stamps | Course materials for STAMPS @ MBL
kandi X-RAY | stamps Summary
kandi X-RAY | stamps Summary
Amy's course materials for Strategies And Techniques For Analysing Microbial Population Structures (STAMPS) at the Marine Biological Laboratory, 2017. This folder mostly contains materials related to the R tutorial, but some other materials as well.
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QUESTION
I would like to know whether there is a recommended way of measuring execution time in Tensorflow Federated. To be more specific, if one would like to extract the execution time for each client in a certain round, e.g., for each client involved in a FedAvg round, saving the time stamp before the local training starts and the time stamp just before sending back the updates, what is the best (or just correct) strategy to do this? Furthermore, since the clients' code run in parallel, are such a time stamps untruthful (especially considering the hypothesis that different clients may be using differently sized models for local training)?
To be very practical, using tf.timestamp()
at the beginning and at the end of @tf.function
client_update(model, dataset, server_message, client_optimizer)
-- this is probably a simplified signature -- and then subtracting such time stamps is appropriate?
I have the feeling that this is not the right way to do this given that clients run in parallel on the same machine.
Thanks to anyone can help me on that.
...ANSWER
Answered 2021-Jun-15 at 12:01There are multiple potential places to measure execution time, first might be defining very specifically what is the intended measurement.
Measuring the training time of each client as proposed is a great way to get a sense of the variability among clients. This could help identify whether rounds frequently have stragglers. Using
tf.timestamp()
at the beginning and end of theclient_update
function seems reasonable. The question correctly notes that this happens in parallel, summing all of these times would be akin to CPU time.Measuring the time it takes to complete all client training in a round would generally be the maximum of the values above. This might not be true when simulating FL in TFF, as TFF maybe decided to run some number of clients sequentially due to system resources constraints. In practice all of these clients would run in parallel.
Measuring the time it takes to complete a full round (the maximum time it takes to run a client, plus the time it takes for the server to update) could be done by moving the
tf.timestamp
calls to the outer training loop. This would be wrapping the call totrainer.next()
in the snippet on https://www.tensorflow.org/federated. This would be most similar to elapsed real time (wall clock time).
QUESTION
One thing which I have learnt from working with Identity Server is that, out of the box, ASP.NET Core Identity does not play too well with Identity Server. Refer to this question.
ASP.NET Identity contains a way of ejecting users where a particular user's data has changed. This is regulated by the SecurityStamp column of the aspnetuser table. When the stamp changes, the next time the cookie is validated, it fails validation.
This is turned on by default and it is the reason why it does not work well with Identity Server.
You end up with users getting kicked out erratically. And when you expect it to kick users out, it doesn't.
Anyhow, how do you disable this feature of ASP.NET Identity???
There is a column on the UserManager called SupportsUserSecurityStamp.
However, it is a "getter" only and I cannot find any configuration setting for switching that to return false
.
It seems to me that the only way is to derive from the UserManager class and make that property only ever return false
.
That feels like a hack. Especially when you look at the code for that property on Github:
...ANSWER
Answered 2021-Jun-14 at 00:24I turned the SecurityStamp
feature off, as described in the question.
So, I created a class which inherits from the UserManager
class.
Should look something like this:
QUESTION
I'm trying to create a regex expression for use with Notepad++ to look for a specific character anywhere in the line but not capture it while still capturing what I want to find later in the string.
A sample of what I'm looking at is this:
...ANSWER
Answered 2021-Jun-13 at 18:05You can use
QUESTION
The format of the .csv file is as below it has gaps in between as it gets data in packets. I want to plot the data with timestamp on the x-axis and sensor1 on the y-axis using matplotlib in python so is there a possibility.
This is the data in the CSV file so you can see 4 data points received 4 times this is being read at different time stamps. I tried approaching the normal way but it shows a blank plot.
This is the link to the CSV file. https://docs.google.com/spreadsheets/d/17SIabIYYmSogOdeYTzpEwy9s2pZuVO3ghoChSSgGwAg/edit?usp=sharing
...ANSWER
Answered 2021-Jun-08 at 16:46Load the csv with pandas:
QUESTION
I've been learning about how to use git and was very surprised to learn that you can change the timestamps of an old commit. It feels weird to me because I thought a big part of git was to ensure validity. That being, when you look back at commits, you know that what you see is what was done and when.
