tf.keras.datasets.cifar10.load_data - FileNotFoundError: [Errno 2] No such file or directory

[ashep29]

Issue with tar.gz file extraction - inconsistent behaviour across systems/platforms:

(train_images, train_labels), (test_images, test_labels) = keras.datasets.cifar10.load_data()

• works on Google colab
• works on Windows > VS Code > Jupyter
• fails on linux RHEL with details below:

NAME="Rocky Linux" VERSION="8.10 (Green Obsidian)" ID="rocky" ID_LIKE="rhel centos fedora" VERSION_ID="8.10" PLATFORM_ID="platform:el8"

Python 3.11.0rcl

absl-py==2.1.0 anyio==4.4.0 argon2-cffi==23.1.0 argon2-cffi-bindings==21.2.0 array_record==0.5.1 arrow==1.3.0 asttokens==2.4.1 astunparse==1.6.3 async-lru==2.0.4 attrs==24.2.0 babel==2.16.0 beautifulsoup4==4.12.3 bleach==6.1.0 blinker==1.4 certifi==2024.7.4 cffi==1.17.0 charset-normalizer==3.3.2 click==8.1.7 comm==0.2.2 contourpy==1.3.0 cryptography==3.4.8 cycler==0.12.1 dbus-python==1.2.18 debugpy==1.8.5 decorator==5.1.1 defusedxml==0.7.1 distro==1.7.0 dm-tree==0.1.8 docstring_parser==0.16 etils==1.9.2 executing==2.0.1 fastjsonschema==2.20.0 flatbuffers==24.3.25 fonttools==4.53.1 fqdn==1.5.1 fsspec==2024.6.1 gast==0.6.0 google-pasta==0.2.0 googleapis-common-protos==1.65.0 grpcio==1.64.1 h11==0.14.0 h5py==3.11.0 httpcore==1.0.5 httplib2==0.20.2 httpx==0.27.2 idna==3.7 immutabledict==4.2.0 importlib-metadata==4.6.4 importlib_resources==6.4.4 ipykernel==6.29.5 ipython==8.26.0 ipywidgets==8.1.5 isoduration==20.11.0 jedi==0.19.1 jeepney==0.7.1 Jinja2==3.1.4 joblib==1.4.2 json5==0.9.25 jsonpointer==3.0.0 jsonschema==4.23.0 jsonschema-specifications==2023.12.1 jupyter==1.0.0 jupyter-console==6.6.3 jupyter-events==0.10.0 jupyter-lsp==2.2.5 jupyter_client==8.6.2 jupyter_core==5.7.2 jupyter_server==2.14.2 jupyter_server_terminals==0.5.3 jupyterlab==4.2.5 jupyterlab_pygments==0.3.0 jupyterlab_server==2.27.3 jupyterlab_widgets==3.0.13 kagglehub==0.2.9 keras==3.4.1 keras-core==0.1.7 keras-cv==0.9.0 keras-nlp==0.14.4 keyring==23.5.0 kiwisolver==1.4.5 launchpadlib==1.10.16 lazr.restfulclient==0.14.4 lazr.uri==1.0.6 libclang==18.1.1 Markdown==3.6 markdown-it-py==3.0.0 MarkupSafe==2.1.5 matplotlib==3.9.2 matplotlib-inline==0.1.7 mdurl==0.1.2 mistune==3.0.2 ml-dtypes==0.4.0 more-itertools==8.10.0 mplfinance==0.12.10b0 namex==0.0.8 nbclient==0.10.0 nbconvert==7.16.4 nbformat==5.10.4 nest-asyncio==1.6.0 notebook==7.2.2 notebook_shim==0.2.4 numpy==1.26.4 oauthlib==3.2.0 opt-einsum==3.3.0 optree==0.12.1 overrides==7.7.0 packaging==24.1 pandas==2.2.2 pandocfilters==1.5.1 parso==0.8.4 pexpect==4.9.0 pillow==10.4.0 platformdirs==4.2.2 prometheus_client==0.20.0 promise==2.3 prompt_toolkit==3.0.47 protobuf==4.25.3 psutil==6.0.0 ptyprocess==0.7.0 pure_eval==0.2.3 pyarrow==17.0.0 pycparser==2.22 pydot==3.0.1 Pygments==2.18.0 PyGObject==3.42.1 PyJWT==2.3.0 pyparsing==3.1.4 python-apt==2.4.0+ubuntu3 python-dateutil==2.9.0.post0 python-json-logger==2.0.7 pytz==2024.1 PyYAML==6.0.2 pyzmq==26.2.0 qtconsole==5.6.0 QtPy==2.4.1 referencing==0.35.1 regex==2024.7.24 requests==2.32.3 rfc3339-validator==0.1.4 rfc3986-validator==0.1.1 rich==13.7.1 rpds-py==0.20.0 scikit-learn==1.5.1 scipy==1.14.1 SecretStorage==3.3.1 Send2Trash==1.8.3 simple_parsing==0.1.5 six==1.16.0 sniffio==1.3.1 soupsieve==2.6 stack-data==0.6.3 tensorboard==2.17.0 tensorboard-data-server==0.7.2 tensorflow==2.17.0 tensorflow-datasets==4.9.6 tensorflow-io-gcs-filesystem==0.37.1 tensorflow-metadata==1.15.0 tensorflow-text==2.17.0 termcolor==2.4.0 terminado==0.18.1 threadpoolctl==3.5.0 tinycss2==1.3.0 toml==0.10.2 tornado==6.4.1 tqdm==4.66.5 traitlets==5.14.3 types-python-dateutil==2.9.0.20240821 typing_extensions==4.12.2 tzdata==2024.1 uri-template==1.3.0 urllib3==2.2.2 wadllib==1.3.6 wcwidth==0.2.13 webcolors==24.8.0 webencodings==0.5.1 websocket-client==1.8.0 Werkzeug==3.0.3 widgetsnbextension==4.0.13 wrapt==1.16.0 zipp==1.0.0

error:

