I get this error when trying to laucnh " python main.py -xgb -odds=fanduel " Not soo good at coding. Don't understand a thing about what is happing.
but here is the error code:
C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master>python main.py -xgb -odds=fanduel
2024-10-20 15:17:35.676488: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
2024-10-20 15:17:36.824470: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
Traceback (most recent call last):
File "C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master\main.py", line 9, in
from src.Predict import NN_Runner, XGBoost_Runner
File "C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master\src\Predict\NN_Runner.py", line 12, in
model = load_model('Models/NN_Models/Trained-Model-ML-1699315388.285516')
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Python312\Lib\site-packages\keras\src\saving\saving_api.py", line 206, in load_model
raise ValueError(
ValueError: File format not supported: filepath=Models/NN_Models/Trained-Model-ML-1699315388.285516. Keras 3 only supports V3 .keras files and legacy H5 format files (.h5 extension). Note that the legacy SavedModel format is not supported by load_model() in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use keras.layers.TFSMLayer(Models/NN_Models/Trained-Model-ML-1699315388.285516, call_endpoint='serving_default') (note that your call_endpoint might have a different name).
I get this error when trying to laucnh " python main.py -xgb -odds=fanduel " Not soo good at coding. Don't understand a thing about what is happing.
but here is the error code: C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master>python main.py -xgb -odds=fanduel 2024-10-20 15:17:35.676488: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable
from src.Predict import NN_Runner, XGBoost_Runner
File "C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master\src\Predict\NN_Runner.py", line 12, in
model = load_model('Models/NN_Models/Trained-Model-ML-1699315388.285516')
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Python312\Lib\site-packages\keras\src\saving\saving_api.py", line 206, in load_model
raise ValueError(
ValueError: File format not supported: filepath=Models/NN_Models/Trained-Model-ML-1699315388.285516. Keras 3 only supports V3
TF_ENABLE_ONEDNN_OPTS=0. 2024-10-20 15:17:36.824470: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variableTF_ENABLE_ONEDNN_OPTS=0. Traceback (most recent call last): File "C:\Users\Administrator\Desktop\NBA-Machine-Learning-Sports-Betting-master\main.py", line 9, in.kerasfiles and legacy H5 format files (.h5extension). Note that the legacy SavedModel format is not supported byload_model()in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, usekeras.layers.TFSMLayer(Models/NN_Models/Trained-Model-ML-1699315388.285516, call_endpoint='serving_default')(note that yourcall_endpointmight have a different name).