Marco Lee marcoleewow

Dealing with Rust to build PactSwiftMockServer

Example of an automated script that does most of this: https://github.com/surpher/PactSwiftMockServer/blob/fb8148866bb05f49a0b1dcaae66c67bad1e7eca7/Support/build_rust_dependencies

Install Rust

curl https://sh.rustup.rs -sSf | sh

Computational Fluid Dynamics (in graphics mostly)

Disclaimer: I have no professional education in Compulational Fluid Dynamics, these are various notes on what I found/learned when trying to learn a bit on the topic. Some of the notes lack sources as I wrote them up later often just remembering some StackExchange answer. Some things I might have misinterpreted.

Computational Fluid Dynamics (in graphics mostly)
General / Overview
- Overarching resources
General Concepts & Keywords

See the official Differentiable Programming Manifesto instead.

Multiplatform (`amd64` and `arm`) Kubernetes cluster setup

The official guide for setting up Kubernetes using kubeadm works well for clusters of one architecture. But, the main problem that crops up is the kube-proxy image defaults to the architecture of the master node (where kubeadm was run in the first place).

This causes issues when arm nodes join the cluster, as they will try to execute the amd64 version of kube-proxy, and will fail.

It turns out that the pod running kube-proxy is configured using a DaemonSet. With a small edit to the configuration, it's possible to create multiple DaemonSets—one for each architecture.

Steps

Follow the instructions at https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/ for setting up the master node. I've been using Weave Net as the network plugin; it see

This guide has moved to a GitHub repository to enable collaboration and community input via pull-requests.

https://github.com/alexellis/k8s-on-raspbian

Alex

	conda uninstall --force pillow -y

	# install libjpeg-turbo to $HOME/turbojpeg
	git clone https://github.com/libjpeg-turbo/libjpeg-turbo
	pushd libjpeg-turbo
	mkdir build
	cd build
	cmake .. -DCMAKE_INSTALL_PREFIX:PATH=$HOME/turbojpeg
	make
	make install

	import numpy as np
	import torch
	import keras

	def pyt_to_keras(pytorch_model, keras_model):
	"""
	Given a PyTorch model, this method transfers the weight to
	a Keras Model (with backend TensorFlow) with the same architecture.
	Assumptions:
	1. The corresponding layer names in both the models will be the same

	"""
	Author: Awni Hannun

	This is an example CTC decoder written in Python. The code is
	intended to be a simple example and is not designed to be
	especially efficient.

	The algorithm is a prefix beam search for a model trained
	with the CTC loss function.

	import math
	from collections import OrderedDict
	import torch.nn as nn
	import torch.nn.init as init
	import torch as th
	import torch.nn.functional as F
	from torch.autograd import Variable


	class SPPLayer(nn.Module):