Month: January 2021

Hello,

I am new to tensorflow and am trying to figure out what I think
should be a rather simple task. I have a model (.pb file) given to
me and I need to use it to markup an image.

I have two classes that the model was trained on: background and
burnish.

From this point on, I have literally no idea what I am doing. I
tried searching online and there is a lot about how to train a
model but I don’t need to do be able to do that.

Any help pointing me in the right direction would be
awesome!

Hey, Very much a beginner with tensorflow, but been enjoying it
so far.

Background: response between 0-200, have 43 variables,
regression type problem, data set is over 200k rows

I’ve built a basic sequential model using Keras, and my loss
and validation loss are ideal – I.e validation loss is slightly
above loss, and it looks as it should.

However my actual loss seems quite high, it is converging around
34 and I’d have liked it to be around 20, now because of the
above I’m not sure if this means my data isn’t actually
predictive?!

I have standardised many variables rather than normalised, I’m
not sure if this would make any difference.

Is there anything I could add you think? I don’t think the
data set is lacking particularly woth the dimensions.

I am have searched a lot of tutorials and courses, most start
with a BERT model or some variation of it. I want to watch/ learn
how a transformer/ attention is trainned from scratch.

I want to try to build a attention/ transformer model for solved
games like chess, (ie I will have generate-able data)

I’m looking at reducing the costs of EfficientNet for a task
that only deals with greyscale data.

To do this, I need to reduce the number of filters across the
network by 1/3rd (RGB -> (B/W)), and train on COCO in
greyscale.

The
TensorFlow 2 Detection Model Zoo has
a link of training configs if you want to train from
scratch.

However, I can’t seem to find how I would edit the architecture
to reduce the number of channels.

I can see there’s an
official definition in Keras, however I’m unsure if this is
what’s used by the config.

If there was some way to load the saved model, and then edit
it’s structure that way, that could work. But I’m unsure if there’s
a better way to do this.

So at this point I’ve managed to get ahold of my checkpoint file
which is of type `DATA-00000-OF-00001` and there is also a similar
one that is of type `INDEX` and this file is significantly smaller
in terms of size. I would like to convert these two into a single
`*.pb` file. Is that possible?

https://reddit-username-generator.herokuapp.com/

Trained on ~400k usernames, this LSTM based approach can
generate pretty realistic looking reddit usernames. You can even
provide a start string like “PM_ME” (warning: lotta profanity).

At first I deployed with TensorFlow.js in React, but to learn
more I rewrote the backend with Flask instead.

Here’s the GitHub: https://github.com/dchen327/reddit-username-generator

Have fun!

Sorry for asking a question that’s not a direct TensorFlow issue
but 2.4 supports the 3000-series GPUs, so a lot of us are waiting
on Anaconda support, and was thinking maybe someone here can
remember how long it took Anaconda to support 2.3 after its
release, to give others an approximate timeframe on 2.4. Thanks.
)

I am trying to get my GPU to train. Gtx 1660 ti, tf 2.4.1, cuda
11.2, python 3.8.7

My NN was taking 15 minutes per epoch on some dummy data so I am
setting up GPU training. At one point I got through 13 epochs
before it got stuck (maybe ran out of memory?). Many github
resolutions later I am stuck at one of two errors:

CUBLAS_STATUS_ALLOC_FAILED CUDNN_STATUS_EXECUTION_FAILED

The only tickets I have found online have been resolved by
setting memory limit or setting “allow_growth” to true. Twice this
has gotten me past the first error, but isnt not working
consistently. Ultimately I end up at the second error either
way.

Has anyone encounter this and not had the widely reported
solution work? Thanks in advance if anyone can help me. Just spent
waaaaay too long trying to get this going and finally am out of
ways to google.