bfloat16 – how it improves AI chip designs

Floating point calculations are slow for computers (specifically CPUs); possibly representing the same struggle for many humans. 🙂

I remember a time when a FPU (floating point unit) was an upgrade and one had to pay extra to get one. Very useful when you needed that extra precision in computing – and in my head, it always seemed like the Turbo button. 🙂

For most #ML workloads and computations, precision isn’t the most important criteria; with every increasing data and parameters (looking at you GPT-3 with 45 TB of data and 175 billion parameters!), what most ML needs today is speed and dynamic range.

This is where bfloat16 (Brain floating-point format with 16 bits) – a new floating-point format comes handy and in the context of #AI improves on IEEE 754 – the current floating-point arithmetic standard.

As per IEEE 754, a floating point it will always take up 32 bits (see Figure 1 below) – irrespective of the size of the number. The exponent (8 bits) tells us how many numbers we shift (left or right) and place the decimal. The fraction (23 bits), also called the mantissa, holds the actual number – i.e. the data.

Figure 1 – IEEE 754 Floating point representation

bfloat16 truncates the data size in a third (see Figure 2) – with the fraction truncated from 23 to 7 bits. This of course means bfloat16 isn’t as precise. However bfloat16 has the same exponent bits as IEEE-754 it can represent a similar range (small to large), but more importantly are easier to convert between bfloat16 and IEEE 754.

Figure 2 – fbloat16 representation

Less precision doesn’t impact the matrix multiplication as much so in the context of ML training and inference these chips at scale are more efficient – not only they are faster, they also use less power, and memory bandwidth.

What is interesting in some neural nets such as a DNN, these less precision bfloat16 are more precise compared to IEEE 754! This is because the regularization and quantization weights cannot use the finer precision represented by IEEE 754 but adapt better with bfloat16. 🙂

Finally, bfloat16 is not a universal standard (yet); most AI chips support this. ARM, Intel, and, AMD have started adding support for this in their chipsets.

WSL2 +Ubuntu on Window 10 (2004)

One of the key advances in the latest version of Windows 10 (2004) is WSL2 (Windows Subsystem for Linux v2) – and whilst a version bump, it offers so much more. This allows us to run with near-native performance linux binaries (ELF64).

Before we get into the steps outlined to install WSL2, I also recommend installing Windows Terminal, and winget. Although not required, it does make it simpler to use and a better (dev) experience – especially when setting up a new workstation.

For WSL2 to work, you need to make sure you are on Windows 10 2004 Build 19041 or higher. If you don’t have this, run Windows update and see if that updates your OS. If that doesn’t offer a update, you could also try the Windows update assistant.

To get WSL2, whilst not complicated one needs to do the following steps, in this order – running the commands in an elevated prompt.

  1. Enable the Windows Subsystem for Linux optional feature.
dism.exe /online /enable-feature /featurename:Microsoft-Windows-Subsystem-Linux /all /norestart
  1. Enable the Virtual machine platform optional feature.
dism.exe /online /enable-feature /featurename:VirtualMachinePlatform /all /norestart
  1. Reboot
  2. Run Windows update (and reboot again if there are updates)
  3. Set WSL2 as your default option.
wsl --set-default-version 2
Administrator: Windows X v 
Administrator: powerf X 
PS C: Bahree> dism.exe /ontine /enabte—feature /featurename:Microsoft—Windows—Subsystem—Linux /att /norestart 
Deployment Image Servicing and Management toot 
Version: 
Image Version: 
Enabling feature(s) 
The operation completed successfully. 
PS C: Bahree> dism.exe /ontine /enabte—feature /featurename:virtualmachineptatform /att /norestart 
Deployment Image Servicing and Management toot 
Version: 
Image Version: 
Enabling feature(s) 
The operation completed successfully. 
PS C: Bahree> dism.exe /ontine /enabte—feature /featurename:virtualmachineptatform /att /norestart 
Deployment Image Servicing and Management toot 
Version: 
Image Version: 
Enabling feature(s) 
The operation completed successfully.
Enabling WSL2
  1. Install your Linux distro of choice. You can do this via Store, or via winget, such as Ubuntu using the following command.
winget install -e --id Canonical.Ubuntu
PS C: Bahree> winget install —e ——id Canonical. Ubuntu 
Found Ubuntu [Canonical . Ubuntu] 
This application is licensed to you by its owner . 
Microsoft is not responsible for, nor does it grant any Licenses to, 
Successfully verified installer hash 
Starting package install... 
100% 
Successfully installed . 
third—party packages .
Installing Ubuntu via winget

Note, when trying to set WSL2 as the default option above (Step 5) and you get a error 0x1bc, that most likely means you need to run Windows update and reboot.

PS C: wsI 
——set—default—version 
2 
Error: exlbc 
For information on key differences with 
WSL 2 please visit https://aka.ms/ws12 
PS C: wsI 
Windows Subsystem for Linux has no installed distributions. 
Distributions can be installed by visiting the Microsoft Store: 
https : / /aka. ms/wslstore
WSL Error

And here is my running Ubuntu and updating it.

Ubuntu 
Installing, this may take a few minutes. . 
Please create a default UNIX user account. The username does not need to match your Windows username. 
For more information visit: https://aka.ms/wslusers 
Enter new UNIX username: amit 
New password: 
Retype new password:
Installing Ubuntu
amitaambahree-laptap: 
$ sudo apt updaze sudo apt upgrade 
lamlcgamoanree-±apcop:•-• 
[sudo] password for amit: 
1 http://security.ubuntu . com/ubuntu focal-security InRe1ease [187 ka] 
et:2 http://archive.ubuntu . com/ubuntu focal InRe1ease [265 ka] 
http://security.ubuntu . com/ubuntu focal -security/main amd64 Packages [147 ka] 
http://archive.ubuntu . com/ubuntu focal -updates InRe1ease [111 ka] 
http://archive.ubuntu . com/ubuntu focal -backports InRe1ease [98.3 ka] 
http://security.ubuntu . com/ubuntu focal-security/main Translation-en [51.8 ka] 
http://security.ubuntu . com/ubuntu focal-security/main amd64 c-n-f Metadata [3432 B] 
http://security.ubuntu . com/ubuntu focal -security/restricted amd64 Packages [28.9 ka] 
http://security.ubuntu . com/ubuntu focal-security/restricted Translation-en [7664 B] 
http://security.ubuntu . com/ubuntu focal-security/restricted amd64 c-n-f Metadata [324 B] 
http://security.ubuntu . com/ubuntu focal-security/universe amd64 Packages [42.8 ka] 
http://security.ubuntu . com/ubuntu focal-security/universe Translation-en [22.6 ka] 
http://security.ubuntu.com/ubuntu focal-security/universe amd64 c-n-f Metadata [1768 B] 
http://security.ubuntu . com/ubuntu focal-security/multiverse amd64 Packages [1172 B] 
http://archive.ubuntu . com/ubuntu focal/main amd64 Packages [978 ka] 
http://security.ubuntu . com/ubuntu focal-security/multiverse Translation-en [548 B] 
http://security.ubuntu.com/ubuntu focal-security/multiverse amd64 c-n-f Metadata [116 B] 
Get : 
Get : 3 
Get . 
Get . 
et. 
Set : 8 
Get . 
• 18 
• 11 
Get . 
• 12 
• 13 
iGet : 14 
Get . 
et. 
• 16 
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et. 
• 18 
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28 
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• 22 
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• 23 
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• 26 
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• 28 'Ittp• 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
http:/'archive.ubuntu . com/ubuntu 
. / 'archive. ubuntu . com/ubuntu 
focal/main Translation -en [SB6 ka] 
focal/main amd64 c-n-f Metadata [29. S ka] 
focal/universe amd64 Packages [8628 ka] 
focal/universe Translation-en [5124 ka] 
focal/universe amd64 c-n-f Metadata [265 ka] 
focal/multiverse amd64 Packages [144 ka] 
focal/multiverse Translation-en [184 ka] 
focal/multiverse amd64 c-n-f Metadata [9136 B] 
focal -updates/main amd64 Packages [312 ka] 
focal -updates/main Translation-en [116 ka] 
focal-u dates/main amd64 c -n-f Metadata 7756 B
Updating Ubuntu

So, what’s the big deal? This is where it gets quite interesting and one simple example is the windows interoperability with Linux – allowing one to run linux commands from within a command prompt.

