# 加载数据 import torch from joblib import dump, load import torch.utils.data as Data import numpy as np import pandas as pd import torch import torch.nn as nn # 参数与配置 torch.manual_seed(100) # 设置随机种子,以使实验结果具有可重复性 device = torch.device("cuda" if torch.cuda.is_...
# 需要导入模块: import pydotplus [as 别名]# 或者: from pydotplus importgraph_from_dot_data[as 别名]deftest_attribute_with_implicit_value(self):d ='digraph {\na -> b[label="hi", decorate];\n}'g = pydotplus.graph_from_dot_data(d) attrs = g.get_edges()[0].get_attributes() self....
正确导入joblib 安装完成后,你可以在你的Python代码中直接导入joblib,而不是尝试从sklearn.externals导入。例如: python import joblib # 现在你可以使用joblib提供的功能了 # 例如,保存一个模型 model = ... # 你的模型 joblib.dump(model, 'model.pkl') # 或者加载一个模型 loaded_model = joblib.load('mod...
ImportError: cannot import name ‘joblib‘ from ‘sklearn.externals,程序员大本营,技术文章内容聚合第一站。
1.载入模块 1from sklearn.externalsimportjoblib 2.保存模型 1joblib.dump(model,'filename.pkl') 3.加载模型 1model = joblib.load('filename.pkl') 4.例子 1# -*- coding: utf-8 -*-2"""3# 作者:wanglei52054# 邮箱:wanglei5205@126.com5# 博客:http://cnblogs.com/wanglei52056# github:http...
ubuntu/.local/lib/python3.5/site-packages/joblib/parallel.py", line 208, in __init__ self.pickled_obj = dumps(obj) File "/home/ubuntu/.local/lib/python3.5/site-packages/joblib/externals/cloudpickle/cloudpickle.py", line 917, in dumps cp.dump(obj) File "/home/ubuntu/.local/lib/python...
2019-12-18 15:40 −sklearn 中模型保存的两种方法 一、 sklearn中提供了高效的模型持久化模块joblib,将模型保存至硬盘。 from sklearn.externals import joblib #lr是一个LogisticRegression模型 joblib.dump(lr, ... junneyang 0 3563 vue中的import {} from '@/api/api' ...
anyconfig Library provides common APIs to load and dump configuration files in various formats 15 pyportfolioopt Financial portfolio optimization in python 15 paddleocr Awesome OCR toolkits based on PaddlePaddle (8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobil...
一些常见的全局数据有：程序设定类、数据库连接类、用户资料等等。有很多方法能够使这些数据成为全局数据，...
tree import DecisionTreeClassifier >>> import numpy as np >>> import joblib >>> clf = DecisionTreeClassifier().fit(np.random.randn(100, 10), np.random.randint(0, 2, 100)) >>> joblib.dump(clf, "clf.joblib") ['clf.joblib'] >>> joblib.load("clf.joblib", mmap_mode="r") Trace...