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Small fixes (#110)

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pollfly 2021-11-08 11:58:41 +02:00 committed by GitHub
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3 changed files with 3 additions and 3 deletions
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2
docs/guides/data management/data_man_cifar_classification.md
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@ -25,7 +25,7 @@ Execute this python script to download the data
Expected reponse:
```bash
COPY THIS DATASET PATH: /home/erez/.clearml/cache/storage_manager/global/f2751d3a22ccb78db0e07874912b5c43.cifar-10-python_artifacts_archive_None
COPY THIS DATASET PATH: ~/.clearml/cache/storage_manager/global/f2751d3a22ccb78db0e07874912b5c43.cifar-10-python_artifacts_archive_None
```
The script prints the path to the downloaded data. It'll be needed later one

2
docs/guides/frameworks/pytorch ignite/integration_pytorch_ignite.md
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@ -65,6 +65,6 @@ ClearML automatically tracks images logged to TensorboardLogger. They appear in
PyTorch Ignite also offers a dedicated `ClearMLLogger` handler to log metrics, text, model / optimizer parameters, plots, and model
checkpoints during training and validation.
For more information, see the [PyTorch Ignite ClearMLLogger](https://pytorch.org/ignite/generated/ignite.contrib.handlers.clearml_logger.html)
For more information, see the [PyTorch Ignite ClearMLLogger](pytorch_ignite_mnist)
example.

2
docs/guides/frameworks/pytorch ignite/pytorch_ignite_mnist.md
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@ -3,7 +3,7 @@ title: PyTorch Ignite ClearMLLogger
---
The `ignite` repository contains the [mnist_with_clearml_logger.py](https://github.com/pytorch/ignite/blob/master/examples/contrib/mnist/mnist_with_clearml_logger.py)
example script that uses [ignite](https://github.com/pytorch/ignite) and integrates **ClearMLLogger** and its helper [handlers](https://github.com/pytorch/ignite/blob/master/ignite/contrib/handlers/clearml_logger.py).
example script that uses [ignite](https://github.com/pytorch/ignite) and integrates **ClearMLLogger** and its [helper handlers](https://pytorch.org/ignite/generated/ignite.contrib.handlers.clearml_logger.html).
PyTorch Ignite offers a `ClearMLLogger` handler to log metrics, text, model / optimizer parameters, plots, and model
checkpoints during training and validation.