File size: 5,111 Bytes
f072939 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 |
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")
# the token result may not be equal to the result model gen
message.update(self.tokenizer(content))
self.input_history.append(message)
def append(self, message):
content = message.get("content")
if "input_ids" not in message or "attention_mask" not in message:
message.update(self.tokenizer(content))
self.input_history.append(message)
def append_left(self, message):
content = message.get("content")
if "input_ids" not in message or "attention_mask" not in message:
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, message):
self.input_history.pop()
self.append(message)
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.cache_time = 0
self.text_until = ""
self.token_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_until.extend(value.tolist())
text = self.tokenizer.decode(self.token_until, **self.decode_kwargs)
if self._is_printable(text) or self.cache_time >= 6:
output_text = text[len(self.text_until):]
self.text_until = text
else:
self.cache_time+=1
return
self.on_finalized_text(output_text)
def end(self):
"""Flushes any remaining cache and prints a newline to stdout."""
# Flush the cache, if it exists
text = self.tokenizer.decode(self.token_until, **self.decode_kwargs)
output_text = text[len(self.text_until):]
self.text_until = text
self.on_finalized_text(output_text, stream_end=True)
self.clear_cache()
def clear_cache(self):
self.cache_time = 0
self.token_until = []
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({"role": "bot", "content": self.text_until, "input_ids": self.token_until,
"attention_mask": [1] * len(self.token_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
|