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Merge pull request #1884 from Azure/release_update_stablev2/Release-166
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update samples from Release-166 as a part of 1.49.0 SDK stable release
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harneetvirk authored Feb 14, 2023
2 parents 9b1e130 + 0ecbbbc commit 40b3068
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2 changes: 1 addition & 1 deletion configuration.ipynb
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"source": [
"import azureml.core\n",
"\n",
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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3 changes: 2 additions & 1 deletion contrib/fairness/fairlearn-azureml-mitigation.yml
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Expand Up @@ -6,7 +6,8 @@ dependencies:
- fairlearn>=0.6.2
- joblib
- liac-arff
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- itsdangerous==2.0.1
- markupsafe<2.1.0
- protobuf==3.20.0
- numpy<1.24.0
3 changes: 2 additions & 1 deletion contrib/fairness/upload-fairness-dashboard.yml
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Expand Up @@ -6,7 +6,8 @@ dependencies:
- fairlearn>=0.6.2
- joblib
- liac-arff
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- itsdangerous==2.0.1
- markupsafe<2.1.0
- protobuf==3.20.0
- numpy<1.24.0
14 changes: 9 additions & 5 deletions how-to-use-azureml/automated-machine-learning/automl_env.yml
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Expand Up @@ -8,13 +8,17 @@ dependencies:
# Azure ML only supports 3.7.0 and later.
- pip==22.3.1
- python>=3.7,<3.9
- conda-forge::fbprophet==0.7.1
- pandas==1.1.5
- scipy==1.5.3
- Cython==0.29.14

- pip:
# Required packages for AzureML execution, history, and data preparation.
- azureml-widgets~=1.48.0
- azureml-defaults~=1.48.0
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.48.0/validated_win32_requirements.txt [--no-deps]
- azureml-widgets~=1.49.0
- azureml-defaults~=1.49.0
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.49.0/validated_win32_requirements.txt [--no-deps]
- matplotlib==3.6.2
- xgboost==1.3.3
- arch==4.14
- mlflow-skinny==1.30.0
- cmdstanpy==0.9.5
- setuptools-git==1.2
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Expand Up @@ -6,7 +6,7 @@ channels:
dependencies:
# The python interpreter version.
# Azure ML only supports 3.7 and later.
- pip==20.1.1
- pip==22.3.1
- python>=3.7,<3.9
- matplotlib==3.2.1
- numpy>=1.21.6,<=1.22.3
Expand All @@ -20,16 +20,13 @@ dependencies:
- pytorch::pytorch=1.11.0
- cudatoolkit=10.1.243
- notebook
- jinja2<=2.11.2
- markupsafe<2.1.0

- pip:
# Required packages for AzureML execution, history, and data preparation.
- azureml-widgets~=1.48.0
- azureml-defaults~=1.48.0
- azureml-widgets~=1.49.0
- azureml-defaults~=1.49.0
- pytorch-transformers==1.0.0
- spacy==2.2.4
- pystan==2.19.1.1
- https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.48.0/validated_linux_requirements.txt [--no-deps]
- arch==4.14
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.49.0/validated_linux_requirements.txt [--no-deps]
11 changes: 4 additions & 7 deletions how-to-use-azureml/automated-machine-learning/automl_env_mac.yml
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Expand Up @@ -6,7 +6,7 @@ channels:
dependencies:
# The python interpreter version.
# Currently Azure ML only supports 3.7 and later.
- pip==20.1.1
- pip==22.3.1
- python>=3.7,<3.9
- matplotlib==3.2.1
- numpy>=1.21.6,<=1.22.3
Expand All @@ -20,16 +20,13 @@ dependencies:
- pytorch::pytorch=1.11.0
- cudatoolkit=9.0
- notebook
- jinja2<=2.11.2
- markupsafe<2.1.0

