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ika-rwth-aachen / Point-Cloud-Compression

Implements a deep RNN based Point Cloud Compression approach for Velodyne Point Clouds. Reference implementation of corresponding IEEE IV22 paper.
MIT License
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Error when running train.py file #3

Open nanfangzhe opened 5 months ago

nanfangzhe commented 5 months ago

Traceback (most recent call last): File "train.py", line 104, in train(args) File "train.py", line 78, in train model.fit( File "/home/coplin/anaconda3/envs/tf/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 67, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/coplin/anaconda3/envs/tf/lib/python3.8/site-packages/keras/engine/training.py", line 1420, in fit raise ValueError('Unexpected result of train_function ' ValueError: Unexpected result of train_function (Empty logs). Please use Model.compile(..., run_eagerly=True), or tf.config.run_functions_eagerly(True) for more information of where went wrong, or file a issue/bug to tf.keras.

TillBeemelmanns commented 5 months ago

Can you please provide more information about your setup. Otherwise, it is not possible to resolve this problem. Are you using the docker setup ? Which Tensorflow Version are you using ? Which command did you use for running train.py

RuiqiYing commented 4 months ago

I encountered the same issue. I used Docker to run the setup. Below are the environment configurations and commands used: Package Version

absl-py 1.0.0 astunparse 1.6.3 cachetools 5.1.0 certifi 2019.11.28 chardet 3.0.4 cloudpickle 3.0.0 dbus-python 1.2.16 decorator 5.1.1 dm-tree 0.1.8 easydict 1.13 flatbuffers 1.12 gast 0.4.0 google-auth 2.6.6 google-auth-oauthlib 0.4.6 google-pasta 0.2.0 grpcio 1.46.1 h5py 3.6.0 idna 2.8 importlib-metadata 4.11.3 keras 2.9.0 Keras-Preprocessing 1.1.2 libclang 14.0.1 Markdown 3.3.7 numpy 1.22.3 oauthlib 3.2.0 opt-einsum 3.3.0 packaging 21.3 pip 20.2.4 protobuf 3.20.1 pyasn1 0.4.8 pyasn1-modules 0.2.8 PyGObject 3.36.0 pyparsing 3.0.9 python-apt 2.0.0+ubuntu0.20.4.7 requests 2.22.0 requests-oauthlib 1.3.1 requests-unixsocket 0.2.0 rsa 4.8 scipy 1.10.1 setuptools 62.2.0 six 1.14.0 tensorboard 2.9.0 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorflow 2.9.0 tensorflow-compression 2.9.0 tensorflow-estimator 2.9.0 tensorflow-io-gcs-filesystem 0.25.0 tensorflow-probability 0.17.0 termcolor 1.1.0 typing-extensions 4.2.0 urllib3 1.25.8 Werkzeug 2.1.2 wheel 0.34.2 wrapt 1.14.1 zipp 3.8.0

python3 ./train.py \ --train_data_dir="demo_samples/training" \ --val_data_dir="demo_samples/validation" \ --train_output_dir="output" \ --model=additive_lstm_demo

TillBeemelmanns commented 4 months ago

Can you double check that the dataset loaded correctly and placed at the correct location? And double check that all pathes are correct. The error usually arises when the dataloader is empty and no training is conducted.

BKB199676 commented 3 months ago

Insufficient training data may be the cause of this error