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extend pip install info (#194)
* extend pip install info * Update README.md * Update README.md
This commit is contained in:
Jirka Borovec
committed by
William Falcon
William Falcon
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7e0ac3149c
commit
447ed30716
@@ -43,7 +43,8 @@ Every research project starts the same, a model, a training loop, validation loo
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Lightning sets up all the boilerplate state-of-the-art training for you so you can focus on the research.
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---
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---
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## README Table of Contents
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- [How do I use it](https://github.com/williamFalcon/pytorch-lightning#how-do-i-do-use-it)
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- [What lightning automates](https://github.com/williamFalcon/pytorch-lightning#what-does-lightning-control-for-me)
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@@ -57,7 +58,8 @@ Lightning sets up all the boilerplate state-of-the-art training for you so you c
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- [Asking for help](https://github.com/williamFalcon/pytorch-lightning#asking-for-help)
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- [FAQ](https://github.com/williamFalcon/pytorch-lightning#faq)
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---
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---
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## How do I do use it?
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Think about Lightning as refactoring your research code instead of using a new framework. The research code goes into a [LightningModule]((https://williamfalcon.github.io/pytorch-lightning/LightningModule/RequiredTrainerInterface/)) which you fit using a Trainer.
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@@ -122,7 +124,6 @@ class CoolSystem(pl.LightningModule):
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# OPTIONAL
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return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
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```
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2. Fit with a [trainer](https://williamfalcon.github.io/pytorch-lightning/Trainer/)
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```python
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from pytorch_lightning import Trainer
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@@ -134,7 +135,7 @@ trainer = Trainer()
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trainer.fit(model)
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```
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Or with tensorboard logger and some options turned on such as multi-gpu, etc...
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Or with tensorboard logger and some options turned on such as multi-gpu, etc...
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```python
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from test_tube import Experiment
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@@ -275,18 +276,18 @@ tensorboard --logdir /some/path
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## Lightning automates all of the following ([each is also configurable](https://williamfalcon.github.io/pytorch-lightning/Trainer/)):
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###### Checkpointing
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#### Checkpointing
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- [Model saving](https://williamfalcon.github.io/pytorch-lightning/Trainer/Checkpointing/#model-saving)
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- [Model loading](https://williamfalcon.github.io/pytorch-lightning/LightningModule/methods/#load-from-metrics)
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- [Restoring training session](https://williamfalcon.github.io/pytorch-lightning/Trainer/Checkpointing/#restoring-training-session)
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###### Computing cluster (SLURM)
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#### Computing cluster (SLURM)
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- [Running grid search on a cluster](https://williamfalcon.github.io/pytorch-lightning/Trainer/SLURM%20Managed%20Cluster#running-grid-search-on-a-cluster)
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- [Walltime auto-resubmit](https://williamfalcon.github.io/pytorch-lightning/Trainer/SLURM%20Managed%20Cluster#walltime-auto-resubmit)
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###### Debugging
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#### Debugging
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- [Fast dev run](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#fast-dev-run)
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- [Inspect gradient norms](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#inspect-gradient-norms)
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@@ -297,7 +298,7 @@ tensorboard --logdir /some/path
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- [Print input and output size of every module in system](https://williamfalcon.github.io/pytorch-lightning/LightningModule/properties/#example_input_array)
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###### Distributed training
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#### Distributed training
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- [16-bit mixed precision](https://williamfalcon.github.io/pytorch-lightning/Trainer/Distributed%20training/#16-bit-mixed-precision)
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- [Multi-GPU](https://williamfalcon.github.io/pytorch-lightning/Trainer/Distributed%20training/#Multi-GPU)
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@@ -306,7 +307,7 @@ tensorboard --logdir /some/path
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- [Self-balancing architecture](https://williamfalcon.github.io/pytorch-lightning/Trainer/Distributed%20training/#self-balancing-architecture)
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###### Experiment Logging
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#### Experiment Logging
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- [Display metrics in progress bar](https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#display-metrics-in-progress-bar)
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- [Log metric row every k batches](https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#log-metric-row-every-k-batches)
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@@ -316,7 +317,7 @@ tensorboard --logdir /some/path
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- [Snapshot code for a training run](https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#snapshot-code-for-a-training-run)
