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"# Issue: `az -h` check fails\n",
"\n",
"When you see the `az -h` check fail as shown in below screenshot, it indicates that the environment where the Jupyter server is lanched does not have `az` installed. \n",
"\n",
"![azcheckfail2](../imgs/azcheckfail2.PNG)\n",
"\n",
"# Resolution: Launch Jupyter server manually\n",
"\n",
"In the console, execute `jupyter sever`. You should see the output similar to below screenshot. You can then access your notebooks at `https://<vm_ip>:<port_number>` or `http://<vm_ip>:<port_number>`, depending on the backend settings. Use the address indicated in the command ouput. \n",
"![jupyterserver](../imgs/jupyterserver.PNG)\n",
"\n",
"If it shows `http(s)://localhost:<port_number>` in the output, use `Ctrl+C` to shut down the server. Try again using command `jupyter notebook --ip=*` or `jupyter notebook --no-browser --ip=*`\n",
"\n",
"\n",
"The bottom line is that, you need to launch Jupyter server manually. Sometimes you may need to modify the configuration file `/home/<your_user_name>/.jupyter/jupyter_notebook_config.py`. Below information are for your reference. \n",
"- [Access Jupyter notebooks on Azure DSVM](http://yiyujia.blogspot.com/2018/05/access-jupyter-notebooks-on-azure-dsvm.html)\n",
"- [How to change the Jupyter start-up folder](https://stackoverflow.com/questions/35254852/how-to-change-the-jupyter-start-up-folder)\n",
"- [Config file and command line options](http://jupyter-notebook.readthedocs.io/en/stable/config.html)\n",
"\n"
]
},
{
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"source": [
"# Issue: `az ml -h` check fails\n",
"When you see the `az ml -h` fail as shown in below screenshot, it indicates that the same check will fail in the console as well.\n",
"\n",
"![azcheckfailnotebook](../imgs/azcheckfailnotebook.PNG)\n",
"![azcheckfail](../imgs/azcheckfail.PNG)\n",
"\n",
"\n",
"# Resolution: Create a New Conda Environment\n",
"\n",
"1. In console, locate file `/DeepLearningModelDeployment/common/cli-requirements.txt` in this repository. Navigate to the same directory where `cli-requirements.txt` is.\n",
"2. Execute below commands in console:\n",
"\n",
" conda create --name az_ml_test python=3.5\n",
" activate az_ml_test\n",
" pip install -r cli-requirements.txt\n",
" pip install azure-cli-ml\n",
"\n",
"Now you should see below screenshot when execute command `conda info --env`. You can see that a new conda environment `az_ml_test` is created. \n",
"\n",
"![condaenv1](../imgs/condaenv1.PNG)\n",
"\n",
"Exectue command `source activate az_ml_test` to make it current active environment (see the `*` is besides it).\n",
" ![condaenv2](../imgs/condaenv2.PNG)\n",
" \n",
" \n",
"Exectue `az ml -h` again, and you should see following screenshot indicating the check is successful.\n",
"\n",
"\n",
"![azcheckinconsole](../imgs/azcheckinconsole.PNG)\n",
"\n",
"\n",
"Now you can manully lanch Jupyter server as shown by the previous section. In the notebooks, you should also see `az ml -h` check successful. As a side note, the check output shown in below screenshot is correct.\n",
"\n",
"![whichaz2](../imgs/whichaz2.PNG) \n",
"\n",
"THe check output shown in below screenshot is incorrect. \n",
"![whichaz1](../imgs/whichaz1.PNG)\n",
"\n"
]
}
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