Mixing Linux and Windows commands

Getting list of users from Microsoft Teams

I recently needed to get a list of users that belong to a specific Microsoft Teams team – and there isnt anything out of the box to get this using the Teams app. AFAIK, the only way to do this is using the Microsoft graph API – for which there are a few options.

For something quick (e.g. getting a list of users in a team), using the Graph explorer could be easy enough. On the other hand, if you need something more robust, you should program against the (REST) API.

Graph Explorer

Navigate to Graph explorer, sign in and authenticate yourself against the specific O365 tenant you are interested in – most folks would only have one.

Microsoft Graph Explorer

Once authenticated, on the panel on the left you see several sample queries and scroll down until you see the Teams.

Teams sample queries

To get members of a specific team, you need to get the team ID for that Team. This is unique ID (GUID) and doesn’t change over the lifetime of the team. If you have this, then go ahead to the next section – Getting team members.

Getting a list of Teams and Team ID

On the query panel in Graph explorer, select the “my joined teams” and run the query. You will get a JSON back that contains the list of teams that you are a member of. The “id” element represents the Team ID which you would need for any team related API calls. For example, I am interested in this specific #AI team: “#Reinforcement Learning and Decision AI”.

Get team details

Getting team members

Once you have the Team ID (the unique GUID that each identifies each team), you can get the members of the team using that option on the left. As shown on the screenshot below, you do need to pass in the team ID to the REST API and this would be something like this (and don’t worry what I am showing below is a fictious GUID):

https://graph.microsoft.com/v1.0/groups/f3f9ad1f-beea-4026-9b86-dd3788404999/members 
Member details for a specific Microsoft Team team

Programmatically getting Microsoft Team details

If you want something more robust and repeatable, then using the API (via code) or PowerShell might be better. If you are programming, you will need to register an app – which can authenticate using the Identify platform. This of course is quite powerful, but at times for simple things might be a bit too much.

In my simple task to get users from Teams, I prefer the PowerShell option. To get this going first you need to install the MicrosoftTeam module. This can be done using the command below.

Install-Module -Name MicrosoftTeams

Depending on your configuration you might get a warning as shown below.

PowerShell module installation

Once the Teams PowerShell module is installed, you can run PowerShell scripts against Teams and achieve the same result. I have two scripts below showing the same steps as with the Graph Explorer above. One of these gets details of the teams that a user is a member of. And the second script is to get members of a selected team.

Using PowerShell to get Team Details

The PowerShell script below to get a Team details is below; you can also get it from GitHub. Before you run this, there are two variables that need to be set.

  • One, the path where you want the team details to be exported (this is a csv file).
  • Two, set the email that you will use. This needs to be the same one that you authenticated against.

You will be prompted to sign in to authentic and this should be an experience that most folks would be familiar with. Note, each time you run the script, you need to authenticate – and this is irrespective of say if you are already logged into Teams of Office 365.

Authenticating user against Office 365

Assuming you have authenticated successfully, you should see an output like the one shown below; and a csv file in the path you configured will be created. This file will always be overwritten – without any prompts (of course this is assuming no other process is open that has a lock on that file).

#Set these variables, to what makes sense in your situation. The email here is the one that is the one connected to your teams account.
$exportLocation = "C:\temp\team-details.csv"
$emailAddress = "your-email@shouldbeputhere.com"

#Authenticate against teams
Connect-MicrosoftTeams

#Patience
Write-Host -ForegroundColor Blue "Successfully connected to Teams"
Write-Host -ForegroundColor Blue "Getting all team details for user: $($emailAddress)"
Write-Host -ForegroundColor Blue "Please be patient, if there are a lot of teams, this can take a while..."

# Get all of the team Groups IDs
# $GetUsersTeams = (Get-Team).GroupID
$GetUsersTeams = Get-Team -User $emailAddress

$Report = @()

# Will hold a basic count of user types and teams
$unavailableTeamCount = 0

# Loop through all teams that the user belongs to
$currentIndex = 1

ForEach($thisTeam in $GetUsersTeams) {
	# Show some output to the user
    Write-Progress -Id 0 -Activity "Building report from Microsoft Teams" -Status "$currentIndex of $($GetUsersTeams.Count)" -PercentComplete (($currentIndex / $GetUsersTeams.Count) * 100)
	
    # Attempt to get team details, throw error message if no access
    try {
        # Get team members
        #$users = Get-TeamUser -GroupId $thisTeam.groupID

		# Create an object to hold all values
        $teamReportObject = New-Object PSObject -Property @{
                GroupID = $thisTeam.GroupID
				TeamName = $thisTeam.DisplayName
                Description = $thisTeam.Description
                Archived = $thisTeam.Archived
                Visibility = $thisTeam.Visibility
				eMail = $thisTeam.MailNickName
            }

            # Add to the report
            $Report += $teamReportObject
       
    } catch [Microsoft.TeamsCmdlets.PowerShell.Custom.ErrorHandling.ApiException] {
        Write-Host -ForegroundColor Yellow "No access to $($team.DisplayName) team, cannot generate report"
        $unavailableTeamCount++
    }
	
	$currentIndex++
}
Write-Progress -Id 0 -Activity " " -Status " " -Completed

# Disconnect from teams
Disconnect-MicrosoftTeams

# Provide some nice output
Write-Host -ForegroundColor Green "============================================================"
Write-Host -ForegroundColor Green "                Microsoft Teams User Report                 "
Write-Host -ForegroundColor Green ""
Write-Host -ForegroundColor Green "  Count of All Teams - $($GetUsersTeams.Count)                "
Write-Host -ForegroundColor Green "  Count of Inaccesible Teams - $($unavailableTeamCount)         "
Write-Host -ForegroundColor Green ""

$Report | Export-CSV $exportLocation -NoTypeInformation -Force
Write-Host -ForegroundColor Blue "Exported report to $($exportLocation)"

Getting Team members using PowerShell

Now that you have the Team ID you are interested, you can run the other PowerShell script (also available on GitHub) to get a list of all the users in a specific team. Like the previous script, you would need set a couple of variables in the script:

  • The Team ID for the team you are interested in.
  • Path for the csv file with details to be saved.

Once you have authenticated and ran the script, the output will look like the one shown below. You get a summary of the team details, and details of the Teams users and their type (owner, member, or guest). And just like earlier, the file will be overwritten without a prompt, assuming no locks on it.

