Check this out on Dev.to
- How to handle SSH keys with ec2-github actions https://zellwk.com/blog/github-actions-deploy/
- SSH_PRIVATE_KEY
- HOST_NAME / IP_ADDRESS
Check this out on Dev.to
| dataset | meta data | contents | with audio |
|---|---|---|---|
| 200DrumMachines | 7371 one-shots | yes | |
| AAM | onsets, pitches, instruments, melody instrument, keys, chords, tempo, beats | 3000 (artificial) tracks | yes |
| ACM_MIRUM | tempo | 1410 excerpts (60s) | yes |
| ACPAS | aligned audio and scores | 2189 performances of 497 scores | downloadable |
| AcousticBrainz-Genre | 15-31 genres with 265-745 subgenres | audio features for ove |
| """ | |
| Train a neural network to implement the discrete Fourier transform | |
| """ | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| from tensorflow.keras.layers import Dense | |
| from tensorflow.keras.models import Sequential | |
| N = 32 | |
| batch = 10000 |
| # This compiles and installs gnuradio including gnuradio-companion for MacOS. | |
| # It uses homebrew (https://brew.sh/) for all non-python libraries and pyenv | |
| # (https://github.com/pyenv/pyenv) for managing python. I'm sure some of this | |
| # would be easier if I used homebrew for python as well but I've found pyenv | |
| # and standard pip to be less buggy in general. However it does mean that for | |
| # python packages that don't install with pip you need to download and compile | |
| # the packages. | |
| # | |
| # Note that this script is not very robust yet, it's not made to run more than | |
| # once (sorry). ~If~ When you find bugs please let me know and we'll update |
Python is the primary language in which TensorFlow models are typically developed and trained. TensorFlow does have bindings for other programming languages. These bindings have the low-level primitives that are required to build a more complete API, however, lack much of the higher-level API richness of the Python bindings, particularly for defining the model structure.
This file demonstrates taking a model (a TensorFlow graph) created by a Python program and running the training loop in C++.
This is my attempt to give Scala newcomers a quick-and-easy rundown to the prerequisite steps they need to a) try Scala, and b) get a standard project up and running on their machine. I'm not going to talk about the language at all; there are plenty of better resources a google search away. This is just focused on the prerequisite tooling and machine setup. I will not be assuming you have any background in JVM languages. So if you're coming from Python, Ruby, JavaScript, Haskell, or anywhere… I hope to present the information you need without assuming anything.
Disclaimer It has been over a decade since I was new to Scala, and when I was new to Scala, I was coming from a Java and Ruby background. This has probably caused me to unknowingly make some assumptions. Please feel free to call me out in comments/tweets!
One assumption I'm knowingly making is that you're on a Unix-like platform. Sorry, Windows users.
| # for ISAKMP (handling of security associations) | |
| iptables -A INPUT -p udp --dport 500 --j ACCEPT | |
| # for NAT-T (handling of IPsec between natted devices) | |
| iptables -A INPUT -p udp --dport 4500 --j ACCEPT | |
| # for ESP payload (the encrypted data packets) | |
| iptables -A INPUT -p esp -j ACCEPT | |
| # for the routing of packets on the server | |
| iptables -t nat -A POSTROUTING -j SNAT --to-source %IP% -o eth0 | |
| # internet access | |
| iptables -t nat -A POSTROUTING -s 10.0.42.0/24 -o eth0 -m policy --dir out --pol ipsec -j ACCEPT |
$ uname -r