Ruben Stefanus rubentea16

Pull Request Etiquette

Why do we use a Pull Request workflow?

PRs are a great way of sharing information, and can help us be aware of the changes that are occuring in our codebase. They are also an excellent way of getting peer review on the work that we do, without the cost of working in direct pairs.

Ultimately though, the primary reason we use PRs is to encourage quality in the commits that are made to our code repositories

Done well, the commits (and their attached messages) contained within tell a story to people examining the code at a later date. If we are not careful to ensure the quality of these commits, we silently lose this ability.

Semantic Commit Messages

See how a minor change to your commit message style can make you a better programmer.

Format: <type>(<scope>): <subject>

<scope> is optional

	model = LightningMNISTClassifier(lr_rate=1e-3)

	# Learning Rate Logger
	lr_logger = LearningRateLogger()

	# Set Early Stopping
	early_stopping = EarlyStopping('val_loss', mode='min', patience=5)

	# saves checkpoints to 'model_path' whenever 'val_loss' has a new min
	checkpoint_callback = ModelCheckpoint(filepath=model_path+'mnist_{epoch}-{val_loss:.2f}',

	def prepare_data():
	# transforms for images
	transform=transforms.Compose([transforms.ToTensor(),
	transforms.Normalize((0.1307,), (0.3081,))])

	# prepare transforms standard to MNIST
	mnist_train = MNIST(os.getcwd(), train=True, download=True, transform=transform)
	mnist_train = [mnist_train[i] for i in range(2200)]

	mnist_train, mnist_val = random_split(mnist_train, [2000, 200])

	# Custom Callbacks
	class MyPrintingCallback(pl.callbacks.base.Callback):

	def on_init_start(self, trainer):
	print('Starting to init trainer!')

	def on_init_end(self, trainer):
	print('trainer is init now')

	def on_train_end(self, trainer, pl_module):

	import torch
	import pytorch_lightning as pl
	import os

	from torch import nn
	from torch.nn import functional as F
	from torch.utils.data import TensorDataset, DataLoader, random_split
	from torchvision.datasets import MNIST
	from torchvision import datasets, transforms

	import concurrent.futures
	import time

	start = time.perf_counter()

	def do_something(seconds):
	print(f'Sleeping {seconds} second(s)...')
	time.sleep(seconds)
	return f'Done Sleeping...{seconds}'

Ruben Stefanus rubentea16

Pull Request Etiquette

Why do we use a Pull Request workflow?

Semantic Commit Messages

Example