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What Exactly Triggers The "Automagic" Logging Of The Model And Weights? I'Ve Pulled My Simple Test Project Out Of Jupyter Lab And The Same Problem Still Exists, So It Isn'T A Jupyter Lab Issues. A Few Things Log, But Never The Model

What exactly triggers the "automagic" logging of the model and weights? I've pulled my simple test project out of jupyter lab and the same problem still exists, so it isn't a jupyter lab issues. A few things log, but never the model

  
  
Posted one year ago
Votes Newest

Answers 16


torch.save(model.state_dict(), " http://test_cnn.pt ")

  
  
Posted one year ago

Hi RoundMole15

What exactly triggers the "automagic" logging of the model and weights?

framework save call, for example torch.save or joblib.save

I've pulled my simple test project out of jupyter lab and the same problem still exists,

What is "the same problem" ?

  
  
Posted one year ago

You should alter the name (or else the model will be overwritten)

  
  
Posted one year ago

"the same problem" is I posted above but I was using jupyter lab, I simplified hoping the problem was with jupyter

  
  
Posted one year ago

RoundMole15 how does the Task.init look like?

  
  
Posted one year ago

AgitatedDove14 other things are logging, I'm using task.connect to log hyperparameters logger to log the loss

  
  
Posted one year ago

from clearml import Task
task = Task.init(project_name='ClearML test', task_name='test 10')

  
  
Posted one year ago

Hi RoundMole15 ! Are you able to see a model logged when you run this simple example?
` from clearml import Task
import torch.nn.functional as F
import torch.nn as nn
import torch
class TheModelClass(nn.Module):
def init(self):
super(TheModelClass, self).init()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 5 * 5, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 10)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, 16 * 5 * 5)
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x

Initialize model

model = TheModelClass()
task = Task.init(project_name='ClearML test', task_name='test 10')
torch.save(model.state_dict(), "test_cnn.pt") `

  
  
Posted one year ago

it's as simple as yours,-- class myCNN(nn.Module):

  
  
Posted one year ago

now that I know the logging is working, it must be something dumb I've overlooked in my code

  
  
Posted one year ago

thanks for your help!

  
  
Posted one year ago

AgitatedDove14 quick question, do I need to alter the name of the dict file I save with torch.save for each run? Or is clearml able to version it out?

  
  
Posted one year ago

this is in the code but still no logged model

  
  
Posted one year ago

hmmm, yes that worked

  
  
Posted one year ago

how does your model look like?

  
  
Posted one year ago

You're welcome! Feel free to write here again if you believe this might be a ClearML problem

  
  
Posted one year ago
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16 Answers
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