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update samples from Release-166 as a part of SDK release

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amlrelsa-ms
2022-10-26 18:46:34 +00:00
parent 41de75a584
commit bd629ae454
5 changed files with 8 additions and 11 deletions
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1
how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml
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@@ -9,7 +9,6 @@ dependencies:
- PyJWT < 2.0.0
- numpy==1.22.3
- pywin32==227
- cryptography<37.0.0
- pip:
# Required packages for AzureML execution, history, and data preparation.

1
how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml
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@@ -11,7 +11,6 @@ dependencies:
- urllib3==1.26.7
- PyJWT < 2.0.0
- numpy>=1.21.6,<=1.22.3
- cryptography<37.0.0
- pip:
# Required packages for AzureML execution, history, and data preparation.

2
how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/pytorch_train.py
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@@ -166,7 +166,7 @@ def download_data():
from zipfile import ZipFile
# download data
data_file = './fowl_data.zip'
download_url = 'https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip'
download_url = 'https://azuremlexamples.blob.core.windows.net/datasets/fowl_data.zip'
urllib.request.urlretrieve(download_url, filename=data_file)
# extract files

13
how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/train-hyperparameter-tune-deploy-with-pytorch.ipynb
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@@ -176,7 +176,7 @@
"metadata": {},
"source": [
"### Download training data\n",
"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`"
"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`"
]
},
{
@@ -260,15 +260,14 @@
"\n",
"channels:\n",
"- conda-forge\n",
"- pytorch\n",
"dependencies:\n",
"- python=3.6.2\n",
"- python=3.8.12\n",
"- pip=21.3.1\n",
"- pytorch::pytorch==1.8.1\n",
"- pytorch::torchvision==0.9.1\n",
"- pip:\n",
" - azureml-defaults==1.43.0\n",
" - torch==1.6.0\n",
" - torchvision==0.7.0\n",
" - future==0.17.1\n",
" - pillow"
" - azureml-defaults"
]
},
{

2
how-to-use-azureml/ml-frameworks/tensorflow/distributed-tensorflow-with-horovod/distributed-tensorflow-with-horovod.ipynb
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@@ -160,7 +160,7 @@
"source": [
"from azureml.core import Dataset\n",
"\n",
"web_paths = ['https://azureopendatastorage.blob.core.windows.net/testpublic/text8.zip']\n",
"web_paths = ['https://azuremlexamples.blob.core.windows.net/datasets/text8.zip']\n",
"dataset = Dataset.File.from_files(path=web_paths)"
]
},