Microsoft Azure Machine Learning TensorBoard API for Python
This package has been tested with Python 3.6 and 3.7.
The SDK is released with backwards compatibility guarantees.
The Azure Machine Learning azureml-tensorboard package combines the AzureML SDK with TensorBoard visualization.
It can be used to:
Export run history to TensorBoard logs directory. You can run TensorBoard against the directory to view metrics.
Launch TensorBoard from run history. TensorFlow logs can be written to a specified logs directory and then automatically loaded in real-time from Azure Blob Storage.
Setup
Follow these instructions to install the Azure ML SDK on your local machine, create an Azure ML workspace, and set up your notebook environment, which is required for the next step. Once you have set up your environment, install the AzureML TensorBoard package:
pip install azureml-tensorboard1 maintainer
Metadata
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Release files for azureml-tensorboard 1.62.0
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| File | Interpreter | ABI | Platform | Reset |
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| azureml_tensorboard-1.62.0-py3-none-any.whl | Python 3 | none | any | Details |
Release files / azureml_tensorboard-1.62.0-py3-none-any.whl
| Download URL | azureml_tensorboard-1.62.0-py3-none-any.whl |
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| Size | 10.1 kB |
| Tags | Python 3 |
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