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Error downloading mini-imagenet data

See original GitHub issue

Somehow I get the following error:

Downloading: /home/miranda9/data/l2l_data/mini-imagenet-cache-test.pkl
Traceback (most recent call last):
  File "/home/miranda9/miniconda3/envs/meta_learning_a100/lib/python3.9/site-packages/learn2learn/vision/datasets/mini_imagenet.py", line 102, in __init__
    self.data = pickle.load(f)
_pickle.UnpicklingError: invalid load key, '<'.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/miranda9/ultimate-utils/ultimate-utils-proj-src/uutils/torch_uu/dataloaders/meta_learning/l2l_mini_imagenet_mi.py", line 268, in <module>
    mi_test()
  File "/home/miranda9/ultimate-utils/ultimate-utils-proj-src/uutils/torch_uu/dataloaders/meta_learning/l2l_mini_imagenet_mi.py", line 255, in mi_test
    args.tasksets: BenchmarkTasksets = get_tasksets(
  File "/home/miranda9/ultimate-utils/ultimate-utils-proj-src/uutils/torch_uu/dataloaders/meta_learning/l2l_mini_imagenet_mi.py", line 212, in get_tasksets
    datasets, transforms = _TASKSETS[name](train_ways=train_ways,
  File "/home/miranda9/ultimate-utils/ultimate-utils-proj-src/uutils/torch_uu/dataloaders/meta_learning/l2l_mini_imagenet_mi.py", line 78, in mini_imagenet_tasksets
    test_dataset = l2l.vision.datasets.MiniImagenet(
  File "/home/miranda9/miniconda3/envs/meta_learning_a100/lib/python3.9/site-packages/learn2learn/vision/datasets/mini_imagenet.py", line 108, in __init__
    self.data = pickle.load(f)
_pickle.UnpicklingError: invalid load key, '<'.

but I only get it in the dgx machine not locally…has anyone had this error before?

cross: https://stackoverflow.com/questions/71094907/how-does-one-download-data-for-a-dgx-a100-machine-that-returns-a-invalid-load-ke

Issue Analytics

State:
Created 2 years ago
Comments:21 (3 by maintainers)

Top GitHub Comments

11reactions

nazagocommented, Feb 25, 2022

A temporal solution I found is the following:

1 Go to /learn2learn/vision/datasets and choose your <dataset>.py (for example, mini_imagenet.py). 2 Look through the code comments, there are the link from which the script download the test. 3 Click the links and download them with your web browser. 4 Move them to the folder the algorithm look for the dataset (by default ~/data).

This is how I have solved 😃

1reaction

woreomcommented, Sep 27, 2022

Just use gdown to download your data from google drive

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