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Sep 18, 2018
Merged

Notebook update #6

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19 changes: 19 additions & 0 deletions 01.getting-started/04.train-on-remote-vm/04.train-on-remote-vm.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -182,6 +182,25 @@
" dsvm_compute.wait_for_completion(show_output = True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Attach an existing Linux DSVM as a compute target\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
" '''\n",
" from azureml.core.compute import RemoteCompute \n",
" dsvm_compute = RemoteCompute.attach(ws,name=\"attach-from-sdk6\",username=<username>,address=<ipaddress>,ssh_port=22,password=<password>)\n",
"'''"
]
},
{
"cell_type": "markdown",
"metadata": {},
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24 changes: 0 additions & 24 deletions automl/00.configuration.ipynb
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Expand Up @@ -231,37 +231,13 @@
"print('Sample projects will be created in {}.'.format(sample_projects_folder))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Install additional packages for demo notebooks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install pandas_ml\n",
"!pip install seaborn"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Success!\n",
"Great, you are ready to move on to the rest of the sample notebooks."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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5 changes: 1 addition & 4 deletions automl/01.auto-ml-classification.ipynb
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Expand Up @@ -50,7 +50,6 @@
"from matplotlib.pyplot import imshow\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from sklearn import datasets\n",
"\n",
"import azureml.core\n",
Expand Down Expand Up @@ -268,9 +267,7 @@
" metricslist[int(properties['iteration'])] = metrics\n",
"\n",
"rundata = pd.DataFrame(metricslist).sort_index(1)\n",
"cm = sns.light_palette(\"lightgreen\", as_cmap = True)\n",
"s = rundata.style.background_gradient(cmap = cm)\n",
"s"
"rundata"
]
},
{
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7 changes: 1 addition & 6 deletions automl/02.auto-ml-regression.ipynb
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Expand Up @@ -50,7 +50,6 @@
"from matplotlib.pyplot import imshow\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from sklearn import datasets\n",
"\n",
"import azureml.core\n",
Expand Down Expand Up @@ -248,12 +247,8 @@
" metrics = {k: v for k, v in run.get_metrics().items() if isinstance(v, float)} \n",
" metricslist[int(properties['iteration'])] = metrics\n",
" \n",
"import pandas as pd\n",
"import seaborn as sns\n",
"rundata = pd.DataFrame(metricslist).sort_index(1)\n",
"cm = sns.light_palette(\"lightgreen\", as_cmap = True)\n",
"s = rundata.style.background_gradient(cmap = cm)\n",
"s"
"rundata"
]
},
{
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69 changes: 18 additions & 51 deletions automl/03.auto-ml-remote-execution.ipynb
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Expand Up @@ -58,7 +58,6 @@
"from matplotlib.pyplot import imshow\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from sklearn import datasets\n",
"\n",
"import azureml.core\n",
Expand Down Expand Up @@ -143,50 +142,6 @@
" dsvm_compute.wait_for_completion(show_output = True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a RunConfiguration with DSVM name\n",
"Run the below code to tell the runconfiguration the name of your dsvm."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from azureml.core.runconfig import RunConfiguration\n",
"\n",
"run_config = RunConfiguration()\n",
"run_config.target = dsvm_compute"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Change index to use master packages\n",
"If you want to use master rather than preview run the below code. Once Public preview is launched we would not need this cell."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from azureml.core.runconfig import CondaDependencies\n",
"\n",
"cd = CondaDependencies()\n",
"\n",
"cd.remove_pip_option(pip_option=\"--index-url https://azuremlsdktestpypi.azureedge.net/sdk-release/Preview/E7501C02541B433786111FE8E140CAA1\")\n",
"cd.set_pip_index_url(index_url=\"--extra-index-url https://azuremlsdktestpypi.azureedge.net/sdk-release/master/588E708E0DF342C4A80BD954289657CF\")\n",
"\n",
"run_config.environment.python.conda_dependencies = cd"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -263,20 +218,27 @@
"\n",
"automl_config = AutoMLConfig(task = 'classification',\n",
" debug_log = 'automl_errors.log',\n",
" path=project_folder,\n",
" run_configuration = run_config,\n",
" path=project_folder, \n",
" compute_target = dsvm_compute,\n",
" data_script = project_folder + \"./get_data.py\",\n",
" **automl_settings\n",
" )\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<b>Note</b> that the first run on a new DSVM may take a several minutes to preparing the environment."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"remote_run = experiment.submit(automl_config, show_output=True)"
"remote_run = experiment.submit(automl_config, show_output=False)"
]
},
{
Expand Down Expand Up @@ -352,9 +314,7 @@
" metricslist[int(properties['iteration'])] = metrics\n",
"\n",
"rundata = pd.DataFrame(metricslist).sort_index(1)\n",
"cm = sns.light_palette(\"lightgreen\", as_cmap = True)\n",
"s = rundata.style.background_gradient(cmap = cm)\n",
"s"
"rundata"
]
},
{
Expand Down Expand Up @@ -504,6 +464,13 @@
" plt.imshow(images[index], cmap=plt.cm.gray_r, interpolation='nearest')\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand Down
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