如何在 Azure 机器学习工作室的 jupyter notebook 中安装 TensorFlow
How to install TensorFlow in jupyter notebook on Azure Machine Learning Studio
我正在尝试测试 Azure 机器学习工作室。
我想使用 TensorFlow,但 Jupyter notebook 上没有安装它。
如何在笔记本上使用 TensorFlow、Theano、Keras 等机器学习库?
我试过这个:
!pip install tensorflow
但是,我得到如下错误:
Collecting tensorflow
Downloading tensorflow-0.12.0rc0-cp34-cp34m-manylinux1_x86_64.whl (43.1MB)
100% |################################| 43.1MB 27kB/s
Collecting protobuf==3.1.0 (from tensorflow)
Downloading protobuf-3.1.0-py2.py3-none-any.whl (339kB)
100% |################################| 348kB 3.7MB/s
Collecting six>=1.10.0 (from tensorflow)
Downloading six-1.10.0-py2.py3-none-any.whl
Requirement already satisfied: numpy>=1.11.0 in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages (from tensorflow)
Requirement already satisfied: wheel>=0.26 in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages (from tensorflow)
Requirement already satisfied: setuptools in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages/setuptools-27.2.0-py3.4.egg (from protobuf==3.1.0->tensorflow)
Installing collected packages: six, protobuf, tensorflow
Found existing installation: six 1.9.0
DEPRECATION: Uninstalling a distutils installed project (six) has been deprecated and will be removed in a future version. This is due to the fact that uninstalling a distutils project will only partially uninstall the project.
Uninstalling six-1.9.0:
Successfully uninstalled six-1.9.0
Rolling back uninstall of six
Exception:
Traceback (most recent call last):
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/basecommand.py", line 215, in main
status = self.run(options, args)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/commands/install.py", line 342, in run
prefix=options.prefix_path,
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_set.py", line 784, in install
**kwargs
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_install.py", line 851, in install
self.move_wheel_files(self.source_dir, root=root, prefix=prefix)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_install.py", line 1064, in move_wheel_files
isolated=self.isolated,
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/wheel.py", line 345, in move_wheel_files
clobber(source, lib_dir, True)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/wheel.py", line 329, in clobber
os.utime(destfile, (st.st_atime, st.st_mtime))
PermissionError: [Errno 1] Operation not permitted
如你所见,活动用户无权写入 Azure 机器学习工作室笔记本中的 site-packages
目录。您可以尝试将软件包安装到您具有写入权限的另一个目录(如默认工作目录)并从那里导入,但我建议使用以下 lower-hassle 选项。
Azure Notebooks is a separate Jupyter Notebook service that will allow you to install tensorflow, theano, and keras. Like the notebooks in AML Studio, these notebooks will persist in your account. The primary downside is that if you want to access your workspace through e.g. the Python azureml
package, you'll need to provide your workspace id/authorization token 建立连接。 (在 Azure ML Studio 中,这些值是从当前工作区自动加载的。)否则我相信 Azure Notebooks 可以做你习惯在 AML Studio 中做的所有事情。
我正在尝试测试 Azure 机器学习工作室。
我想使用 TensorFlow,但 Jupyter notebook 上没有安装它。
如何在笔记本上使用 TensorFlow、Theano、Keras 等机器学习库?
我试过这个:
!pip install tensorflow
但是,我得到如下错误:
Collecting tensorflow
Downloading tensorflow-0.12.0rc0-cp34-cp34m-manylinux1_x86_64.whl (43.1MB)
100% |################################| 43.1MB 27kB/s
Collecting protobuf==3.1.0 (from tensorflow)
Downloading protobuf-3.1.0-py2.py3-none-any.whl (339kB)
100% |################################| 348kB 3.7MB/s
Collecting six>=1.10.0 (from tensorflow)
Downloading six-1.10.0-py2.py3-none-any.whl
Requirement already satisfied: numpy>=1.11.0 in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages (from tensorflow)
Requirement already satisfied: wheel>=0.26 in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages (from tensorflow)
Requirement already satisfied: setuptools in /home/nbcommon/anaconda3_23/lib/python3.4/site-packages/setuptools-27.2.0-py3.4.egg (from protobuf==3.1.0->tensorflow)
Installing collected packages: six, protobuf, tensorflow
Found existing installation: six 1.9.0
DEPRECATION: Uninstalling a distutils installed project (six) has been deprecated and will be removed in a future version. This is due to the fact that uninstalling a distutils project will only partially uninstall the project.
Uninstalling six-1.9.0:
Successfully uninstalled six-1.9.0
Rolling back uninstall of six
Exception:
Traceback (most recent call last):
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/basecommand.py", line 215, in main
status = self.run(options, args)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/commands/install.py", line 342, in run
prefix=options.prefix_path,
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_set.py", line 784, in install
**kwargs
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_install.py", line 851, in install
self.move_wheel_files(self.source_dir, root=root, prefix=prefix)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/req/req_install.py", line 1064, in move_wheel_files
isolated=self.isolated,
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/wheel.py", line 345, in move_wheel_files
clobber(source, lib_dir, True)
File "/home/nbcommon/anaconda3_23/lib/python3.4/site-packages/pip/wheel.py", line 329, in clobber
os.utime(destfile, (st.st_atime, st.st_mtime))
PermissionError: [Errno 1] Operation not permitted
如你所见,活动用户无权写入 Azure 机器学习工作室笔记本中的 site-packages
目录。您可以尝试将软件包安装到您具有写入权限的另一个目录(如默认工作目录)并从那里导入,但我建议使用以下 lower-hassle 选项。
Azure Notebooks is a separate Jupyter Notebook service that will allow you to install tensorflow, theano, and keras. Like the notebooks in AML Studio, these notebooks will persist in your account. The primary downside is that if you want to access your workspace through e.g. the Python azureml
package, you'll need to provide your workspace id/authorization token 建立连接。 (在 Azure ML Studio 中,这些值是从当前工作区自动加载的。)否则我相信 Azure Notebooks 可以做你习惯在 AML Studio 中做的所有事情。