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I Want To Save Some Data On My Outputmodel In Order To Make It More Accessible When I'M Using The Model. When I Use

I want to save some data on my OutputModel in order to make it more accessible when I'm using the model. When I use myOuputModel.save_metadata("somekey", "someval", "str") I get failed validation when I try to upload the model.

jsonschema.exceptions.ValidationError: 'model' is a required property     

     'required': ['model', 'metadata'],
     'type': 'object'}

On instance:
    {'metadata': [{'key': 'final_score',
                   'type': 'float',
                   'value': '0.00)'}],
     'replace_metadata': False}

I've tried with both set_metadata and set_all_metadata(replace=False) but still get the same.

Posted 11 months ago
Votes Newest

Answers 4

Hi @<1562973083189383168:profile|GrievingDuck15> , do you have a standalone snippet that reproduces this error?

Posted 11 months ago

import torch
import torchvision
from clearml import Task, OutputModel

scripted_model = torch.jit.script(torchvision.models.resnet18())

task = Task.init(project_name="OutputModelMVE", task_name="Testing shit")

outputmodel = OutputModel(task=task, framework='PyTorch')
outputmodel.update_labels({'Clearml': 0, 'Debug': 1})
outputmodel.set_upload_destination(INSERT DESTINATION)
metadatas = dict(Score=("0.2", "float"),
                SomeField=("SomeField", "str"),
                OtherField=("OtherField", "str"))

for key, (val, type) in metadatas.items():
    outputmodel.set_metadata(key, val, type, )


If you remove lines 17-18 and dont't change the metadtata the upload works.

Posted 11 months ago

Ok, the mistake was staring me in the eye the entire time.

I thought that set_metadata worked on the local output model. But what it actually does is try to update metadata on the remote. The output model doesn't exist on the remote before you call update_weights , so you have to set_metadata after upload.

Posted 11 months ago

I'll make one:)

Posted 11 months ago