入行深度学习会遇到各种bug ，希望我的这些经验对大家有用
1 tf torch 与 python gpu版本搭配的bug
2 加载各种预训练模型的bug
3 git上抄袭各种代码 linux转win的各种bug、
4 库不搭配的各种 bug
sentence_transformers 加载预训练模型
# pip install sentence_transformers==2.2.0 -i https://pypi.tuna.tsinghua.edu.cn/simple --trusted-host pypi.tuna.tsinghua.edu.cn
# transformers 4.17.0 sentence_transformers==2.2.0
# 用jupyter 就可以下载 用 pycharm就不行 transformers 4.17.0 sentence_transformers==2.2.0
# -*- coding: utf-8 -*-
import jieba
import re,random
import numpy as np
import pandas as pd
from datetime import datetime
import time
from tqdm import tqdm
import numpy as np
import time,random
from sentence_transformers import SentenceTransformer, InputExample
from sentence_transformers import models, losses
from torch.utils.data import DataLoader
from sentence_transformers import SentenceTransformer, util
from sentence_transformers import SentenceTransformer, SentencesDataset, InputExample, evaluation, losses, models
from torch.utils.data import DataLoader
# 加载预训练模型
model_name = 'cyclone/simcse-chinese-roberta-wwm-ext'
word_embedding_model = models.Transformer(model_name, max_seq_length=64)
pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension())
Dense=models.Dense(768,128)
model = SentenceTransformer(modules=[word_embedding_model, pooling_model,Dense])
# 查看一下模型架构是否一样，而这并没有什么区别，都是按照上面的模型图：bert+pooling组成
print("加载预训练模型:",model)
自动下载成功
tf torch 与 python gpu版本搭配的bug 版本对应
安装详细请看我的博客
cudnn :cuDNN Archive | NVIDIA Developer
查看cuda cudnn版本
# import tensorflow as tf
# hello = tf.constant('Hello, TensorFlow!')
# sess = tf.Session()
# print(sess.run(hello))
#Anaconda3 + Cuda10.0 + Cudnn7.4.1 + tensorflow-gpu==1.14.0(需要镜像网站pip下载或本地下载)
import torch
print(torch.__version__)
print(torch.version.cuda)
print(torch.backends.cudnn.version())
