--- title: MegEngine --- The [megengine_mnist.py](https://github.com/clearml/clearml/blob/master/examples/frameworks/megengine/megengine_mnist.py) example demonstrates the integration of ClearML into code that uses [MegEngine](https://github.com/MegEngine/MegEngine) and [TensorBoardX](https://github.com/lanpa/tensorboardX). ClearML automatically captures models saved with `megengine`. The example script does the following: * Trains a simple deep neural network on MegEngine's built-in [MNIST](https://www.megengine.org.cn/doc/master/en/reference/api/megengine.data.dataset.MNIST.html) dataset. * Creates a TensorBoardX `SummaryWriter` object to log scalars during training. * Creates a ClearML task named `megengine mnist train` in the `examples` project. ## Hyperparameters ClearML automatically logs command line options defined with `argparse`. They appear in the task's **CONFIGURATION** tab under **HYPERPARAMETERS** **>** **Args**.  ## Scalars The example script's `train` function calls TensorBoardX's `SummaryWriter.add_scalar` method to report `loss`. ClearML automatically captures the data that is added to the `SummaryWriter` object. These scalars can be visualized in plots, which appear in the ClearML [WebApp](../../../webapp/webapp_home.md), in the task's **SCALARS** tab.  ## Models ClearML automatically captures the model logged using the `megengine.save` method, and saves it as an artifact. View saved snapshots in the task's **ARTIFACTS** tab.  To view the model details, click the model name in the **ARTIFACTS** page, which will open the model's info tab. Alternatively, download the model. The model info panel contains the model details, including: * Model URL * Framework * Snapshot locations.  ## Console All console output during the script's execution appears in the task's **CONSOLE** page. 