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Hello Everyone, While Calling Get_Local_Copy Of The Dataset From The Fileserver, I Get The Path To The Local Copy, But The Files Are Not Downloaded And The Folder Is Empty. Tell Me What Could Be The Problem. I Don'T Get Any Additional Errors Or Warnings.

Hello everyone, while calling get_local_copy of the dataset from the fileserver, I get the path to the local copy, but the files are not downloaded and the folder is empty. Tell me what could be the problem. I don't get any additional errors or warnings. Everything looks fine, but the files in the specified path do not appear. Also the same problem with using get_mutable_local_copy function.

from clearml import Dataset

dataset = Dataset.get(
    dataset_name="test OCR dataset",
    dataset_project="Text Recognition"
)

print(dataset.get_local_copy())

image

  
  
Posted 10 months ago
Votes Newest

Answers 7


@<1523701435869433856:profile|SmugDolphin23>
I rechecked on single files, creating new datasets, and everything works properly. I tried to create dataset using original data, and I got the following logs. Could you suggest what could be causing this?
Uploading dataset changes (1497 files compressed to 9.07 MiB) to None
2023-05-12 08:46:03,114 - clearml.storage - ERROR - Exception encountered while uploading Failed uploading object /addudkin2/.datasets/test-addudkin/test-addudkin.19ab55776fed408cab214814543699de/artifacts/data/dataset.19ab55776fed408cab214814543699de.mr7nkbq8.zip (413): <html>
<head><title>413 Request Entity Too Large</title></head>
<body>
<center><h1>413 Request Entity Too Large</h1></center>
<hr><center>nginx</center>
</body>
</html>

WARNING:root:Failed uploading artifact 'data'. Retrying... (1/3)
2023-05-12 08:46:03,602 - clearml.storage - ERROR - Exception encountered while uploading Failed uploading object /addudkin2/.datasets/test-addudkin/test-addudkin.19ab55776fed408cab214814543699de/artifacts/data/dataset.19ab55776fed408cab214814543699de.mr7nkbq8.zip (413): <html>
<head><title>413 Request Entity Too Large</title></head>
<body>
<center><h1>413 Request Entity Too Large</h1></center>
<hr><center>nginx</center>
</body>
</html>

WARNING:root:Failed uploading artifact 'data'. Retrying... (2/3)
2023-05-12 08:46:03,920 - clearml.storage - ERROR - Exception encountered while uploading Failed uploading object /addudkin2/.datasets/test-addudkin/test-addudkin.19ab55776fed408cab214814543699de/artifacts/data/dataset.19ab55776fed408cab214814543699de.mr7nkbq8.zip (413): <html>
<head><title>413 Request Entity Too Large</title></head>
<body>
<center><h1>413 Request Entity Too Large</h1></center>
<hr><center>nginx</center>
</body>
</html>

WARNING:root:Failed uploading artifact 'data'. Retrying... (3/3)
2023-05-12 08:46:04,392 - clearml.storage - ERROR - Exception encountered while uploading Failed uploading object /addudkin2/.datasets/test-addudkin/test-addudkin.19ab55776fed408cab214814543699de/artifacts/data/dataset.19ab55776fed408cab214814543699de.mr7nkbq8.zip (413): <html>
<head><title>413 Request Entity Too Large</title></head>
<body>
<center><h1>413 Request Entity Too Large</h1></center>
<hr><center>nginx</center>
</body>
</html>

File compression and upload completed: total size 9.07 MiB, 1 chunk(s) stored (average size 9.07 MiB)

  
  
Posted 10 months ago

Hi @<1524560082761682944:profile|MammothParrot39> , did you make sure to finalize the dataset you're trying to access?

  
  
Posted 10 months ago

@<1523701070390366208:profile|CostlyOstrich36> Yes, sure

import pandas as pd
import yaml
import os
from omegaconf import OmegaConf
from clearml import Dataset

config_path = 'configs/structured_docs.yml'

with open(config_path) as f:
    config = yaml.full_load(f)

config = OmegaConf.create(config)
path2images = config.data.images_folder


def get_data(config, split):
    path2annotation = os.path.join(config.data.annotation_folder, f"sample_{split}.csv")
    data = pd.read_csv(path2annotation)
    return data


data_train = get_data(config, 'train')
data_val = get_data(config, 'val')
data = pd.concat([data_val, data_train])

files = [os.path.join(path2images, file) for file in data['filename'].values]


dataset = Dataset.create(
    dataset_name="test OCR dataset",
    dataset_project="Text Recognition"
)
for file in files:
    dataset.add_files(path=file)

dataset.upload()
dataset.finalize()

With this script, I uploaded data to the server. You can also see the final status of the dataset in the screenshot.

  
  
Posted 10 months ago

Hi @<1524560082761682944:profile|MammothParrot39> ! A few thoughts:
You likely know this, but the files may be downloaded to something like /home/user/.clearml/cache/storage_manager/datasets/ds_e0833955ded140a69b4c9c9d8e84986c . .clearml may be hidden and if you are using an explorer you are not able to see the directory.

If that is not the issue: are you able to download some other datasets, such as our example one: UrbanSounds example ? I'm wondering if the problem only happens for your specific dataset.

  
  
Posted 10 months ago

problem solved. Removed nginx limits

  
  
Posted 10 months ago

How can you solve this problem? I'm with this one too.

  
  
Posted 9 months ago

@<1578193574506270720:profile|DashingAlligator28> Removed nginx limits

  
  
Posted 9 months ago
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