FileNotFoundError Traceback (most recent call last) Cell In[25], line 1 ----> 1 (train_images, train_labels), (test_images, test_labels) = keras.datasets.cifar10.load_data() File ~/.conda/envs/env_name/lib/python3.12/site-packages/keras/src/datasets/cifar10.py:84, in load_data() 79 for i in range(1, 6): 80 fpath = os.path.join(path, "databatch" + str(i)) 81 ( 82 x_train[(i - 1) 10000 : i 10000, :, :, :], 83 y_train[(i - 1) 10000 : i 10000], ---> 84 ) = load_batch(fpath) 86 fpath = os.path.join(path, "test_batch") 87 x_test, y_test = load_batch(fpath)

File ~/.conda/envs/env_name/lib/python3.12/site-packages/keras/src/datasets/cifar.py:17, in load_batch(fpath, label_key) 6 def load_batch(fpath, label_key="labels"): 7 """Internal utility for parsing CIFAR data. 8 9 Args: (...) 15 A tuple (data, labels). 16 """ ---> 17 with open(fpath, "rb") as f: 18 d = cPickle.load(f, encoding="bytes") 19 # decode utf8

FileNotFoundError: [Errno 2] No such file or directory: '/home/username/.keras/datasets/cifar-10-batches-py/data_batch_1'

Data is being saved to '/home/username/.keras/datasets/cifar-10-batches-py/cifar-10-batches-py/data_batch_1'

[mehtamansi29]

Hi @ashep29 -

Thanks for reporting the issue. I am not able to reproduce this issue on RHEL CentOS Stream release 9 machine with Python env: Python 3.11.9 and keras version: 3.5.0. Can you try to upgrade keras version(pip install --upgrade keras) and try to rerun the code ?

[ashep29]

Thanks for taking a look.

I'm running a jupyter notebook (screenshot below) with tensorflow install using docker://tensorflow/tensorflow:latest-gpu (which installs keras). I've separately installed keras-cv and keras-nlp.

Even after the keras upgrade, the error persists:

[ghsanti]

Actually, I realised you were right while testing smth else, it does reproduce in Colab.

Here is a simple repro (unrelated code, but shows up in first cells.)

Tagging @mehtamansi29 since he may realise what's wrong (this uses 3.5.0)

https://colab.research.google.com/gist/ghsanti/f5111b30cd9dbe778d0f127d6b7b7647/print.ipynb

[ashep29]

Thanks @ghsanti, definitely the same error you have reproduced. Hopefully this can be resolved soon!

[ghsanti]

It happens with cifar100 as well, but not with MNIST.

Datasets' loading code are here: https://github.com/keras-team/keras/tree/master/keras/src/datasets

[ashep29]

Perhaps it has something to do with how the tar.gz is being extracted? Seems to be a difference between mnist and the cifar datasets.

[ghsanti]

The files are downloaded to:

/root/.keras/datasets/cifar-10-batches-py/cifar-10-batches-py

Here is where it looks for:

/root/.keras/datasets/cifar-10-batches-py/data_batch_1

So there is a repetition of cifar-10-batches-py before the batches' files. Does commenting out dirname work? (It may be a duplication by some un-tarring artifact, just like you suggested.)

[ashep29]

Thanks @ghsanti, I've commented out the dirname argument, but the value returned by get_file is still '/home/username/.keras/datasets/cifar-10-batches-py/data_batch_1', so the error persists. Perhaps the error actually lies in keras.src.utils.file_utils (get_file)?

[dwgily]

If you get it please, let us know!!!

[ghsanti]

This works in colab @ashep29 @himanshurana-27

    origin = "https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz"
    path = get_file(
        fname="cifar-10-batches-py",
        cache_dir="cifar-10-batches-py",
        origin=origin,
        untar=True,
        file_hash=(  # noqa: E501
            "6d958be074577803d12ecdefd02955f39262c83c16fe9348329d7fe0b5c001ce"
        ),

Added cache_dir since fname can not use /.

The function recommends replacing untar with extract, but those do not do the same thing, so I left untar.

[ashep29]

OK so the only change that needed to be done was to add extract=True in the get_file method. It is now working. Didn't need the cache_dir and left fname as it was originally, so final working code:

dirname = "cifar-10-batches-py"
    origin = "https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz"
    path = get_file(
        fname=dirname,
        origin=origin,
        extract=True,
        untar=True,
        file_hash=(  # noqa: E501
            "6d958be074577803d12ecdefd02955f39262c83c16fe9348329d7fe0b5c001ce"
        ),
    )

Thank you for your help!

[ghsanti]

That's another possibility indeed @ashep29 :-) May need to be added cifar100 as well.

Thank you for your help!

My pleasure

[mehtamansi29]

Actually, I realised you were right while testing smth else, it does reproduce in Colab.

Here is a simple repro (unrelated code, but shows up in first cells.)

Tagging @mehtamansi29 since he may realise what's wrong (this uses 3.5.0)

https://colab.research.google.com/gist/ghsanti/f5111b30cd9dbe778d0f127d6b7b7647/print.ipynb

Hi @ashep29 , @ghsanti -

This issue is reproduce with keras nightly(3.5.0.dev2024082903) version. Keras 3.5.0 its working fine. Attached the gist for your reference. We will look into the issue and update you on that.

[ghsanti]

yes, there is a PR just above your comment with more information in case you want to look at it. @mehtamansi29

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