Members of a Microsoft Team
#Global variables to set:
#path of the file where to export
#specific ID of the team that you want the users for. 
$exportLocation = "C:\temp\RL-decision-AI-export.csv"
$TEAM_ID = "f3f9ad1f-beea-4026-9b86-dd3788404999"
            
$Report = @()

# counters
$ownerCount = 0
$memberCount = 0
$guestCount = 0

#connect to teams
Connect-MicrosoftTeams

$team = Get-Team -GroupId $TEAM_ID

#Patience, supposed to be a virtue
Write-Host -ForegroundColor Blue "Successfully connected to Team: $($team.DisplayName)"
Write-Host -ForegroundColor Blue "Getting all users in the team"
Write-Host -ForegroundColor Blue "Please be patient, if there are a lot of users, this can take a while..."

# Attempt to get team users, throw error message if no access
try {
	# Get team members
	$users = Get-TeamUser -GroupId $team.groupID

	# Loop through and get all the users
	$currentIndex = 1
	
	# foreach user create a line in the report
	ForEach($user in $users) {
		# Show some output to the user
		Write-Progress -Id 0 -Activity "Generating user report from Teams" -Status "$currentIndex of $($users.Count)" -PercentComplete (($currentIndex / $users.Count) * 100)
	
		# Maintain a count of user types
		switch($user.Role) {
			"owner" { $ownerCount++ }
			"member" { $memberCount++ }
			"guest" { $guestCount++ }
		}

		# Create an object to hold all values
		$ReportObject = New-Object PSObject -Property @{
			User = $user.Name
			Email = $user.User
			Role = $user.Role
		}

		# Add to the report
		$Report += $ReportObject
		
		$currentIndex++
	}
} 
catch [Microsoft.TeamsCmdlets.PowerShell.Custom.ErrorHandling.ApiException] {
	Write-Host -ForegroundColor Yellow "No access to $($team.DisplayName) team, cannot generate report"
}

#Complete progress
Write-Progress -Id 0 -Activity " " -Status " " -Completed

# Disconnect from teams
Disconnect-MicrosoftTeams

# Write out details for the user
Write-Host -ForegroundColor Green "============================================================"
Write-Host -ForegroundColor Green "                Microsoft Teams User Report                 "
Write-Host -ForegroundColor Green ""
Write-Host -ForegroundColor Green "Team Details:"
Write-Host -ForegroundColor Green "Name: $($team.DisplayName)"
Write-Host -ForegroundColor Green "Description: $($team.Description)"
Write-Host -ForegroundColor Green "Mail Nickname: $($team.MailNickName)"
Write-Host -ForegroundColor Green "Archived: $($team.Archived)"
Write-Host -ForegroundColor Green "Visiblity: $($team.Visibility)"
Write-Host -ForegroundColor Green ""
Write-Host -ForegroundColor Green "Team User Details:"
Write-Host -ForegroundColor Green "Owners - $($ownerCount)"
Write-Host -ForegroundColor Green "Members - $($memberCount)"
Write-Host -ForegroundColor Green "Guests - $($guestCount)"
Write-Host -ForegroundColor Green "============================================================"

$Report | Export-CSV $exportLocation -NoTypeInformation -Force
Write-Host -ForegroundColor Blue "Exported report to $($exportLocation)"

Of course, programming against the API is always more powerful, but sometimes quick and easy is what is needed. 🙂

Livelock == 2020

With everything going around us – this is what 2020 feels like. 🙁

// Livelock == an infinite loop that 
// means the program is frozen
#define FROZEN while(1)
// in hell, there are demons with pitchforks
#define HELL fork();

FROZEN HELL

Git and Code

I think this from xkcd sums up my afternoon quite nicely. Messed up a repo, and then was trying to ‘clean up’.

A huge thank you to Lily, on the team, for working with me to cleaning up my mess, and helping me show some of the ropes.

I know there are quite a few tutorials our there a couple of these that I found including one from Lily.

So go ahead, and setup a experiment repo and don’t be afraid to play and break things.

Maybe this needs to be updated to reflect Git, from REST. 🙂

Deleting Windows run history

If you have butter fingers like me, and over time end up with a lot of old commands with typos in your Windows run box that get annoying – deleting them is a simple. All you need to do it remove the following registry key.

HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Explorer\RunMRU

Now every time one plays with regedit, it can be dangerous – you can also save this commend as a .cmd file, and then run it with admin privileges – essentially does the same thing.

reg delete "HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Explorer\RunMRU" /f

You can also download the same thing from here.

Docker / Docker Compose on a Pi

Been playing with a few things at home, and as part of that was trying to get Docker and Docker Compose running on a Raspberry Pi. Docker Compose if you aren’t familiar with, allows one to run multi-container apps, and is very handy when building multi-tier layered applications – which are quite common.

I was running it docker on my (Synology) NAS, but a recent update from them broke docker – specifically environment variables. That in turn broke the ability to run Docker Compose, and of course a bunch of stuff; and the opportunity to experiment.

First, we need to install docker – which these days is quite simple. You need the ability to ssh into the pi (or if you are connected to a display, then via a terminal prompt). And in some cases if things fail then you might need to run them as root (via sudo). To install docker, run the following:

curl -sSL https://get.docker.com | sh

And once you are done installing docker, then test it by running the classic hello world image. To so that you run the following command – this will get the Hello World image, and once run will automatically remove it (which is because of the –rm option)

docker run --rm hello-world

If everything is installed OK, then you should see a output that looks something like this the shown below. And this is good – means everything is up and running as expected.

pi@pi-server2:~ $ docker run --rm hello-world
Unable to find image 'hello-world:latest' locally
latest: Pulling from library/hello-world
c1eda109e4da: Pull complete
Digest: sha256:b8ba256769a0ac28dd126d584e0a2011cd2877f3f76e093a7ae560f2a5301c00
Status: Downloaded newer image for hello-world:latest

Hello from Docker!
This message shows that your installation appears to be working correctly.

To generate this message, Docker took the following steps:
 1. The Docker client contacted the Docker daemon.
 2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
    (arm32v7)
 3. The Docker daemon created a new container from that image which runs the
    executable that produces the output you are currently reading.
 4. The Docker daemon streamed that output to the Docker client, which sent it
    to your terminal.

To try something more ambitious, you can run an Ubuntu container with:
 $ docker run -it ubuntu bash

Share images, automate workflows, and more with a free Docker ID:
 https://hub.docker.com/

For more examples and ideas, visit:
 https://docs.docker.com/get-started/

To make like more simple, you should add the user you are logged in as to the ‘docker’ group. In my case it is the default ‘pi’ user, so that command would look like this. And for this to take effect, you would need to logout – I just reboot the machine – old habits. 🙂

sudo usermod -aG docker pi

OK, now that docker is installed, lets get to docker-compose. For that we first install pip, and use that to install docker-compose. And don’t forget the apt-get update in the end.

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py && sudo python3 get-pip.py
sudo pip3 install docker-compose
sudo apt-get update

Now before anything else, lets try and make sure all dependencies are there. Create a file called ‘docker-compose.yml’ with the following. You can put this file anywhere, but I like to create a separate folder and save it in that.