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- [Write logs file to csv every k batches](https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#write-logs-file-to-csv-every-k-batches)
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###### Training loop
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#### Training loop
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- [Accumulate gradients](https://williamfalcon.github.io/pytorch-lightning/Trainer/Training%20Loop/#accumulated-gradients)
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- [Force training for min or max epochs](https://williamfalcon.github.io/pytorch-lightning/Trainer/Training%20Loop/#force-training-for-min-or-max-epochs)
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@@ -328,7 +329,7 @@ tensorboard --logdir /some/path
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- [Set how much of the training set to check (1-100%)](https://williamfalcon.github.io/pytorch-lightning/Trainer/Training%20Loop/#set-how-much-of-the-training-set-to-check)
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- [Step optimizers at arbitrary intervals](https://williamfalcon.github.io/pytorch-lightning/Trainer/hooks/#optimizer_step)
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###### Validation loop
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#### Validation loop
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- [Check validation every n epochs](https://williamfalcon.github.io/pytorch-lightning/Trainer/Validation%20loop/#check-validation-every-n-epochs)
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- [Hooks](https://williamfalcon.github.io/pytorch-lightning/Trainer/hooks/)
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@@ -337,7 +338,7 @@ tensorboard --logdir /some/path
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- [Set validation check frequency within 1 training epoch](https://williamfalcon.github.io/pytorch-lightning/Trainer/Validation%20loop/#set-validation-check-frequency-within-1-training-epoch)
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- [Set the number of validation sanity steps](https://williamfalcon.github.io/pytorch-lightning/Trainer/Validation%20loop/#set-the-number-of-validation-sanity-steps)
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###### Testing loop
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#### Testing loop
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- [Run test set](https://williamfalcon.github.io/pytorch-lightning/Trainer/Testing%20loop/)
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## Demo
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@@ -378,7 +379,7 @@ If you have any questions, feel free to:
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If no one replies to you quickly enough, feel free to post the stackoverflow link to our Gitter chat!
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To chat with the rest of us visit our [gitter channel](https://gitter.im/PyTorch-Lightning/community?utm_source=share-link&utm_medium=link&utm_campaign=share-link)!
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To chat with the rest of us visit our [gitter channel](https://gitter.im/PyTorch-Lightning/community)!
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---
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## FAQ
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@@ -404,22 +405,36 @@ Nope.
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Nope. Please use anaconda or miniconda.
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**Which PyTorch versions do you support?**
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##### PyTorch 1.1.0
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```bash
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# install pytorch 1.1.0 using the official instructions
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- **PyTorch 1.1.0**
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```bash
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# install pytorch 1.1.0 using the official instructions
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# install test-tube 0.6.7.6 which supports 1.1.0
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pip install test-tube==0.6.7.6
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# install latest Lightning version without upgrading deps
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pip install -U --no-deps pytorch-lightning
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```
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- **PyTorch 1.2.0**
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Install via pip as normal
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# install test-tube 0.6.7.6 which supports 1.1.0
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pip install test-tube==0.6.7.6
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## Custom installation
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# install latest Lightning version without upgrading deps
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pip install -U --no-deps pytorch-lightning
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```
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### Bleeding edge
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##### PyTorch 1.2.0
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Install via pip as normal
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If you can't wait for the next release, install the most up to date code with:
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* using GIT (locally clone whole repo with full history)
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```bash
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pip install git+https://github.com/williamFalcon/pytorch-lightning.git@master --upgrade
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```
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* using instant zip (last state of the repo without git history)
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```bash
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pip install https://github.com/williamFalcon/pytorch-lightning/archive/master.zip --upgrade
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```
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## Bleeding edge
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If you can't wait for the next release, install the most up to date code with:
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### Any release installation
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You can also install any past release from this repository:
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```bash
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pip install git+https://github.com/williamFalcon/pytorch-lightning.git@master --upgrade
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pip install https://github.com/williamFalcon/pytorch-lightning/archive/0.4.4.zip --upgrade
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```
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