ronrest

#!/bin/bash

# MAYAVI SETUP
# mayavi is a python library for scientific visualisations, that can handle
# visualisation of Lidar Data. But, it can also be used to project Lidar data
# to 2D images.
# 
# The set of commands I used to get mayavi set up on my computer so far. 
# NOTE: I still do not know if it is set up properly, so this set of steps 
#       might be incomplete. 

telekosmos

One problem when trying to debug a Java application running inside a Docker container is:

You can't expose an additional port when re(starting) a Docker container.

Here are the steps I used to create a remote debugging session for Planets:

In our scenario we can't simply override the Dockerfile CMD or pass an environment variable JAVA_OPTS to enable remote debugging.

So we have to "enter" the container with exec and add the JAVA_OPTS to the start script there:

ipedrazas

kubectl get pods | grep Evicted | awk '{print $1}' | xargs kubectl delete pod

tuannvm

ArgoCD CheatSheet

• ArgoCD CheatSheet
  • Overview
  • Architecture & Components
  • Getting Started
  • Installation & Setup
  • ArgoCD CLI Commands
  • Application Management
• Defining an Application

filipececcon

@ECHO OFF

SET SERVICENAME=MY_SERVICE
SET NSSM="%CD%\nssm\nssm.exe"

ECHO INSTALLING SERVICE %SERVICENAME%

%NSSM% stop %SERVICENAME%
%NSSM% remove %SERVICENAME% confirm
%NSSM% install %SERVICENAME% %SERVICENAME%

ndevenish

cmake_minimum_required(VERSION 3.5)

# Find python and Boost - both are required dependencies
find_package(PythonLibs 2.7 REQUIRED)
find_package(Boost COMPONENTS python REQUIRED)

# Without this, any build libraries automatically have names "lib{x}.so"
set(CMAKE_SHARED_MODULE_PREFIX "")

# Add a shared module - modules are intended to be imported at runtime.

MihaiTheCoder

FROM nvidia/cuda:8.0-cudnn6-devel-ubuntu14.04

RUN apt-get update && apt-get install -y --no-install-recommends \
        autotools-dev \
        build-essential \
        cmake \
        git \
        gfortran-multilib \
        libavcodec-dev \
        libavformat-dev \

charlesreid1

#!/bin/bash
# 
# Download the Large-scale CelebFaces Attributes (CelebA) Dataset
# from their Google Drive link.
# 
# CelebA: http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
# 
# Google Drive: https://drive.google.com/drive/folders/0B7EVK8r0v71pWEZsZE9oNnFzTm8

python3 get_drive_file.py 0B7EVK8r0v71pZjFTYXZWM3FlRnM celebA.zip

jaytaylor

One liner for deleting images from a v2 docker registry

Just plug in your own values for registry and repo/image name.

registry='localhost:5000'
name='my-image'
curl -v -sSL -X DELETE "http://${registry}/v2/${name}/manifests/$(
    curl -sSL -I \
        -H "Accept: application/vnd.docker.distribution.manifest.v2+json" \

jjallaire

'''Train MNIST with tfrecords yielded from a TF Dataset

In order to run this example you should first run 'mnist_to_tfrecord.py'
which will download MNIST data and serialize it into 3 tfrecords files
(train.tfrecords, validation.tfrecords, and test.tfrecords).

This example demonstrates the use of TF Datasets wrapped by a generator
function. The example currently only works with a fork of keras that accepts
`workers=0` as an argument to fit_generator, etc. Passing `workers=0` results
in the generator function being run on the main thread (without this various