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Merge pull request #1972 from Azure/release_update_stablev2/Release-243
update samples from Release-243 as a part of 1.58.0 SDK stable release
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configuration.ipynb

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"source": [
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"import azureml.core\n",
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"\n",
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"print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
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"print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
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"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
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]
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},

how-to-use-azureml/automated-machine-learning/automl_env.yml

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- pip:
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# Required packages for AzureML execution, history, and data preparation.
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- azureml-widgets~=1.57.0
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- azureml-defaults~=1.57.0
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_win32_requirements.txt [--no-deps]
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- azureml-widgets~=1.58.0
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- azureml-defaults~=1.58.0
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_win32_requirements.txt [--no-deps]
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- matplotlib==3.7.1
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- xgboost==1.5.2
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- prophet==1.1.4
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- pandas==1.3.5
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- cmdstanpy==1.1.0
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- setuptools-git==1.2
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- spacy==3.7.4
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- https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz

how-to-use-azureml/automated-machine-learning/automl_env_linux.yml

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- pip:
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# Required packages for AzureML execution, history, and data preparation.
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- azureml-widgets~=1.57.0
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- azureml-defaults~=1.57.0
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- azureml-widgets~=1.58.0
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- azureml-defaults~=1.58.0
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- pytorch-transformers==1.0.0
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- spacy==3.7.4
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- xgboost==1.5.2
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- prophet==1.1.4
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- https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_linux_requirements.txt [--no-deps]
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_linux_requirements.txt [--no-deps]

how-to-use-azureml/automated-machine-learning/automl_env_mac.yml

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- pip:
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# Required packages for AzureML execution, history, and data preparation.
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- azureml-widgets~=1.57.0
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- azureml-defaults~=1.57.0
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- azureml-widgets~=1.58.0
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- azureml-defaults~=1.58.0
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- pytorch-transformers==1.0.0
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- prophet==1.1.4
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- xgboost==1.5.2
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- spacy==3.7.4
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- matplotlib==3.7.1
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- https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_darwin_requirements.txt [--no-deps]
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- -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_darwin_requirements.txt [--no-deps]

how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb

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"from azureml.core.workspace import Workspace\n",
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"from azureml.core.dataset import Dataset\n",
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"from azureml.train.automl import AutoMLConfig\n",
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"from azureml.interpret import ExplanationClient"
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"from azureml.interpret import ExplanationClient\n",
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"from azureml.data.datapath import DataPath"
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]
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},
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{
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"pd.DataFrame(data).to_csv(\"data/train_data.csv\", index=False)\n",
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"\n",
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"ds = ws.get_default_datastore()\n",
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"ds.upload(\n",
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" src_dir=\"./data\", target_path=\"bankmarketing\", overwrite=True, show_progress=True\n",
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"target = DataPath(\n",
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" datastore=ds, path_on_datastore=\"bankmarketing/train_data.csv\", name=\"bankmarketing\"\n",
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")\n",
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"Dataset.File.upload_directory(\n",
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" src_dir=\"./data\", target=target, overwrite=True, show_progress=True\n",
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")\n",
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"\n",
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"\n",
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"# Upload the training data as a tabular dataset for access during training on remote compute\n",
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"train_data = Dataset.Tabular.from_delimited_files(\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.12"
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"version": "3.10.14"
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},
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"nteract": {
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"version": "nteract-front-end@1.0.0"
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"task": "Classification"
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},
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"nbformat": 4,
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"nbformat_minor": 1
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"nbformat_minor": 4
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}

how-to-use-azureml/automated-machine-learning/experimental/autofeaturization-codegen/codegen-for-autofeaturization.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
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"print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
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"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
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]
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},

how-to-use-azureml/automated-machine-learning/experimental/autofeaturization-custom-model-training/custom-model-training-from-autofeaturization-run.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
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"print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
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"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
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]
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},

how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
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"print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
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"print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
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]
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},

how-to-use-azureml/ml-frameworks/pytorch/distributed-pytorch-with-distributeddataparallel/distributed-pytorch-with-distributeddataparallel.ipynb

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"source": [
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"from azureml.core import Environment\n",
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"\n",
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"pytorch_env = Environment.get(ws, name='azureml-acpt-pytorch-1.13-cuda11.7')"
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"pytorch_env = Environment.get(ws, name='azureml-acpt-pytorch-2.2-cuda12.1')"
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]
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},
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{

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