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from transformers import AutoTokenizer, PreTrainedTokenizerFast
from transformers.tokenization_utils_base import AddedToken
from http.server import HTTPServer, BaseHTTPRequestHandler
import json
import argparse
def _prompt_split_image(
image_seq_len,
image_rows,
image_cols,
fake_token_around_image,
image_token,
global_img_token,
):
"""Prompt with expanded image tokens for when the image is split into patches."""
text_split_images = ""
for n_h in range(image_rows):
for n_w in range(image_cols):
text_split_images += (
f"{fake_token_around_image}"
+ f"<row_{n_h + 1}_col_{n_w + 1}>"
+ f"{image_token}" * image_seq_len
)
text_split_images += "\n"
text_split_images += (
f"\n{fake_token_around_image}"
+ f"{global_img_token}"
+ f"{image_token}" * image_seq_len
+ f"{fake_token_around_image}"
)
return text_split_images
def _prompt_single_image(
image_seq_len, fake_token_around_image, image_token, global_img_token
):
"""Prompt with expanded image tokens for a single image."""
return (
f"{fake_token_around_image}"
+ f"{global_img_token}"
+ f"{image_token}" * image_seq_len
+ f"{fake_token_around_image}"
)
def get_image_prompt_string(
image_rows,
image_cols,
image_seq_len,
fake_token_around_image,
image_token,
global_img_token,
):
if image_rows == 0 and image_cols == 0:
return _prompt_single_image(
image_seq_len,
fake_token_around_image=fake_token_around_image,
image_token=image_token,
global_img_token=global_img_token,
)
return _prompt_split_image(
image_seq_len,
image_rows,
image_cols,
fake_token_around_image,
image_token,
global_img_token,
)
class Tokenizer_Http():
def __init__(self):
path = 'smolvlm_tokenizer'
self.tokenizer = AutoTokenizer.from_pretrained(path,
trust_remote_code=True,
use_fast=False)
def encode(self, content):
prompt = f"<|im_start|>User:{content}<end_of_utterance>\nAssistant:"
input_ids = self.tokenizer(prompt)
return input_ids["input_ids"]
def encode_vpm(self, content="Can you describe this image?"):
prompt = f"<|im_start|>User:<image>{content}<end_of_utterance>\nAssistant:"
text = [prompt]
image_rows = [[0]]
image_cols = [[0]]
image_seq_len = 64
image_token = "<image>"
fake_image_token = "<fake_token_around_image>"
global_img_token = "<global-img>"
prompt_strings = []
for sample, sample_rows, sample_cols in zip(text, image_rows, image_cols):
# Replace the image token with fake tokens around the expanded image token sequence of length `image_seq_len`
image_prompt_strings = []
for n_rows, n_cols in zip(sample_rows, sample_cols):
image_prompt_string = get_image_prompt_string(
n_rows,
n_cols,
image_seq_len,
image_token=image_token,
fake_token_around_image=fake_image_token,
global_img_token=global_img_token,
)
image_prompt_strings.append(image_prompt_string)
split_sample = sample.split(image_token)
if len(split_sample) == 0:
raise ValueError("The image token should be present in the text.")