- pip:
# Required packages for AzureML execution, history, and data preparation.
- azureml-widgets~=1.48.0
- azureml-defaults~=1.48.0
- azureml-widgets~=1.49.0
- azureml-defaults~=1.49.0
- pytorch-transformers==1.0.0
- spacy==2.2.4
- pystan==2.19.1.1
- https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.48.0/validated_darwin_requirements.txt [--no-deps]
- arch==4.14
- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.49.0/validated_darwin_requirements.txt [--no-deps]
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Expand Up @@ -97,7 +97,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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Expand Up @@ -97,7 +97,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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Expand Up @@ -3,7 +3,7 @@ dependencies:
# The python interpreter version.
# Currently Azure ML only supports 3.7.0 and later.
- pip<=22.3.1
- python>=3.7.0,<3.10
- python>=3.7.0,<3.11

- pip:
# Required packages for AzureML execution, history, and data preparation.
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Expand Up @@ -4,10 +4,10 @@ channels:
- main
dependencies:
# The python interpreter version.
# Currently Azure ML only supports 3.6.0 and later.
# Currently Azure ML only supports 3.7.0 and later.
- pip<=20.2.4
- nomkl
- python>=3.6.0,<3.10
- python>=3.7.0,<3.11
- urllib3==1.26.7
- PyJWT < 2.0.0
- numpy>=1.21.6,<=1.22.3
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Expand Up @@ -92,7 +92,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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Expand Up @@ -91,7 +91,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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Expand Up @@ -106,7 +106,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(\"This notebook was created using version 1.48.0 of the Azure ML SDK\")\n",
"print(\"This notebook was created using version 1.49.0 of the Azure ML SDK\")\n",
"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
]
},
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"pip uninstall -y xgboost && \\\n",
"conda install py-xgboost==1.3.3 && \\\n",
"pip uninstall -y numpy && \\\n",
"pip install {numpy_dep} &&\\\n",
"pip install {sklearn_dep} \\\n",
"pip install {numpy_dep} && \\\n",
"pip install {sklearn_dep} && \\\n",
"pip install chardet \\\n",
"\"\"\"\n",
"\n",
"env.python.user_managed_dependencies = True\n",
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Expand Up @@ -10,7 +10,7 @@ dependencies:
- ipython
- matplotlib
- ipywidgets
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- itsdangerous==2.0.1
- markupsafe<2.1.0
- scipy>=1.5.3
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Expand Up @@ -10,7 +10,7 @@ dependencies:
- matplotlib
- azureml-dataset-runtime
- ipywidgets
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- itsdangerous==2.0.1
- markupsafe<2.1.0
- scipy>=1.5.3
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Expand Up @@ -9,7 +9,7 @@ dependencies:
- ipython
- matplotlib
- ipywidgets
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- packaging>=20.9
- itsdangerous==2.0.1
- markupsafe<2.1.0
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Expand Up @@ -9,7 +9,7 @@ dependencies:
- ipython
- matplotlib
- ipywidgets
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- packaging>=20.9
- itsdangerous==2.0.1
- markupsafe<2.1.0
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Expand Up @@ -11,7 +11,7 @@ dependencies:
- azureml-dataset-runtime
- azureml-core
- ipywidgets
- raiwidgets~=0.23.0
- raiwidgets~=0.24.0
- itsdangerous==2.0.1
- markupsafe<2.1.0
- scipy>=1.5.3
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Expand Up @@ -330,7 +330,7 @@
"- **inputs:** List of input connections for data consumed by this step. Fetch this inside the notebook using dbutils.widgets.get(\"input\")\n",
"- **outputs:** List of output port definitions for outputs produced by this step. Fetch this inside the notebook using dbutils.widgets.get(\"output\")\n",
"- **existing_cluster_id:** Cluster ID of an existing Interactive cluster on the Databricks workspace. If you are providing this, do not provide any of the parameters below that are used to create a new cluster such as spark_version, node_type, etc.\n",
