So far I have taken one mnist image, and done the following:

` from PIL import Image
import numpy as np

def preprocess(img, format, dtype, h, w, scaling):

sample_img = img.convert('L')


resized_img = sample_img.resize((1, w*h), Image.BILINEAR)
resized = np.array(resized_img)
resized = resized.astype(dtype)

return resized

png img file

img = Image.open('./7.png')

preprocessed img, FP32 formated numpy array

img = preprocess(img, format, "float32", 28, 28, None)

...

where should I look for this folder?
I am talking about serving

logger.report_media( title=name_title, series="Nan", iteration=0, local_path=fig_nan, delete_after_upload=delete_after_upload, ) clearml_task.upload_artifact( name=name_title, artifact_object=fig_nan, wait_on_upload=True, )

Hi CostlyOstrich36
I added this instruction at the very end of my postprocess function
shutil.rmtree("~/.clearml")

ok, thanks Jake!

Sent it to you via DM!

Same thing SuccessfulKoala55 😞

I have this inside my pipeline defined with decorator

{"detail":"Error processing request: [Errno 2] No such file or directory: '~/.clearml'"}

(base) emilio@unicorn:~$ docker version Client: Docker Engine - Community Version: 19.03.13 API version: 1.40 Go version: go1.13.15 Git commit: 4484c46d9d Built: Wed Sep 16 17:02:36 2020 OS/Arch: linux/amd64 Experimental: false (base) emilio@unicorn:~$ docker-compose --version docker-compose version 1.17.1, build unknown

Yeah, that would be nice!

i'm just interested in actually running a prediction with the serving engine and all

web_server:

well, what are the types of input expected? is parent_datasets a list of names or IDs?

some documentation for understanding the parameters, flags, options etc.
I want my serving controller to go into a particular project instead of the default DevOps, for example
Other things might be programatically adding endpoints instead of using cli (this is because I potentially have hundreds of models to serve so I can't do this manually)

my server isn't the latest, though..

SuccessfulKoala55 I can't get it to work... I tried using the pip conf locally and it works, but the agent doesn't seem to be able to install the package

yep, setting it to -1 is still caching envs..

any 7.6.2-x if I'm not wrong

can you elaborate a bit on the token side? i'm not sure exactly what would be a bad practice here

using clearML agent

it says method not allowed when i try to access that url

right, and why can't a particular version be found? how it does it try to find python versions?

Is this a possible future feature? I have used cometML before and they have this. I'm not sure how they do it though...

Hey AgitatedDove14 , thanks for the answer. What does that mean? In any case I think it would be a nice to have feature.

Ah, so you're saying I can write a callback for stuff like train_loss , val_loss , etc.

Absolutely, I could try but I'm not sure what it entails...

Hey AgitatedDove14 , did you get a chance to look at this?

And then you'll hook it