Consider this scenario: Someone uploads his local git project, which already has several commits in it, to GitHub. This person then adds another collaborator to this project. Can this collaborator tell if any of the time stamps on these existent commits have been edited?
...ANSWER
Answered 2021-Jun-08 at 06:41You cannot determine if the timestamps in a Git commit are accurate or not.
Commits are created on the local computer, so even if someone didn’t use Git tooling to fabricate timestamps, they could simply change their computer’s clock before committing. Or, they could use a modified Git program that writes any timestamp they want.
Once you know the hash of a commit, Git verifies that none of the data reachable from that commit have been modified since the hash was generated. In addition, if you use GPG signing of commits or tags, Git can verify that the signature matches a public key you have. But, Git cannot prove how the commit data itself was created.
QUESTION
So I'm accessing an Siemens LOGO! PLC to extract some data from. I managed to do that with my work partner but we're stuck on how the data is being saved. The data is being timestamped in a dictionary with the output and input bytes from the PLC. But the data comes in a certain order and is timestamped the moment the data is extracted.
Now the problem is that the timestamps and data isn't saved in the same order that the data comes in. Somewhere in the process it makes a mistake (I think), but we can't seem to find it.
Here's the Python Code we use: ...ANSWER
Answered 2021-Jun-07 at 13:29I found out why it was so duplicating the data packets.
Because the dict
data is defined outside the while loop it keeps adding new keys,values to the dict
. The dict
is being wrapped into a json file and keeps getting exponentially increasing.
The dict
data needs to be defined inside the while loop so that it can be reused every time it dumps the dict
into the json.
QUESTION
I have a situation where I have a very large dataframe that has airplane location data with 5 rows per timestamp (see table below for an example of 1 timestamp... 3 of the rows just have dots but imagine they have plane_nums and locations)
...ANSWER
Answered 2021-Jun-03 at 00:07Here's a method to get all your data in one row prior to any calculations. Instead of the lambda function to reshape the data you can have a function that does your calculations.
QUESTION
First, I add a stamp to pdf files used iText7, about drawing's rev date... I get it. Second, if I update the drawings, need to update the stamp information, the simplest, to delete the stamp and add it again. But, I can't get the stamps in pdf.
...ANSWER
Answered 2021-Jun-02 at 11:59According to a comment you added the stamps in question like this:
QUESTION
I have a table which contains a column Start_Timestamp which has time stamp values like 2020-06-02 21:08:37. I would like to create new column which classifies these timestamps into bins of 6hours.
Eg.
Input :
Start_Timestamp 2020-06-02 21:08:37 2020-07-19 01:23:40 2021-11-13 12:08:37Expected Output ( Here each bin is of 6hours width) :
Start_Timestamp Bin 2020-06-02 21:08:37 18H - 24H 2020-07-19 01:23:40 00H - 06H 2021-11-13 12:08:37 12H - 18HI have tried using TIMESERIES but can anyone help to generate output in following format
...ANSWER
Answered 2021-May-27 at 11:16You can simply extract the hour and do some arithmetic:
QUESTION
I have been trying to externally log data to my home server with a little GSM modem and InfluxDB2 HTTP API- it is far away and needs to be external, just checking water levels and other system stuff.
I am struggeling to understand the correct payload and keys to give it in order for it to accept my data.
I am using an ESP32 and the requests module on Micro Python, using MicroPython_ESP32_psRAM_LoBo.
The GSM library I am using makes everything work as if I was connected to Wifi, I am pretty certian that my problem has nothing to do with the GSM side of things.
The system uses InfluxDB2 and Python3 ( Micro Python to be exact )
Current Setup
...ANSWER
Answered 2021-May-27 at 17:24I managed to find a solution after days of searching and trying new things.
Basically I used the mrequests lib ( https://github.com/SpotlightKid/mrequests )
With this I managed to get the whole thing working as expected using the following code - Done in Micropython
I did make a free account with No-IP to set my ISP external IP to a URL, I dont think this has a massive change but it is worth noting. I did try the older methods with this new URL and they still did not work.
Here is the new code with the mrequest lib.
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