Lucas Vazquez lgvaz

How to mount a GCP compute instance filesystem locally using `sshfs`

This guide assumes that:

make sure your gcloud config is correct for the instance you're trying to access:

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

	import torch
	from torch.optim.lr_scheduler import CosineAnnealingLR
	from torch.optim import SGD
	import matplotlib.pyplot as plt

	STEPS = 100

	optimizer = SGD([torch.tensor(1)], lr=1)
	# Use a scheduler of your choice below.
	# Great for debugging your own schedulers!

	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats

	# Typical setup to include TensorFlow.
	import tensorflow as tf

	# Make a queue of file names including all the JPEG images files in the relative
	# image directory.
	filename_queue = tf.train.string_input_producer(
	tf.train.match_filenames_once("./images/*.jpg"))

	# Read an entire image file which is required since they're JPEGs, if the images
	# are too large they could be split in advance to smaller files or use the Fixed