In this example I expose port 6666 to the host which is mapped to port 8000 internally on the image. If your port 6666 is taken you can choose another port – it doesn’t matter. Spacing and indent, do matter in a yml file, so you would want to pay extra attention to that.

version: '3'
services:
  webapp:
    ports:
      - 6666:8000
    image: python:3.7-alpine
    command: "python -m http.server 8000"

Once the file is saved you run it with the following command. The image handles you would see are very likely going to be different and that is OK.

pi@pi-server2:~/docker/docker-test $ docker-compose up
Creating network "docker-test_default" with the default driver
Pulling webapp (python:3.7-alpine)...
3.7-alpine: Pulling from library/python
33b18ff7f9b7: Pull complete
0c1f90421c3a: Pull complete
91543a0ba590: Pull complete
913b1310b79e: Pull complete
6b545e90ee55: Pull complete                                                                                             Digest: sha256:9363cb46e52894a22ba87ebec0845d30f4c27efd6b907705ba9a27192b45e797
Status: Downloaded newer image for python:3.7-alpine
Creating docker-test_webapp_1 ... done                                                                                  Attaching to docker-test_webapp_1

At this point, the image is running in attached mode and it seems like it is waiting, when in reality it is running. If you open another ssh terminal and type in the following command – change the port to whatever you used earlier in the yml file.

pi@pi-server2:~ $ curl -iv 0.0.0.0:6666

And if everything is working then you will see a output something like this. And if you see towards the top you got a HTTP 200 – that is all that mattes in this case.

* Expire in 0 ms for 6 (transfer 0x1b097c0)
*   Trying 0.0.0.0...
* TCP_NODELAY set
* Expire in 200 ms for 4 (transfer 0x1b097c0)
* Connected to 0.0.0.0 (127.0.0.1) port 6666 (#0)
> GET / HTTP/1.1
> Host: 0.0.0.0:6666
> User-Agent: curl/7.64.0
> Accept: */*
>
* HTTP 1.0, assume close after body
< HTTP/1.0 200 OK
HTTP/1.0 200 OK
< Server: SimpleHTTP/0.6 Python/3.7.4
Server: SimpleHTTP/0.6 Python/3.7.4
< Date: Thu, 26 Sep 2019 22:10:28 GMT
Date: Thu, 26 Sep 2019 22:10:28 GMT
< Content-type: text/html; charset=utf-8
Content-type: text/html; charset=utf-8
< Content-Length: 915
Content-Length: 915

<
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>Directory listing for /</title>
</head>
<body>
<h1>Directory listing for /</h1>
<hr>
<ul>
<li><a href=".dockerenv">.dockerenv</a></li>
<li><a href="bin/">bin/</a></li>
<li><a href="dev/">dev/</a></li>
<li><a href="etc/">etc/</a></li>
<li><a href="home/">home/</a></li>
<li><a href="lib/">lib/</a></li>
<li><a href="media/">media/</a></li>
<li><a href="mnt/">mnt/</a></li>
<li><a href="opt/">opt/</a></li>
<li><a href="proc/">proc/</a></li>
<li><a href="root/">root/</a></li>
<li><a href="run/">run/</a></li>
<li><a href="sbin/">sbin/</a></li>
<li><a href="srv/">srv/</a></li>
<li><a href="sys/">sys/</a></li>
<li><a href="tmp/">tmp/</a></li>
<li><a href="usr/">usr/</a></li>
<li><a href="var/">var/</a></li>
</ul>
<hr>
</body>
</html>
* Closing connection 0

You can go back to the first ssh session and hit Ctrl + C to shutdown the image. Once you do that you will see something like:

^CGracefully stopping... (press Ctrl+C again to force)
Stopping docker-test_webapp_1 ... done                                                                                  pi@pi-server2:~/docker/docker-test $

Now you know docker-compose and all the dependencies are installed. Next I would want docker to auto start whenever the pi boots up, and for that we will use the following two commands.

sudo systemctl enable docker
sudo systemctl start docker

And that should be it. If you are running low on space you might want to clean up the images we downloaded in testing this installation.

Tesla API v3.9.1

Haven’t had time until now to explore on what is new as Tesla continues to push updates. The latest version as of this post is v3.9.1 which is what there I decompiled and when compared to the earlier version (I had posted (v3.8.2), there three new REST API’s outlined below.

Service data from the car – not sure what exactly does this will. Need to try it.

   "VEHICLE_SERVICE_DATA": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/service_data",
    "AUTH": true
  }

Now, when I call that, I get a 200OK response (see below), so it is accepting the request, and that includes the bearer code in the header as expected. I don’t see anything interesting back, but that could be because my car is not in service. Maybe someone who has their vehicle in the service center can try and validate this.

{
    "response": {}
}

The next new API is a POST, for reports; and calling this just sends a 200OK back, but I don’t know what it is for. It seems very similar to the SEND_LOG method.

"SEND_REPORT": {
    "TYPE": "POST",
    "URI": "api/1/reports",
    "AUTH": true
  }

The next two set of APIs seem quite interesting and related t AutoPilot upgrade. It might be that these could be in app purchases – checking the eligibility, and then allowing one to purchase.

"UPGRADE_ELIGIBILITY": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/eligible_upgrades",
    "AUTH": true
  },
  "AUTOPILOT_UPGRADE_URL": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/purchase_url",
    "AUTH": true
  }

When I try and call the Purchase_URL, I get a HTTP 400, and seems like I am missing some parameters – other than the headers.

{
    "error": "bad_request",
    "error_description": "The data given to this server does not meet our criteria."
}

And calling the eligible_upgrades I get a ‘false’. Now I already have AutoPilot, so this might make sense. And given this seems to be a key-value pair, I am guessing there will be other things that Tesla would add over time to up-sell.

{
    "autopilot": false
}

The final new API is related to energy sites, and something I of course don’t have or have an interest, but sharing here if someone does care. 🙂

"CALENDAR_HISTORY_DATA": {
    "TYPE": "GET",
    "URI": "api/1/energy_sites/{site_id}/calendar_history",
    "AUTH": true
  }

I am not publishing the full API here as there aren’t significant changes. You of course can see the older post which has the details.

npm install blues – npm ERR! Error: Method Not Allowed

This is a output of a few frustrating hours (spanning over a few days – as and when I can get time), and finally got it fixed and working. Hopefully it might help someone who is also dealing with npm blues.

When NodeJS and npm works, its awesome. But when it borks, it is worst than my code or so it seems :).

Been playing with a few things and wanting to get a dashboard going with Grafana (and InfluxBD as a time-series DB). But some of the installation was failing and for the life of me, could not figure out why and how. Clean image install and downgrading to the previous stable version also didn’t help.

One example of npm failing miserably was the “Error: Method not Allowed” which is not very helpful. Here is an example of what I was seeing:

root@pi-server:/var/lib/grafana/plugins/grafana-trackmap-panel# npm install
(node:4538) [DEP0022] DeprecationWarning: os.tmpDir() is deprecated. Use os.tmpdir() instead.
npm ERR! Error: Method Not Allowed
npm ERR!     at errorResponse (/usr/share/npm/lib/cache/add-named.js:260:10)
npm ERR!     at /usr/share/npm/lib/cache/add-named.js:203:12
npm ERR!     at saved (/usr/share/npm/node_modules/npm-registry-client/lib/get.js:167:7)
npm ERR!     at FSReqWrap.oncomplete (fs.js:135:15)
npm ERR! If you need help, you may report this *entire* log,
npm ERR! including the npm and node versions, at:
npm ERR!     <http://github.com/npm/npm/issues>

npm ERR! System Linux 4.19.57-v7+
npm ERR! command "/usr/bin/node" "/usr/bin/npm" "install"
npm ERR! cwd /var/lib/grafana/plugins/grafana-trackmap-panel
npm ERR! node -v v8.11.1
npm ERR! npm -v 1.4.21
npm ERR! code E405
npm ERR!
npm ERR! Additional logging details can be found in:
npm ERR!     /var/lib/grafana/plugins/grafana-trackmap-panel/npm-debug.log
npm ERR! not ok code 0
root@pi-server:/var/lib/grafana/plugins/grafana-trackmap-panel#

Again, like I said not very helpful. But I finally got to be able to fix it and move on. And here is what worked for me, and it seems like in the OS image, there was a corrupted files, at some level. In most cases you need root access.

