how do I check?

Monsieur Martin! 1.3.2

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)

...

But where do you manually set the name of each task in this code? the .component has a name argument you can provide

I am curious about the updates on version 1.0.0, where can I see some info regarding this?
Passing state information from pre to postprocessing and the dynamic preprocessing code thing, for example

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

does this make more sense? SuccessfulKoala55

web_server:

In fact I just did that yesterday. I'll let you know how it goes

yes

Thanks!!

sure. Removing the task.connect(args_) does not fix my situation

ah.. agent was on a different machine..

my script is Aborted with the above error

so it tries to find it under /usr/bin/python/ I assume?

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

sheesh, weird. I don't get the same.

What is the latest rc?

This is a minimal comet example. I'm afraid I don't know what it does under the hood.. There are no callbacks on the metrics tracked in model.fit and yet if you check out your project in the website, your training and validation losses are tracked automatically, live.

https://www.comet.ml/docs/python-sdk/keras/

using clearML agent

And got the same error

instead of, say, the binary the task was launched with

img.tofile('7.binaryimage',format='binary') can this be the 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] } ]

yes, I can see them

i don't know ahahaha

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

but it's been that way for over 1 hour.. I remember I can force the task to wait for the upload. how do i do this?

hi SuccessfulKoala55 ! has the docker compose been updated with this?>

is this a possibility?