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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

eugene123tw

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eugene123tw

// Copyright(c) Microsoft Corporation.All rights reserved.
// Licensed under the MIT License.
//

/*
pranav@XXX:~$ wget https://github.com/microsoft/onnxruntime/releases/download/v1.8.1/onnxruntime-linux-x64-1.8.1.tgz
....
2021-07-28 19:44:06 (7.60 MB/s) - ‘onnxruntime-linux-x64-1.8.1.tgz’ saved [4736207/4736207]

pranav@XXX:~$ tar xvfz onnxruntime-linux-x64-1.8.1.tgz

eugene123tw

Installing Postgres via Brew

Pre-Reqs

Brew Package Manager

In your command-line run the following commands:

1. brew doctor
2. brew update

eugene123tw

This gist pertains to a Bad Request(400) error when trying to access an EC2 instance running django . . . 

I set up an EC2 server, installed django, started runserver and tested. The result was

Bad Request (400)

When using Django 1.5 and higher, when DEBUG=False in the settings.py file, you must specify ALLOWED_HOSTS 
or you will recieve a "Bad Request (400)" error message when attempting to retrieve a page.

On an Amazone EC2 instance, if you are testing with the public DNS, then you should put the public DNS in

eugene123tw

Initialize

gitflow	git
git flow init	git init
	git commit --allow-empty -m "Initial commit"
	git checkout -b develop master

Connect to the remote repository

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"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)