""
self.stop_signal = None
self.next_tokens_are_prompt = True
self.history.append({"role": "bot", "content": self.text_until})
def put(self, value):
"""
put printable text into queue
"""
if len(value.shape) > 1 and value.shape[0] > 1:
raise ValueError("TextStreamer only supports batch size 1")
elif len(value.shape) > 1:
value = value[0]
if self.skip_prompt and self.next_tokens_are_prompt:
self.next_tokens_are_prompt = False
return
if value[-1] == self.tokenizer.eos_token_id:
return
# there may be some smart way to decode.
self.token_cache.extend(value.tolist())
text = self.tokenizer.decode(self.token_cache, **self.decode_kwargs)
self.cache_time += 1
if self._is_printable(text) or self.cache_time >= 6:
self.text_until += text
self.token_cache = []
self.cache_time = 0
else:
return
self.on_finalized_text(text)
def end(self):
"""Flushes any remaining cache and prints a newline to stdout."""
# Flush the cache, if it exists
text = ""
if len(self.token_cache) > 0:
text = self.tokenizer.decode(self.token_cache, **self.decode_kwargs)
self.text_until += text
self.on_finalized_text(text, stream_end=True)
self.clear_cache()
def clear_cache(self):
self.cache_time = 0
self.token_cache = []
self.text_until = ""
self.history = None
self.next_tokens_are_prompt = True
def on_finalized_text(self, text: str, stream_end: bool = False):
"""Put the text tuple in the queue."""
self.history.update(self.text_until)
self.text_queue.put((text, self.history), timeout=self.timeout)
if stream_end:
self.text_queue.put((self.stop_signal, self.history), timeout=self.timeout)
@staticmethod
def _is_printable(cp):
"""Checks whether tokens can be decoded or not"""
if "�" in cp:
return False
return True
def __iter__(self):
return self
def __next__(self):
value_now, history_until = self.text_queue.get(timeout=self.timeout)
if value_now == self.stop_signal:
raise StopIteration()
else:
return value_now, history_until
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