You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Traceback (most recent call last): File "p2b1_baseline_keras2.py", line 298, in <module> main() File "p2b1_baseline_keras2.py", line 294, in main run(gParameters) File "p2b1_baseline_keras2.py", line 231, in run molecular_model.compile(optimizer=opt, loss=loss_func, metrics=['mean_squared_error', 'mean_absolute_error']) File "/nfs/gce/software/custom/linux-ubuntu18.04-x86_64/anaconda3/rolling/envs/candle-tf1/lib/python3.7/site-packages/keras/engine/training.py", line 95, in compile self.optimizer = optimizers.get(optimizer) File "/nfs/gce/software/custom/linux-ubuntu18.04-x86_64/anaconda3/rolling/envs/candle-tf1/lib/python3.7/site-packages/keras/optimizers.py", line 873, in get str(identifier)) ValueError: Could not interpret optimizer identifier: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7f06fa323d90>
This might be due to mixed Tensorflow keras and keras API in the code.
The text was updated successfully, but these errors were encountered:
Traceback (most recent call last): File "p2b1_baseline_keras2.py", line 298, in <module> main() File "p2b1_baseline_keras2.py", line 294, in main run(gParameters) File "p2b1_baseline_keras2.py", line 231, in run molecular_model.compile(optimizer=opt, loss=loss_func, metrics=['mean_squared_error', 'mean_absolute_error']) File "/nfs/gce/software/custom/linux-ubuntu18.04-x86_64/anaconda3/rolling/envs/candle-tf1/lib/python3.7/site-packages/keras/engine/training.py", line 95, in compile self.optimizer = optimizers.get(optimizer) File "/nfs/gce/software/custom/linux-ubuntu18.04-x86_64/anaconda3/rolling/envs/candle-tf1/lib/python3.7/site-packages/keras/optimizers.py", line 873, in get str(identifier)) ValueError: Could not interpret optimizer identifier: <tensorflow.python.keras.optimizer_v2.adam.Adam object at 0x7f06fa323d90>
This might be due to mixed Tensorflow keras and keras API in the code.
The text was updated successfully, but these errors were encountered: