Jianjie(JJ) Luo jianjieluo

Moving to ES6 from CoffeeScript

I fell in love with CoffeeScript a couple of years ago. Javascript has always seemed something of an interesting curiosity to me and I was happy to see the meteoric rise of Node.js, but coming from a background of Python I really preferred a cleaner syntax.

In any fast moving community it is inevitable that things will change, and so today we see a big shift toward ES6, the new version of Javascript. It incorporates a handful of the nicer features from CoffeeScript and is usable today through tools like Babel. Here are some of my thoughts and issues on moving away from CoffeeScript in favor of ES6.

While reading I suggest keeping open a tab to Babel's learning ES6 page. The examples there are great.

Punctuation

Holy punctuation, Batman! Say goodbye to your whitespace and hello to parenthesis, curly braces, and semicolons again. Even with the advanced ES6 syntax you'll find yourself writing a lot more punctuatio

Updated 4/11/2018

Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.

	import os
	from PIL import Image


	'''
	I searched high and low for solutions to the "extract animated GIF frames in Python"
	problem, and after much trial and error came up with the following solution based
	on several partial examples around the web (mostly Stack Overflow).

	There are two pitfalls that aren't often mentioned when dealing with animated GIFs -

	/* Solarized Dark

	For use with Jekyll and Pygments

	http://ethanschoonover.com/solarized

	SOLARIZED HEX ROLE
	--------- -------- ------------------------------------------
	base03 #002b36 background
	base01 #586e75 comments / secondary content

	# coding=UTF-8
	from __future__ import division
	import nltk
	import re
	import requests

	# Add your freebase key here
	# If you don't have one, register at https://code.google.com/apis/console
	FREEBASE_KEY = ""

	/* Solarized Dark

	For use with Jekyll and Pygments

	http://ethanschoonover.com/solarized

	SOLARIZED HEX ROLE
	--------- -------- ------------------------------------------
	base03 #002b36 background
	base01 #586e75 comments / secondary content

	# References:
	# [1] Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding, Fukui et al., https://arxiv.org/abs/1606.01847
	# [2] Compact Bilinear Pooling, Gao et al., https://arxiv.org/abs/1511.06062
	# [3] Fast and Scalable Polynomial Kernels via Explicit Feature Maps, Pham and Pagh, https://chbrown.github.io/kdd-2013-usb/kdd/p239.pdf
	# [4] Fastfood — Approximating Kernel Expansions in Loglinear Time, Le et al., https://arxiv.org/abs/1408.3060
	# [5] Original implementation in Caffe: https://github.com/gy20073/compact_bilinear_pooling

	# TODO: migrate to use of new native complex64 types
	# TODO: change strided x coo matmul to torch.matmul(): M[sparse_coo] @ M[strided] -> M[strided]

	import torch
	from torchvision import datasets

	class ImageFolderWithPaths(datasets.ImageFolder):
	"""Custom dataset that includes image file paths. Extends
	torchvision.datasets.ImageFolder
	"""

	# override the __getitem__ method. this is the method that dataloader calls
	def __getitem__(self, index):

	model.zero_grad() # Reset gradients tensors
	for i, (inputs, labels) in enumerate(training_set):
	predictions = model(inputs) # Forward pass
	loss = loss_function(predictions, labels) # Compute loss function
	loss = loss / accumulation_steps # Normalize our loss (if averaged)
	loss.backward() # Backward pass
	if (i+1) % accumulation_steps == 0: # Wait for several backward steps
	optimizer.step() # Now we can do an optimizer step
	model.zero_grad() # Reset gradients tensors
	if (i+1) % evaluation_steps == 0: # Evaluate the model when we...

Jianjie(JJ) Luo jianjieluo

Moving to ES6 from CoffeeScript

Punctuation

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