57 lines
1.6 KiB
Markdown
57 lines
1.6 KiB
Markdown
## Basic Examples
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Use these examples to test how Lightning works.
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### AutoEncoder
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This script shows you how to implement a CNN auto-encoder.
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```bash
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# CPU
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python autoencoder.py
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# GPUs (any number)
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python autoencoder.py --trainer.accelerator 'gpu' --trainer.devices 2
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# Distributed Data Parallel (DDP)
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python autoencoder.py --trainer.accelerator 'gpu' --trainer.devices 2 --trainer.strategy 'ddp'
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```
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______________________________________________________________________
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### Backbone Image Classifier
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This script shows you how to implement a `LightningModule` as a system.
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A system describes a `LightningModule` which takes a single `torch.nn.Module` which makes exporting to producion simpler.
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```bash
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# CPU
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python backbone_image_classifier.py
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# GPUs (any number)
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python backbone_image_classifier.py --trainer.accelerator 'gpu' --trainer.devices 2
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# Distributed Data Parallel (DDP)
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python backbone_image_classifier.py --trainer.accelerator 'gpu' --trainer.devices 2 --trainer.strategy 'ddp'
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```
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______________________________________________________________________
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### Transformers
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This example contains a simple training loop for next-word prediction with a [Transformer model](https://arxiv.org/abs/1706.03762) on a subset of the [WikiText2](https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/) dataset.
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```bash
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python transformer.py
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```
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______________________________________________________________________
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### PyTorch Profiler
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This script shows you how to activate the [PyTorch Profiler](https://github.com/pytorch/kineto) with Lightning.
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```bash
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python profiler_example.py
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```
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