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

Ok gotchu. I'll do that as soon as I can.

ok, thanks Jake!

I think the issue is that the host is not trusted... it looks like it looks into the index

I tested 0.17.2 and 0.17.4

And then you'll hook it

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)

...

Because sometimes it clones a cached version of a private repository, instead of cloning the requested version

Thanks!!

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

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

Not sure why it tries to establish some http connection, or why it's / ...

nevermind! I have figured out my issue

platform: "tensorflow_savedmodel" input [ { name: "dense_input" data_type: TYPE_FP32 dims: [-1, 784] } ] output [ { name: "activation_2" data_type: TYPE_FP32 dims: [-1, 10] } ]

fp32 seems to be floating point 32 so my preprocessing seems wrong

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

I have done this but I remember someone once told me this could be an issue... Or I could be misremembering. I just wanted to double check

i'm not sure how to double check this is the case when it happens... usually we have all requirements specified with git repo

i'm guessing the cleanup_period_in_days can only actually run every day or whatever if the script is enqueued to services

if i enqueue the script to the services queue but run_as_service is false, what happens?

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

SuccessfulKoala55 Yup!

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

I think it's still caching environments... I keep deleting the caches (pip, vcs, venvs-*) and running an experiment. it re-creates all these folders and even prints

Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20.0->clearml==1.6.4->prediction-service-utilities==0.1.0) (3.4)
Requirement already satisfied: charset-normalizer<4,>=2 in /root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages (from requests>=2.20.0->clearml==1.6....

@<1523701205467926528:profile|AgitatedDove14> any ideas?

Hi SuccessfulKoala55 , do you have an update on this?

hiya Jake, how do I inject this with the extra_docker_shell_script setting?

it's from the github issue you sent me but i don't know what the "application" part is or the "NV-InferRequest:...."

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