chenerg

Here's a simple implementation of bilinear interpolation on tensors using PyTorch.

I wrote this up since I ended up learning a lot about options for interpolation in both the numpy and PyTorch ecosystems. More generally than just interpolation, too, it's also a nice case study in how PyTorch magically can put very numpy-like code on the GPU (and by the way, do autodiff for you too).

For interpolation in PyTorch, this open issue calls for more interpolation features. There is now a nn.functional.grid_sample() feature but at least at first this didn't look like what I needed (but we'll come back to this later).

In particular I wanted to take an image, W x H x C, and sample it many times at different random locations. Note also that this is different than upsampling which exhaustively samples and also doesn't give us fle

	import torch
	from torch import nn
	from torch.autograd import Variable
	import torch.nn.functional as F
	import torch.optim as optim


	# toy feed-forward net
	class Net(nn.Module):
	def __init__(self):

	#!/bin/bash

	# This script downloads and installs a specific version of VSCode Server for Linux.
	# The version is specified by the first argument to the script.
	# You can find the git commit id in the output of Remote - SSH plugin in VSCode.
	# The output looks like this:
	# ...
	# Using commit id "af28b32d7e553898b2a91af498b1fb666fdebe0c" and quality "stable" for server
	# ...