mirland

video2gif() {
  ffmpeg -y -i "${1}" -vf fps=${3:-10},scale=${2:-320}:-1:flags=lanczos,palettegen "${1}.png"
  ffmpeg -i "${1}" -i "${1}.png" -filter_complex "fps=${3:-10},scale=${2:-320}:-1:flags=lanczos[x];[x][1:v]paletteuse" "${1}".gif
  rm "${1}.png"
}

record_gif() {
    if [ -z "$1" ]; then
        VIDEO_NAME=$(date +%F_%H-%M-%S)

korakot

# authenticate
from google.colab import auth
auth.authenticate_user()
import gspread
from oauth2client.client import GoogleCredentials as GC
gc = gspread.authorize(GC.get_application_default())
# create, and save df
from gspread_dataframe import set_with_dataframe
title = 'New Sheet'
gc.create(title)  # if not exist

bryant1410

import time

import torch
import torch.nn as nn

from apex.normalization import FusedLayerNorm


torch.backends.cudnn.benchmark = True

eidosam

#!/usr/bin/env bash

### ------ Preparation ------ ###
# Acquire new user credentials to use for Application Default Credentials
# Run: gcloud auth application-default login
### ------ -------------- --- ###

function printUsage() {
    echo -e "
        \rUsage: bash ./create-transfer-job.sh [options] <s3-source-data> <gcs-bucket-name>

mirland

apply from: rootProject.file('read_secrets.gradle')

apply plugin: 'com.android.application'
....

android {
    defaultConfig {
        buildConfigField 'String', 'SOMETHING_SECRET', getEnvVariable('SOMETHING_SECRET')
    }
    signingConfigs {

JSchulte01

"""Provides methods around syncing and usage of AWS s3 buckets as local caches rather than individually
downloading every file"""

import os
import shutil
import boto3 as boto
import multiprocessing
import copy
import hashlib

h0bbel

# See http://help.ubuntu.com/community/UpgradeNotes for how to upgrade to
# newer versions of the distribution.
deb http://us.archive.ubuntu.com/ubuntu/ bionic main restricted
# deb-src http://us.archive.ubuntu.com/ubuntu/ bionic main restricted

## Major bug fix updates produced after the final release of the
## distribution.
deb http://us.archive.ubuntu.com/ubuntu/ bionic-updates main restricted
# deb-src http://us.archive.ubuntu.com/ubuntu/ bionic-updates main restricted

zeyademam

Troubleshooting Convolutional Neural Networks

Intro

This is a list of hacks gathered primarily from prior experiences as well as online sources (most notably Stanford's CS231n course notes) on how to troubleshoot the performance of a convolutional neural network . We will focus mainly on supervised learning using deep neural networks. While this guide assumes the user is coding in Python3.6 using tensorflow (TF), it can still be helpful as a language agnostic guide.

Suppose we are given a convolutional neural network to train and evaluate and assume the evaluation results are worse than expected. The following are steps to troubleshoot and potentially improve performance. The first section corresponds to must-do's and generally good practices before you start troubleshooting. Every subsequent section header corresponds to a problem and the section is devoted to solving it. The sections are ordered to reflect "more common" issues first and under each header the "most-eas

willwhitney

from tensorboard.backend.event_processing import event_accumulator
import tensorflow as tf
import glob
import pandas as pd
tf.logging.set_verbosity(tf.logging.ERROR)

basedir = "/path/to/log/directory/"

def load_tf(dirname):
    prefix = basedir + "tboard/VisibleSwimmer-v2/"

Zate

#! /bin/bash

# [get_golang.sh](https://gist.github.com/n8henrie/1043443463a4a511acf98aaa4f8f0f69)
# Download latest Golang release for AMD64
# https://dl.google.com/go/go1.10.linux-amd64.tar.gz

set -euf -o pipefail
# Install pre-reqs
sudo apt-get install python3 git -y
o=$(python3 -c $'import os\nprint(os.get_blocking(0))\nos.set_blocking(0, True)')