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Merge pull request #1848 from Azure/release_update/Release-166
update samples from Release-166 as a part of SDK release
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@@ -9,7 +9,6 @@ dependencies:
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- PyJWT < 2.0.0
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- PyJWT < 2.0.0
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- numpy==1.22.3
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- numpy==1.22.3
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- pywin32==227
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- pywin32==227
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- cryptography<37.0.0
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- pip:
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- pip:
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# Required packages for AzureML execution, history, and data preparation.
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# Required packages for AzureML execution, history, and data preparation.
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@@ -11,7 +11,6 @@ dependencies:
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- urllib3==1.26.7
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- urllib3==1.26.7
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- PyJWT < 2.0.0
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- PyJWT < 2.0.0
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- numpy>=1.21.6,<=1.22.3
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- numpy>=1.21.6,<=1.22.3
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- cryptography<37.0.0
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- pip:
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- pip:
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# Required packages for AzureML execution, history, and data preparation.
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# Required packages for AzureML execution, history, and data preparation.
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@@ -166,7 +166,7 @@ def download_data():
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from zipfile import ZipFile
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from zipfile import ZipFile
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# download data
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# download data
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data_file = './fowl_data.zip'
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data_file = './fowl_data.zip'
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download_url = 'https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip'
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download_url = 'https://azuremlexamples.blob.core.windows.net/datasets/fowl_data.zip'
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urllib.request.urlretrieve(download_url, filename=data_file)
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urllib.request.urlretrieve(download_url, filename=data_file)
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# extract files
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# extract files
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@@ -176,7 +176,7 @@
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"### Download training data\n",
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"### Download training data\n",
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"The dataset we will use (located on a public blob [here](https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip) as a zip file) consists of about 120 training images each for turkeys and chickens, with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We will download and extract the dataset as part of our training script `pytorch_train.py`"
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"The dataset we will use (located on a public blob [here](https://azuremlexamples.blob.core.windows.net/datasets/fowl_data.zip) as a zip file) consists of about 120 training images each for turkeys and chickens, with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We will download and extract the dataset as part of our training script `pytorch_train.py`"
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]
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]
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},
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},
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{
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{
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@@ -260,15 +260,14 @@
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"\n",
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"\n",
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"channels:\n",
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"channels:\n",
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"- conda-forge\n",
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"- conda-forge\n",
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"- pytorch\n",
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"dependencies:\n",
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"dependencies:\n",
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"- python=3.6.2\n",
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"- python=3.8.12\n",
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"- pip=21.3.1\n",
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"- pip=21.3.1\n",
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"- pytorch::pytorch==1.8.1\n",
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"- pytorch::torchvision==0.9.1\n",
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"- pip:\n",
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"- pip:\n",
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" - azureml-defaults==1.43.0\n",
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" - azureml-defaults"
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" - torch==1.6.0\n",
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" - torchvision==0.7.0\n",
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" - future==0.17.1\n",
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" - pillow"
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]
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]
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},
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},
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{
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{
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@@ -160,7 +160,7 @@
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"source": [
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"source": [
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"from azureml.core import Dataset\n",
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"from azureml.core import Dataset\n",
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"\n",
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"\n",
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"web_paths = ['https://azureopendatastorage.blob.core.windows.net/testpublic/text8.zip']\n",
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"web_paths = ['https://azuremlexamples.blob.core.windows.net/datasets/text8.zip']\n",
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"dataset = Dataset.File.from_files(path=web_paths)"
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"dataset = Dataset.File.from_files(path=web_paths)"
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]
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]
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},
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},
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