Step 1: – Remove and clean up NodeJS.

sudo apt-get remove nodejs nodejs-legacy nodered

Step 2: Get the latest stable source.

curl -sL https://deb.nodesource.com/setup_$NODE_STABLE_BRANCH | sudo -E bash -
sudo apt-get install -y nodejs
npm install -g npm@latest\

I also noticed sometimes the commands above don’t work. If that is the case then then try the following, to get the latest.

curl -sL https://deb.nodesource.com/setup_9.x | sudo -E bash -
sudo apt-get install -y nodejs
npm install -g npm@latest

And based on your dependencies, v9 might not work and you need v8 then you change the first line as following Or for the latest:

curl -sL https://deb.nodesource.com/setup_8.x | sudo -E bash -
sudo apt-get install -y nodejs
npm install -g npm@latest

And finally in the end install and start.

npm install &amp;&amp; npm start

And if you do need to check for the update and get the latest, then try:

sudo npm install -g npm@latest

ML Algorithms

Sometimes one needs a quick snapshot of what are the options to think through and I really like this for that.

Machine Learning Algorithms
Machine Learning Algorithms

Geek Haiku 3 – Streaming Chaos

Rain drops as I dive,
into packet stream; Chaos.
Malicious patterns.

#Haiku #GeekHaiku

Atom

Never trust an atom, they make up everything. 🤓

#GeekyJokes

Programming

A key virtue of a programmer is laziness. As an example it is what inspires me to automate my home to the point where I don’t have to lift a finger to switch on the light. Removing friction from a system is a anesthetic joy. The drug of efficiency, feels really good.

I still write code and people get surprised by that sometimes – maybe it’s the quality of the code 🤓.

Tesla REST APIs v3.8.2

It has been a while since I played with the various Tesla endpoint (APIs) – been too busy and haven’t had the time. I de-compiled the Tesla app and noticed a few new things in there – or at least new to me.

The following are the ones which seem new and stand out. How exactly some of these are used, can only be one’s guess, but I can certainly infer a few things from this.

  • VEHICLE_DATA_LEGACY – So this seems to be the ‘old’ end point, hence the legacy. The new endpoint is now at ‘VEHICLE_DATA’ which seems to return a combined (some) vehicle information, and, consolidate data state of the vehicle. This seems to be cleaner than the earlier version where it was too isolated and multiple calls.
  • NEARBY_CHARGING_SITES – The name says it all – returns a list of Tesla chargers close by (both superchargers, and destination chargers).
  • Media – there are a few media controls that are outlined below. I think these were part of earlier updates when a passenger could control the media playback from their phone. Most of the names are self explanatory and I skipped outlining them below.
    • MEDIA_NEXT_TRACK and MEDIA_PREVIOUS_TRACK – plays the next and previous track respectively.
    • MEDIA_NEXT_FAVORITE and MEDIA_PREVIOUS_FAVORITE – This skips to the next / previous favourite station (different from the track).
  • DEACTIVATE_DEVICE_TOKEN – This is new but I am not sure how this is different from REVOKE_AUTH_TOKEN. What kind of devices is this looking to revoke? AFAIK, it doesn’t seem to be related to the Powerwall.
  • ROADSIDE_ASSISTANCE_DATA – Intrigued seeing this and not sure what data it is sending (need to spend more time writing code to examine the output of the API). I wonder if this is related to the ETA details that might be pushed out (see Elon’s tweet).
  • SET_SENTRY_MODE – As the name suggests, this toggles Sentry mode for the car.
  • Software updates (from the phone) – as expected a couple of API’s to start and cancel software updates – SCHEDULE_SOFTWARE_UPDATE, CANCEL_SOFTWARE_UPDATE
  • REMOTE_SEAT_HEATER_REQUEST – Switching on the seat heating in the car. I presume there will be parameters on which seat, and the setting for each of the seats.
  • REFERRAL_DATA – I would be interested to see what this shows and how it is changing on the backend given that Tesla can’t seem to make up their mind on how to run this and keep changing it adhoc.
  • Message Center – there are a bunch of API’s that are around message center and I wonder what that exactly means. Is it messages in the app (you know, the Inbox that you have seen), or is it something new coming out on the screen in the car. (e.g. MESSAGE_CENTER_MESSAGE, MESSAGE_CENTER_MESSAGE_ACTION_UPDATE, etc.

I have the full output pasted below for you to have a look . This is as of v3.8.2 and it includes not just the car, but the powerwall, and the charging sites (both destination and superchargers).

