Eugene Liu eugene123tw

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

Installing Postgres via Brew

Pre-Reqs

Brew Package Manager

In your command-line run the following commands:

brew doctor
brew update

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

How to use multiple instances of gcc?

You need to let update-alternatives to know that you have 2 C/C++ compilers, create a record for each one, and then configure which one you want to use.

This is done with the following:

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.7 60 --slave /usr/bin/g++ g++ /usr/bin/g++-4.7
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.8 40 --slave /usr/bin/g++ g++ /usr/bin/g++-4.8
sudo update-alternatives --config gcc

	{
	// Use IntelliSense to learn about possible attributes.
	// Hover to view descriptions of existing attributes.
	// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
	"version": "0.2.0",
	"configurations": [
	{
	"name": "Python: Flask",
	"type": "python",
	"request": "launch",

	// 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

	{
	"configurations": [
	{
	"name": "Linux",
	"includePath": [
	"${workspaceFolder}/**",
	"/usr/include/python3.6m",
	"/usr/local/cuda-10.0/targets/x86_64-linux/include",
	"{PYTORCH_ENV}/lib/python3.6/site-packages/torch/include",
	"{PYTORCH_ENV}/lib/python3.6/site-packages/torch/include/torch/csrc/api/include",

	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

	import pickle
	import numpy as np
	from data_processor import *
	import tensorflow as tf
	from tool import *
	from model import LeNet

	def detect():
	### Replace each question mark with the appropriate value.
	### Use python, pandas or numpy methods rather than hard coding the results