releasing feature as nightly (#5233)

Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>
(cherry picked from commit c479351a93)
This commit is contained in:
Jirka Borovec 2020-12-23 21:29:00 +01:00 committed by Jirka Borovec
parent 52c3081b4c
commit 5e71c88096
2 changed files with 24 additions and 8 deletions

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@ -13,7 +13,10 @@ jobs:
runs-on: ubuntu-20.04 runs-on: ubuntu-20.04
steps: steps:
# does nightly releases from feature branch
- uses: actions/checkout@v2 - uses: actions/checkout@v2
with:
ref: release/1.2-dev
- uses: actions/setup-python@v2 - uses: actions/setup-python@v2
with: with:
python-version: 3.7 python-version: 3.7
@ -29,7 +32,6 @@ jobs:
ls -lh dist/ ls -lh dist/
- name: Delay releasing - name: Delay releasing
if: startsWith(github.event.ref, 'refs/tags') || github.event_name == 'release'
uses: juliangruber/sleep-action@v1 uses: juliangruber/sleep-action@v1
with: with:
time: 5m time: 5m

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@ -101,7 +101,7 @@ Lightning can automatically export to ONNX or TorchScript for those cases.
## How To Use ## How To Use
#### Step 0: Install ### Step 0: Install
Simple installation from PyPI Simple installation from PyPI
```bash ```bash
@ -114,12 +114,26 @@ From Conda
conda install pytorch-lightning -c conda-forge conda install pytorch-lightning -c conda-forge
``` ```
Install bleeding-edge (no guarantees) #### Install bleeding-edge - future 1.2
the actual status of 1.2 [nightly] is following:
![CI base testing](https://github.com/PyTorchLightning/pytorch-lightning/workflows/CI%20base%20testing/badge.svg?branch=release%2F1.2-dev&event=push)
![CI complete testing](https://github.com/PyTorchLightning/pytorch-lightning/workflows/CI%20complete%20testing/badge.svg?branch=release%2F1.2-dev&event=push)
![PyTorch & Conda](https://github.com/PyTorchLightning/pytorch-lightning/workflows/PyTorch%20&%20Conda/badge.svg?branch=release%2F1.2-dev&event=push)
![TPU tests](https://github.com/PyTorchLightning/pytorch-lightning/workflows/TPU%20tests/badge.svg?branch=release%2F1.2-dev&event=push)
![Docs check](https://github.com/PyTorchLightning/pytorch-lightning/workflows/Docs%20check/badge.svg?branch=release%2F1.2-dev&event=push)
Install future release from the source (no guarantees)
```bash ```bash
pip install git+https://github.com/PytorchLightning/pytorch-lightning.git@master --upgrade pip install git+https://github.com/PytorchLightning/pytorch-lightning.git@release/1.2-dev --upgrade
```
or nightly from testing PyPI
```bash
pip install -iU https://test.pypi.org/simple/ pytorch-lightning
``` ```
#### Step 0: Add these imports ### Step 1: Add these imports
```python ```python
import os import os
@ -132,7 +146,7 @@ from torchvision import transforms
import pytorch_lightning as pl import pytorch_lightning as pl
``` ```
#### Step 1: Define a LightningModule (nn.Module subclass) ### Step 2: Define a LightningModule (nn.Module subclass)
A LightningModule defines a full *system* (ie: a GAN, autoencoder, BERT or a simple Image Classifier). A LightningModule defines a full *system* (ie: a GAN, autoencoder, BERT or a simple Image Classifier).
```python ```python
@ -163,9 +177,9 @@ class LitAutoEncoder(pl.LightningModule):
return optimizer return optimizer
``` ```
###### Note: Training_step defines the training loop. Forward defines how the LightningModule behaves during inference/prediction. **Note: Training_step defines the training loop. Forward defines how the LightningModule behaves during inference/prediction.**
#### Step 2: Train! ### Step 3: Train!
```python ```python
dataset = MNIST(os.getcwd(), download=True, transform=transforms.ToTensor()) dataset = MNIST(os.getcwd(), download=True, transform=transforms.ToTensor())