{
  "AUTHENTICATE": {
    "TYPE": "POST",
    "URI": "oauth/token",
    "AUTH": false
  },
  "REVOKE_AUTH_TOKEN": {
    "TYPE": "POST",
    "URI": "oauth/revoke",
    "AUTH": true
  },
  "PRODUCT_LIST": {
    "TYPE": "GET",
    "URI": "api/1/products",
    "AUTH": true
  },
  "VEHICLE_LIST": {
    "TYPE": "GET",
    "URI": "api/1/vehicles",
    "AUTH": true
  },
  "VEHICLE_SUMMARY": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}",
    "AUTH": true
  },
  "VEHICLE_DATA_LEGACY": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/data",
    "AUTH": true
  },
  "VEHICLE_DATA": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/vehicle_data",
    "AUTH": true
  },
  "NEARBY_CHARGING_SITES": {
    "TYPE": "GET",
    "URI": "api/1/vehicles/{vehicle_id}/nearby_charging_sites",
    "AUTH": true
  },
  "WAKE_UP": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/wake_up",
    "AUTH": true
  },
  "UNLOCK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/door_unlock",
    "AUTH": true
  },
  "LOCK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/door_lock",
    "AUTH": true
  },
  "HONK_HORN": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/honk_horn",
    "AUTH": true
  },
  "FLASH_LIGHTS": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/flash_lights",
    "AUTH": true
  },
  "CLIMATE_ON": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/auto_conditioning_start",
    "AUTH": true
  },
  "CLIMATE_OFF": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/auto_conditioning_stop",
    "AUTH": true
  },
  "CHANGE_CLIMATE_TEMPERATURE_SETTING": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/set_temps",
    "AUTH": true
  },
  "CHANGE_CHARGE_LIMIT": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/set_charge_limit",
    "AUTH": true
  },
  "CHANGE_SUNROOF_STATE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/sun_roof_control",
    "AUTH": true
  },
  "ACTUATE_TRUNK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/actuate_trunk",
    "AUTH": true
  },
  "REMOTE_START": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/remote_start_drive",
    "AUTH": true
  },
  "CHARGE_PORT_DOOR_OPEN": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/charge_port_door_open",
    "AUTH": true
  },
  "CHARGE_PORT_DOOR_CLOSE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/charge_port_door_close",
    "AUTH": true
  },
  "START_CHARGE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/charge_start",
    "AUTH": true
  },
  "STOP_CHARGE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/charge_stop",
    "AUTH": true
  },
  "MEDIA_TOGGLE_PLAYBACK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_toggle_playback",
    "AUTH": true
  },
  "MEDIA_NEXT_TRACK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_next_track",
    "AUTH": true
  },
  "MEDIA_PREVIOUS_TRACK": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_prev_track",
    "AUTH": true
  },
  "MEDIA_NEXT_FAVORITE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_next_fav",
    "AUTH": true
  },
  "MEDIA_PREVIOUS_FAVORITE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_prev_fav",
    "AUTH": true
  },
  "MEDIA_VOLUME_UP": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_volume_up",
    "AUTH": true
  },
  "MEDIA_VOLUME_DOWN": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/media_volume_down",
    "AUTH": true
  },
  "SEND_LOG": {
    "TYPE": "POST",
    "URI": "api/1/logs",
    "AUTH": true
  },
  "RETRIEVE_NOTIFICATION_PREFERENCES": {
    "TYPE": "GET",
    "URI": "api/1/notification_preferences",
    "AUTH": true
  },
  "SEND_NOTIFICATION_PREFERENCES": {
    "TYPE": "POST",
    "URI": "api/1/notification_preferences",
    "AUTH": true
  },
  "RETRIEVE_NOTIFICATION_SUBSCRIPTION_PREFERENCES": {
    "TYPE": "GET",
    "URI": "api/1/vehicle_subscriptions",
    "AUTH": true
  },
  "SEND_NOTIFICATION_SUBSCRIPTION_PREFERENCES": {
    "TYPE": "POST",
    "URI": "api/1/vehicle_subscriptions",
    "AUTH": true
  },
  "DEACTIVATE_DEVICE_TOKEN": {
    "TYPE": "POST",
    "URI": "api/1/device/{device_token}/deactivate",
    "AUTH": true
  },
  "CALENDAR_SYNC": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/upcoming_calendar_entries",
    "AUTH": true
  },
  "SET_VALET_MODE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/set_valet_mode",
    "AUTH": true
  },
  "RESET_VALET_PIN": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/reset_valet_pin",
    "AUTH": true
  },
  "SPEED_LIMIT_ACTIVATE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/speed_limit_activate",
    "AUTH": true
  },
  "SPEED_LIMIT_DEACTIVATE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/speed_limit_deactivate",
    "AUTH": true
  },
  "SPEED_LIMIT_SET_LIMIT": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/speed_limit_set_limit",
    "AUTH": true
  },
  "SPEED_LIMIT_CLEAR_PIN": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/speed_limit_clear_pin",
    "AUTH": true
  },
  "SCHEDULE_SOFTWARE_UPDATE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/schedule_software_update",
    "AUTH": true
  },
  "CANCEL_SOFTWARE_UPDATE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/cancel_software_update",
    "AUTH": true
  },
  "SET_SENTRY_MODE": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/set_sentry_mode",
    "AUTH": true
  },
  "POWERWALL_ORDER_SESSION_DATA": {
    "TYPE": "GET",
    "URI": "api/1/users/powerwall_order_entry_data",
    "AUTH": true
  },
  "POWERWALL_ORDER_PAGE": {
    "TYPE": "GET",
    "URI": "powerwall_order_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "ONBOARDING_EXPERIENCE": {
    "TYPE": "GET",
    "URI": "api/1/users/onboarding_data",
    "AUTH": true
  },
  "ONBOARDING_EXPERIENCE_PAGE": {
    "TYPE": "GET",
    "URI": "onboarding_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "SERVICE_SELF_SCHEDULING_ELIGIBILITY": {
    "TYPE": "GET",
    "URI": "api/1/users/service_scheduling_data",
    "AUTH": true
  },
  "SERVICE_SELF_SCHEDULING_PAGE": {
    "TYPE": "GET",
    "URI": "service_scheduling_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "REFERRAL_DATA": {
    "TYPE": "GET",
    "URI": "api/1/users/referral_data",
    "AUTH": true
  },
  "REFERRAL_PAGE": {
    "TYPE": "GET",
    "URI": "referral_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "ROADSIDE_ASSISTANCE_DATA": {
    "TYPE": "GET",
    "URI": "api/1/users/roadside_assistance_data",
    "AUTH": true
  },
  "ROADSIDE_ASSISTANCE_PAGE": {
    "TYPE": "GET",
    "URI": "roadside_assistance_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "MESSAGE_CENTER_MESSAGE_LIST": {
    "TYPE": "GET",
    "URI": "api/1/messages",
    "AUTH": true
  },
  "MESSAGE_CENTER_MESSAGE": {
    "TYPE": "GET",
    "URI": "api/1/messages/{message_id}",
    "AUTH": true
  },
  "MESSAGE_CENTER_COUNTS": {
    "TYPE": "GET",
    "URI": "api/1/messages/count",
    "AUTH": true
  },
  "MESSAGE_CENTER_MESSAGE_ACTION_UPDATE": {
    "TYPE": "POST",
    "URI": "api/1/messages/{message_id}/actions",
    "AUTH": true
  },
  "MESSAGE_CENTER_CTA_PAGE": {
    "TYPE": "GET",
    "URI": "messages_cta_page",
    "AUTH": true,
    "CONTENT": "HTML"
  },
  "AUTH_COMMAND_TOKEN": {
    "TYPE": "POST",
    "URI": "api/1/users/command_token",
    "AUTH": true
  },
  "SEND_DEVICE_KEY": {
    "TYPE": "POST",
    "URI": "api/1/users/keys",
    "AUTH": true
  },
  "DIAGNOSTICS_ENTITLEMENTS": {
    "TYPE": "GET",
    "URI": "api/1/diagnostics",
    "AUTH": true
  },
  "SEND_DIAGNOSTICS": {
    "TYPE": "POST",
    "URI": "api/1/diagnostics",
    "AUTH": true
  },
  "BATTERY_SUMMARY": {
    "TYPE": "GET",
    "URI": "api/1/powerwalls/{battery_id}/status",
    "AUTH": true
  },
  "BATTERY_DATA": {
    "TYPE": "GET",
    "URI": "api/1/powerwalls/{battery_id}",
    "AUTH": true
  },
  "BATTERY_POWER_TIMESERIES_DATA": {
    "TYPE": "GET",
    "URI": "api/1/powerwalls/{battery_id}/powerhistory",
    "AUTH": true
  },
  "BATTERY_ENERGY_TIMESERIES_DATA": {
    "TYPE": "GET",
    "URI": "api/1/powerwalls/{battery_id}/energyhistory",
    "AUTH": true
  },
  "BATTERY_BACKUP_RESERVE": {
    "TYPE": "POST",
    "URI": "api/1/powerwalls/{battery_id}/backup",
    "AUTH": true
  },
  "BATTERY_SITE_NAME": {
    "TYPE": "POST",
    "URI": "api/1/powerwalls/{battery_id}/site_name",
    "AUTH": true
  },
  "BATTERY_OPERATION_MODE": {
    "TYPE": "POST",
    "URI": "api/1/powerwalls/{battery_id}/operation",
    "AUTH": true
  },
  "SITE_SUMMARY": {
    "TYPE": "GET",
    "URI": "api/1/energy_sites/{site_id}/status",
    "AUTH": true
  },
  "SITE_DATA": {
    "TYPE": "GET",
    "URI": "api/1/energy_sites/{site_id}/live_status",
    "AUTH": true
  },
  "SITE_CONFIG": {
    "TYPE": "GET",
    "URI": "api/1/energy_sites/{site_id}/site_info",
    "AUTH": true
  },
  "HISTORY_DATA": {
    "TYPE": "GET",
    "URI": "api/1/energy_sites/{site_id}/history",
    "AUTH": true
  },
  "BACKUP_RESERVE": {
    "TYPE": "POST",
    "URI": "api/1/energy_sites/{site_id}/backup",
    "AUTH": true
  },
  "SITE_NAME": {
    "TYPE": "POST",
    "URI": "api/1/energy_sites/{site_id}/site_name",
    "AUTH": true
  },
  "OPERATION_MODE": {
    "TYPE": "POST",
    "URI": "api/1/energy_sites/{site_id}/operation",
    "AUTH": true
  },
  "TIME_OF_USE_SETTINGS": {
    "TYPE": "POST",
    "URI": "api/1/energy_sites/{site_id}/time_of_use_settings",
    "AUTH": true
  },
  "STORM_MODE_SETTINGS": {
    "TYPE": "POST",
    "URI": "api/1/energy_sites/{site_id}/storm_mode",
    "AUTH": true
  },
  "SEND_NOTIFICATION_CONFIRMATION": {
    "TYPE": "POST",
    "URI": "api/1/notification_confirmations",
    "AUTH": true
  },
  "NAVIGATION_REQUEST": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/navigation_request",
    "AUTH": true
  },
  "REMOTE_SEAT_HEATER_REQUEST": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/remote_seat_heater_request",
    "AUTH": true
  },
  "REMOTE_STEERING_WHEEL_HEATER_REQUEST": {
    "TYPE": "POST",
    "URI": "api/1/vehicles/{vehicle_id}/command/remote_steering_wheel_heater_request",
    "AUTH": true
  }
}

