| def f1_loss(y_true:torch.Tensor, y_pred:torch.Tensor, is_training=False) -> torch.Tensor: | |
| '''Calculate F1 score. Can work with gpu tensors | |
| The original implmentation is written by Michal Haltuf on Kaggle. | |
| Returns | |
| ------- | |
| torch.Tensor | |
| `ndim` == 1. 0 <= val <= 1 | |
| #!/bin/sh | |
| IP=192.168.2.200 | |
| docker run -d -p $IP:8019:8019 voxhub/silvius-worker:latest /bin/sh -c 'cd /root/silvius-backend ; python kaldigstserver/master_server.py' | |
| docker run -d voxhub/silvius-worker /root/worker.sh -u ws://$IP:8019/worker/ws/speech |
| 7 | |
| 2 | |
| 1 | |
| 0 | |
| 4 | |
| 1 | |
| 4 | |
| 9 | |
| 5 | |
| 9 |
| -- this program takes an original image, such as a photo, | |
| -- and a generated image, such as generated by jcjohnson/fast-neural-style | |
| -- and copies the original colors to the generated image | |
| -- like when using the original_colors param in jcjohnson/neural-style | |
| -- | |
| -- by hannu töyrylä @htoyryla 30 oct 2016 | |
| -- | |
| require 'torch' | |
| require 'image' |
| import urllib2, re, json, os, time, sys, HTMLParser | |
| html_parser = HTMLParser.HTMLParser() | |
| auth_address = "1KbV1e1u6P6AsY8XNBydgtbtN8iSB5WMyG" | |
| auth_privatekey = "xxxx" | |
| site = "1TaLkFrMwvbNsooF4ioKAY9EuxTBTjipT" | |
| zeronet_dir = ".." | |
| os.chdir(zeronet_dir) |
| """ | |
| 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) |
The purpose of this document is to make recommendations on how to browse in a privacy and security conscious manner. This information is compiled from a number of sources, which are referenced throughout the document, as well as my own experiences with the described technologies.
I welcome contributions and comments on the information contained. Please see the How to Contribute section for information on contributing your own knowledge.
name: CaffeNet fine-tuned on the Oxford 102 category flower dataset
caffemodel: oxford102.caffemodel
caffemodel_url: https://s3.amazonaws.com/jgoode/oxford102.caffemodel
gist_id: 0179e52305ca768a601f
license: BSD-3
| #!/bin/bash | |
| ### Command log to install Cuda Toolkit 6.5, driver 343.22, and ccminer. | |
| ## Update the system | |
| sudo apt-get update && sudo apt-get -y dist-upgrade | |
| # All the dependencies for Cuda & ccminer (I think) | |
| sudo apt-get -y install gcc g++ build-essential automake linux-headers-$(uname -r) git gawk libcurl4-openssl-dev libjansson-dev xorg libc++-dev libgmp-dev python-dev | |
