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add megengine example docs (#134)
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@ -42,8 +42,10 @@ Check out some of ClearML's automatic reporting examples for supported packages:
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TensorFlow flags
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* [Tensorboard with PyTorch](../guides/frameworks/pytorch/pytorch_tensorboard.md) - logging TensorBoard scalars, debug samples, and text integrated into
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code that uses PyTorch
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* [TensorBoardX](../guides/frameworks/tensorboardx/tensorboardx.md) - logging TensorBoardX scalars, debug
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* TensorBoardX
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* [TensorBoardX with Pytorch](../guides/frameworks/tensorboardx/tensorboardx.md) - logging TensorBoardX scalars, debug
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samples, and text in code using PyTorch
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* [MegEngine MNIST](../guides/frameworks/megengine/megengine_mnist.md) - logging scalars using TensorBoardX's `SummaryWriter`
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* Matplotlib
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* [Matplotlib](../guides/frameworks/matplotlib/matplotlib_example.md) - logging scatter diagrams plotted with Matplotlib
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* [Matplotlib with PyTorch](../guides/frameworks/pytorch/pytorch_matplotlib.md) - logging debug images shown
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docs/guides/frameworks/megengine/megengine_mnist.md
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docs/guides/frameworks/megengine/megengine_mnist.md
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---
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title: MegEngine MNIST
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---
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The [megengine_mnist.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/megengine/megengine_mnist.py)
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example demonstrates the integration of ClearML into code that uses [MegEngine](https://github.com/MegEngine/MegEngine)
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and [TensorBoardX](https://github.com/lanpa/tensorboardX). ClearML automatically captures models saved with `megengine`.
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The example script does the following:
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* Trains a simple deep neural network on MegEngine's built-in [MNIST](https://megengine.org.cn/doc/stable/en/reference/api/megengine.data.dataset.MNIST.html)
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dataset.
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* Creates a TensorBoardX `SummaryWriter` object to log scalars during training.
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* Creates a ClearML experiment named `megengine mnist train`, which is associated with the `examples` project.
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## Hyperparameters
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ClearML automatically logs command line options defined with `argparse`. They appear in the experiment's **CONFIGURATIONS**
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page under **HYPER PARAMETERS** **>** **Args**.
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## Scalars
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The example script's `train` function calls TensorBoardX's `SummaryWriter.add_scalar` method to report `loss`.
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ClearML automatically captures the data that is added to the `SummaryWriter` object.
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These scalars can be visualized in plots, which appear in the ClearML [WebApp](../../../webapp/webapp_home.md), in the
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experiment's **RESULTS** **>** **SCALARS** page.
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## Models
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ClearML automatically captures the model logged using the `megengine.save` method, and saves it as an artifact.
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View saved snapshots in the experiment's **ARTIFACTS** tab.
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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.
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The model info panel contains the model details, including:
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* Model URL
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* Framework
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* Snapshot locations.
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## Console
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All console output during the script’s execution appears in the experiment’s **RESULTS > CONSOLE** page.
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@ -67,11 +67,10 @@ module.exports = {
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{'Frameworks': [
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{'Autokeras': ['guides/frameworks/autokeras/integration_autokeras', 'guides/frameworks/autokeras/autokeras_imdb_example']},
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{'FastAI': ['guides/frameworks/fastai/fastai_with_tensorboard']},
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{
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'Keras': ['guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']
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},
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{'Keras': ['guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']},
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{'LightGBM': ['guides/frameworks/lightgbm/lightgbm_example']},
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{'Matplotlib': ['guides/frameworks/matplotlib/matplotlib_example']},
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{'MegEngine':['guides/frameworks/megengine/megengine_mnist']},
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{'PyTorch':
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['guides/frameworks/pytorch/pytorch_distributed_example', 'guides/frameworks/pytorch/pytorch_matplotlib',
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'guides/frameworks/pytorch/pytorch_mnist', 'guides/frameworks/pytorch/pytorch_tensorboard', 'guides/frameworks/pytorch/pytorch_tensorboardx',
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