Getting DonkeyCar working on a Mac

I have been playing with a #selfdriving car for a while, and that is super exciting. From a #AI and #ML perspective it is small scale, but allows one to exploit all aspects of the tech stack and also appreciate the limitations of not only the software, but also the hardware.

With this You run a NN on a raspberry pi that uses TensorFlow, and Keras and runs inference on the edge. The pi doesn’t have enough power to train, so you need to do that on a beefier machine and then deploy the model back to run this.

Now, I didn’t have any issues in getting this running on Windows, but to get it on a Mac was a different story. The documentation is there that outlines all the steps, and even if you follow it to the T, it breaks right in the end.

When I tried to create a car, using a createcar command (this essentially creates the buckets, where you would save the training images, and the model, and the configuration of the car when you connect to it from your machine). The actual file paths would probably be different for you but, essentially it is the same thing.

(donkey) AMAC02XN1T9JGH5:donkeycar amit.bahree$ donkey createcar ~/mycar
Traceback (most recent call last):
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 660, in _build_master
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 968, in require
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 859, in resolve
pkg_resources.ContextualVersionConflict: (imageio 2.4.1 (/anaconda3/envs/donkey/lib/python3.6/site-packages), Requirement.parse('imageio<3.0,>=2.5'), {'moviepy'})

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/anaconda3/envs/donkey/bin/donkey", line 6, in <module>
    from pkg_resources import load_entry_point
  File "<frozen importlib._bootstrap>", line 961, in _find_and_load
  File "<frozen importlib._bootstrap>", line 950, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 646, in _load_unlocked
  File "<frozen importlib._bootstrap>", line 616, in _load_backward_compatible
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 2985, in <module>
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 2971, in _call_aside
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 2998, in _initialize_master_working_set
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 662, in _build_master
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 675, in _build_from_requirements
  File "/anaconda3/envs/donkey/lib/python3.6/site-packages/setuptools-27.2.0-py3.6.egg/pkg_resources/__init__.py", line 854, in resolve
pkg_resources.DistributionNotFound: The 'imageio<3.0,>=2.5' distribution was not found and is required by moviepy

The key here to focus is on the last lines on both of those blocks of code – the main thing causing the issue is MoviePy (see highlighted lines above).

MoviePy is a Python library for video editing: cutting, concatenations, title insertions, video compositing (a.k.a. non-linear editing), video processing, and creation of custom effects.

It seems like when you go through the steps – clone the repo, setup anaconda, install tensorflow and get the car configured – there is a mismatch in the MoviePy dependencies which it doesn’t like. The way to fix the issue is outlined below.

Skip MoviePy

MoviePy is something you don’t need to use right away but later when trying to make a movie (using the makemovie command – which allows you to create a movie file from the images in a Tub.); this is not essential. To do this, the easiest way is to remove (or my suggestion it to comment) out the moviepy dependency from the setup.py file.

This should be line 33 in the setup.py file that you will find in the same folder where you cloned the git repo. As an example the updated file is below, where the moviepy dependency is commented out (see highlighted). And once you save this and go about creating the car, it should work. Of course you cannot use the makemovie option later.

from setuptools import setup, find_packages

import os

with open("README.md", "r") as fh:
    long_description = fh.read()


setup(name='donkeycar',
      version='2.5.7',
      description='Self driving library for python.',
      long_description=long_description,
      long_description_content_type="text/markdown",
      url='https://github.com/autorope/donkeycar',
      download_url='https://github.com/autorope/donkeycar/archive/2.1.5.tar.gz',
      author='Will Roscoe',
      author_email='wroscoe@gmail.com',
      license='MIT',
      entry_points={
          'console_scripts': [
              'donkey=donkeycar.management.base:execute_from_command_line',
          ],
      },
      install_requires=['numpy',
                        'pillow',
                        'docopt',
                        'tornado==4.5.3',
                        'requests',
                        'h5py',
                        'python-socketio',
                        'flask',
                        'eventlet',
                        #'moviepy',
                        'pandas',
                        ],

      extras_require={
                      'tf': ['tensorflow>=1.9.0'],
                      'tf_gpu': ['tensorflow-gpu>=1.9.0'],
                      'pi': [
                          'picamera',
                          'Adafruit_PCA9685',
                          ],
                      'dev': [
                          'pytest',
                          'pytest-cov',
                          'responses'
                          ],
                      'ci': ['codecov']
                  },

      include_package_data=True,

      classifiers=[
          # How mature is this project? Common values are
          #   3 - Alpha
          #   4 - Beta
          #   5 - Production/Stable
          'Development Status :: 3 - Alpha',

          # Indicate who your project is intended for
          'Intended Audience :: Developers',
          'Topic :: Scientific/Engineering :: Artificial Intelligence',

          # Pick your license as you wish (should match "license" above)
          'License :: OSI Approved :: MIT License',

          # Specify the Python versions you support here. In particular, ensure
          # that you indicate whether you support Python 2, Python 3 or both.