"- **spark_version:** Version of spark for the databricks run cluster. You can refer to [DataBricks runtime version](https://learn.microsoft.com/azure/databricks/dev-tools/api/#--runtime-version-strings) to specify the spark version. default value: 4.0.x-scala2.11\n",
"- **spark_version:** Version of spark for the databricks run cluster. You can refer to [DataBricks runtime version](https://learn.microsoft.com/azure/databricks/dev-tools/api/#--runtime-version-strings) to specify the spark version. default value: 10.4.x-scala2.12\n",
"- **node_type:** Azure vm node types for the databricks run cluster. default value: Standard_D3_v2\n",
"- **num_workers:** Specifies a static number of workers for the databricks run cluster\n",
"- **min_workers:** Specifies a min number of workers to use for auto-scaling the databricks run cluster\n",
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Expand Up @@ -86,7 +86,7 @@
"import requests\n",
"\n",
"oj_sales_path = \"./oj.csv\"\n",
"r = requests.get(\"http://www.cs.unitn.it/~taufer/Data/oj.csv\")\n",
"r = requests.get(\"https://raw.githubusercontent.com/Azure/azureml-examples/main/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales/data/dominicks_OJ.csv\")\n",
"open(oj_sales_path, \"wb\").write(r.content)"
]
},
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"metadata": {},
"outputs": [],
"source": [
"partitioned_dataset = dataset.partition_by(partition_keys=['store', 'brand'], target=(datastore, \"partition_by_key_res\"), name=\"partitioned_oj_data\")\n",
"partitioned_dataset = dataset.partition_by(partition_keys=['Store', 'Brand'], target=(datastore, \"partition_by_key_res\"), name=\"partitioned_oj_data\")\n",
"partitioned_dataset.partition_keys"
]
},
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"parallel_run_config = ParallelRunConfig(\n",
" source_directory=scripts_folder,\n",
" entry_script=script_file, # the user script to run against each input\n",
" partition_keys=['store', 'brand'],\n",
" partition_keys=['Store', 'Brand'],\n",
" error_threshold=5,\n",
" output_action='append_row',\n",
" append_row_file_name=\"revenue_outputs.txt\",\n",
Expand Down Expand Up @@ -362,8 +362,8 @@
"result_file = os.path.join(target_dir, batch_output.path_on_datastore, parallel_run_config.append_row_file_name)\n",
"\n",
"df = pd.read_csv(result_file, delimiter=\" \", header=None)\n",
"df.columns=[\"WeekStarting\", \"Quantity\", \"logQuantity\", \"Advert\", \"Price\", \"Age60\", \"COLLEGE\", \"INCOME\", \"Hincome150\", \"Large HH\", \"Minorities\", \"WorkingWoman\", \"SSTRDIST\", \"SSTRVOL\", \"CPDIST5\", \"CPWVOL5\", \"Store\", \"Brand\", \"total_income\"]\n",
"\n",
"df.columns = [\"week\", \"logmove\", \"feat\", \"price\", \"AGE60\", \"EDUC\", \"ETHNIC\", \"INCOME\", \"HHLARGE\", \"WORKWOM\", \"HVAL150\", \"SSTRDIST\", \"SSTRVOL\", \"CPDIST5\", \"CPWVOL5\", \"store\", \"brand\", \"total_income\"]\n",
"print(\"Prediction has \", df.shape[0], \" rows\")\n",
"df.head(10)"
]
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
"version": "3.8.13"
}
},
"nbformat": 4,
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2 changes: 0 additions & 2 deletions how-to-use-azureml/reinforcement-learning/README.md
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Expand Up @@ -36,8 +36,6 @@ Using these samples, you will learn how to do the following.
| [cartpole_ci.ipynb](cartpole-on-compute-instance/cartpole_ci.ipynb) | Notebook to train a Cartpole playing agent on an Azure Machine Learning Compute Instance |
| [cartpole_sc.ipynb](cartpole-on-single-compute/cartpole_sc.ipynb) | Notebook to train a Cartpole playing agent on an Azure Machine Learning Compute Cluster (single node) |
| [pong_rllib.ipynb](atari-on-distributed-compute/pong_rllib.ipynb) | Notebook for distributed training of Pong agent using RLlib on multiple compute targets |
| [minecraft.ipynb](minecraft-on-distributed-compute/minecraft.ipynb) | Notebook to train an agent to navigate through a lava maze in the Minecraft game |
| [particle.ipynb](multiagent-particle-envs/particle.ipynb) | Notebook to train policies in a multiagent cooperative navigation scenario based on OpenAI's Particle environments |

## Prerequisites

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