# Place in the image prompt strings where the image tokens are
sample = split_sample[0]
for i, image_prompt_string in enumerate(image_prompt_strings):
sample += image_prompt_string + split_sample[i + 1]
prompt_strings.append(sample)
fake_image_token = AddedToken(fake_image_token, normalized=False, special=True)
image_token = AddedToken(image_token, normalized=False, special=True)
end_of_utterance_token = AddedToken(
"<end_of_utterance>", normalized=False, special=True
)
tokens_to_add = {
"additional_special_tokens": [
fake_image_token,
image_token,
end_of_utterance_token,
]
}
self.tokenizer.add_special_tokens(tokens_to_add)
input_ids = self.tokenizer(prompt_strings)["input_ids"][0]
return input_ids
def decode(self, token_ids):
return self.tokenizer.decode(token_ids,
clean_up_tokenization_spaces=False)
@property
def bos_id(self):
return self.tokenizer.bos_token_id
@property
def eos_id(self):
return self.tokenizer.eos_token_id
@property
def bos_token(self):
return self.tokenizer.bos_token
@property
def eos_token(self):
return self.tokenizer.eos_token
tokenizer = Tokenizer_Http()
print(tokenizer.bos_id, tokenizer.bos_token, tokenizer.eos_id,
tokenizer.eos_token)
token_ids = tokenizer.encode_vpm()
# [151644, 8948, 198, 56568, 104625, 100633, 104455, 104800, 101101, 32022, 102022, 99602, 100013, 9370, 90286, 21287, 42140, 53772, 35243, 26288, 104949, 3837, 105205, 109641, 67916, 30698, 11, 54851, 46944, 115404, 42192, 99441, 100623, 48692, 100168, 110498, 1773, 151645, 151644, 872, 198,
# 151646,
# 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648, 151648,
# 151647,
# 198, 5501, 7512, 279, 2168, 19620, 13, 151645, 151644, 77091, 198]
# 118
print(token_ids)
print(len(token_ids))
token_ids = tokenizer.encode("hello world")
# [151644, 8948, 198, 56568, 104625, 100633, 104455, 104800, 101101, 32022, 102022, 99602, 100013, 9370, 90286, 21287, 42140, 53772, 35243, 26288, 104949, 3837, 105205, 109641, 67916, 30698, 11, 54851, 46944, 115404, 42192, 99441, 100623, 48692, 100168, 110498, 1773, 151645, 151644, 872, 198, 14990, 1879, 151645, 151644, 77091, 198]
# 47
print(token_ids)
print(len(token_ids))
class Request(BaseHTTPRequestHandler):
#通过类继承，新定义类
timeout = 5
server_version = 'Apache'
def do_GET(self):
print(self.path)
#在新类中定义get的内容（当客户端向该服务端使用get请求时，本服务端将如下运行）
self.send_response(200)
self.send_header("type", "get") #设置响应头，可省略或设置多个
self.end_headers()
if self.path == '/bos_id':
bos_id = tokenizer.bos_id
# print(bos_id)
# to json
if bos_id is None:
msg = json.dumps({'bos_id': -1})
else:
msg = json.dumps({'bos_id': bos_id})
elif self.path == '/eos_id':
eos_id = tokenizer.eos_id
if eos_id is None:
msg = json.dumps({'eos_id': -1})
else:
msg = json.dumps({'eos_id': eos_id})
else:
msg = 'error'
print(msg)
msg = str(msg).encode() #转为str再转为byte格式
self.wfile.write(msg) #将byte格式的信息返回给客户端
def do_POST(self):
#在新类中定义post的内容（当客户端向该服务端使用post请求时，本服务端将如下运行）
data = self.rfile.read(int(
self.headers['content-length'])) #获取从客户端传入的参数（byte格式）
data = data.decode() #将byte格式转为str格式
self.send_response(200)
self.send_header("type", "post") #设置响应头，可省略或设置多个
self.end_headers()
if self.path == '/encode':
req = json.loads(data)
print(req)
prompt = req['text']
b_img_prompt = False
if 'img_prompt' in req:
b_img_prompt = req['img_prompt']
if b_img_prompt:
token_ids = tokenizer.encode_vpm(prompt)
else:
token_ids = tokenizer.encode(prompt)
if token_ids is None:
msg = json.dumps({'token_ids': -1})
else:
msg = json.dumps({'token_ids': token_ids})
elif self.path == '/decode':
req = json.loads(data)
token_ids = req['token_ids']
text = tokenizer.decode(token_ids)
if text is None:
msg = json.dumps({'text': ""})
else:
msg = json.dumps({'text': text})
else:
msg = 'error'
print(msg)
msg = str(msg).encode() #转为str再转为byte格式
self.wfile.write(msg) #将byte格式的信息返回给客户端
if __name__ == "__main__":
args = argparse.ArgumentParser()
args.add_argument('--host', type=str, default='localhost')
args.add_argument('--port', type=int, default=8080)
args = args.parse_args()
host = (args.host, args.port) #设定地址与端口号，'localhost'等价于'127.0.0.1'
print('http://%s:%s' % host)
server = HTTPServer(host, Request) #根据地址端口号和新定义的类，创建服务器实例
server.serve_forever() #开启服务
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