          'Programming Language :: Python :: 3.5',
          'Programming Language :: Python :: 3.6',
      ],
      keywords='selfdriving cars donkeycar diyrobocars',

      packages=find_packages(exclude=(['tests', 'docs', 'site', 'env'])),
      )

Once you have saved the setup.py file, you need to run the installation again with the following command and then run the create car command. Both of these are outlined below.

pip install -e .
donkey createcar ~/mycar

Once you run these, then you should see the successful installation as shown by the output below. Note – your output might be a little different depending on the conda state of packages

(donkey) AMAC02XN1T9JGH5:donkeycar amit.bahree$ pip install -e .
Obtaining file:///Users/amit.bahree/CloudStation/Documents/Code/donkeycar
Requirement already satisfied: numpy in /anaconda3/envs/donkey/lib/python3.6/site-packages (from donkeycar==2.5.7) (1.14.5)
Requirement already satisfied: pillow in /anaconda3/envs/donkey/lib/python3.6/site-packages (from donkeycar==2.5.7) (4.2.1)
Requirement already satisfied: docopt in /anaconda3/envs/donkey/lib/python3.6/site-packages (from donkeycar==2.5.7) (0.6.2)
Collecting tornado==4.5.3 (from donkeycar==2.5.7)
Requirement already satisfied: requests in /anaconda3/envs/donkey/lib/python3.6/site-packages (from donkeycar==2.5.7) (2.18.4)
Requirement already satisfied: h5py in /anaconda3/envs/donkey/lib/python3.6/site-packages (from donkeycar==2.5.7) (2.7.1)
Collecting python-socketio (from donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/a1/71/118e4b7fb453d7095d6863f4b783dbaa57109af4bc2380300649c8942d61/python_socketio-4.0.0-py2.py3-none-any.whl
Collecting flask (from donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/7f/e7/08578774ed4536d3242b14dacb4696386634607af824ea997202cd0edb4b/Flask-1.0.2-py2.py3-none-any.whl
Collecting eventlet (from donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/86/7e/96e1412f96eeb2f2eca9342dcc4d5bc9305880a448b603b0a8e54439b71c/eventlet-0.24.1-py2.py3-none-any.whl
Collecting pandas (from donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/99/12/bf4c58eea94cea4f91ff931f284146337814fb8546e6eb0b52584446fd52/pandas-0.24.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Requirement already satisfied: olefile in /anaconda3/envs/donkey/lib/python3.6/site-packages (from pillow->donkeycar==2.5.7) (0.44)
Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /anaconda3/envs/donkey/lib/python3.6/site-packages (from requests->donkeycar==2.5.7) (3.0.4)
Requirement already satisfied: certifi>=2017.4.17 in /anaconda3/envs/donkey/lib/python3.6/site-packages (from requests->donkeycar==2.5.7) (2017.7.27.1)
Requirement already satisfied: idna<2.7,>=2.5 in /anaconda3/envs/donkey/lib/python3.6/site-packages (from requests->donkeycar==2.5.7) (2.6)
Requirement already satisfied: urllib3<1.23,>=1.21.1 in /anaconda3/envs/donkey/lib/python3.6/site-packages (from requests->donkeycar==2.5.7) (1.22)
Requirement already satisfied: six in /anaconda3/envs/donkey/lib/python3.6/site-packages (from h5py->donkeycar==2.5.7) (1.10.0)
Collecting python-engineio>=3.2.0 (from python-socketio->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/95/91/d083bd7b5d408af53633377dfbf87bf181236c8916d36213388b12eaa999/python_engineio-3.4.3-py2.py3-none-any.whl
Collecting click>=5.1 (from flask->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/fa/37/45185cb5abbc30d7257104c434fe0b07e5a195a6847506c074527aa599ec/Click-7.0-py2.py3-none-any.whl
Collecting itsdangerous>=0.24 (from flask->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/76/ae/44b03b253d6fade317f32c24d100b3b35c2239807046a4c953c7b89fa49e/itsdangerous-1.1.0-py2.py3-none-any.whl
Collecting Werkzeug>=0.14 (from flask->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/20/c4/12e3e56473e52375aa29c4764e70d1b8f3efa6682bef8d0aae04fe335243/Werkzeug-0.14.1-py2.py3-none-any.whl
Collecting Jinja2>=2.10 (from flask->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/7f/ff/ae64bacdfc95f27a016a7bed8e8686763ba4d277a78ca76f32659220a731/Jinja2-2.10-py2.py3-none-any.whl
Collecting monotonic>=1.4 (from eventlet->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/ac/aa/063eca6a416f397bd99552c534c6d11d57f58f2e94c14780f3bbf818c4cf/monotonic-1.5-py2.py3-none-any.whl
Collecting greenlet>=0.3 (from eventlet->donkeycar==2.5.7)
Collecting dnspython>=1.15.0 (from eventlet->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/ec/d3/3aa0e7213ef72b8585747aa0e271a9523e713813b9a20177ebe1e939deb0/dnspython-1.16.0-py2.py3-none-any.whl
Collecting pytz>=2011k (from pandas->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/61/28/1d3920e4d1d50b19bc5d24398a7cd85cc7b9a75a490570d5a30c57622d34/pytz-2018.9-py2.py3-none-any.whl
Collecting python-dateutil>=2.5.0 (from pandas->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/41/17/c62faccbfbd163c7f57f3844689e3a78bae1f403648a6afb1d0866d87fbb/python_dateutil-2.8.0-py2.py3-none-any.whl
Collecting MarkupSafe>=0.23 (from Jinja2>=2.10->flask->donkeycar==2.5.7)
  Using cached https://files.pythonhosted.org/packages/f0/00/a6aea33f5598b080b86d6b6d1214b51afe3ffa6100b902d5aa465080083f/MarkupSafe-1.1.1-cp36-cp36m-macosx_10_6_intel.whl
Installing collected packages: tornado, python-engineio, python-socketio, click, itsdangerous, Werkzeug, MarkupSafe, Jinja2, flask, monotonic, greenlet, dnspython, eventlet, pytz, python-dateutil, pandas, donkeycar
  Found existing installation: tornado 4.5.1
    Uninstalling tornado-4.5.1:
      Successfully uninstalled tornado-4.5.1
  Found existing installation: Werkzeug 0.12.2
    Uninstalling Werkzeug-0.12.2:
      Successfully uninstalled Werkzeug-0.12.2
  Running setup.py develop for donkeycar
Successfully installed Jinja2-2.10 MarkupSafe-1.1.1 Werkzeug-0.14.1 click-7.0 dnspython-1.16.0 donkeycar eventlet-0.24.1 flask-1.0.2 greenlet-0.4.15 itsdangerous-1.1.0 monotonic-1.5 pandas-0.24.1 python-dateutil-2.8.0 python-engineio-3.4.3 python-socketio-4.0.0 pytz-2018.9 tornado-4.5.3

And when I run the createcar, you can see it worked as expected. In my case creating the ‘mycar’ folder in my home directory. Of course you can choose this wherever you prefer.

(donkey) AMAC02XN1T9JGH5:donkeycar amit.bahree$ donkey createcar ~/mycar
using donkey version: 2.5.7 ...
Creating car folder: /Users/amit.bahree/mycar
making dir  /Users/amit.bahree/mycar
Creating data &amp; model folders.
making dir  /Users/amit.bahree/mycar/models
making dir  /Users/amit.bahree/mycar/data
making dir  /Users/amit.bahree/mycar/logs
Copying car application template: donkey2
Copying car config defaults. Adjust these before starting your car.
Donkey setup complete.

It is interesting to see this is more stable on Windows, than on a Mac. Also, one last thing to leave you with – when I first ran the installation, the hint that someone was wrong was in the output, but I didn’t pay too much attention to it. See the red line highlighted in the output below.

moviepy failure - donkeycar installation
moviepy failure – donkeycar installation

Don’t know at this time on what the solution for moviepy is to get this sorted – luckily its not a big deal at the moment.