fail to train for unet 3D

[jinxsfe]

Hi, whether adjust UNET structure for 4 depth, instead of 3 depth, and training show an error, for weight names,

ValueError Traceback (most recent call last)
in <cell line: 18>()
16 start = time.time()
17 # Start Training
---> 18 model.train(epochs=number_of_epochs,
19 batch_size=batch_size,
20 train_generator=train_generator,

1 frames
/usr/local/lib/python3.10/dist-packages/keras/src/callbacks/model_checkpoint.py in init(self, filepath, monitor, verbose, save_best_only, save_weights_only, mode, save_freq, initial_value_threshold)
181 if save_weights_only:
182 if not self.filepath.endswith(".weights.h5"):
--> 183 raise ValueError(
184 "When using save_weights_only=True in ModelCheckpoint"
185 ", the filepath provided must end in .weights.h5 "

ValueError: When using save_weights_only=True in ModelCheckpoint, the filepath provided must end in .weights.h5 (Keras weights format). Received: filepath=/content/gdrive/MyDrive/cryo/cryo-data_processing_volume/model/gaussian4layer_320_50_0.00014/ckpt/gaussian4layer_320_50_0.00014.hdf5

I tried to change if save_best_ckpt_only:
ckpt_name = ckpt_dir + '/' + model_name + '.hdf5'
else:
ckpt_name = ckpt_dir + '/' + model_name + 'epoch{epoch:02d}val_loss{val_loss:.4f}.hdf5' to if save_best_ckpt_only:
ckpt_name = ckpt_dir + '/' + model_name + '.weights.h5'
else:
ckpt_name = ckpt_dir + '/' + model_name + 'epoch{epoch:02d}val_loss{val_loss:.4f}.weighths.h5' or keras corresponding to the save_weight"_only = True and save best only =True requirement but error output.

I even go model check point to set these two parameter equal true and false, but also cause the same issue

[jinxsfe]

@esgomezm @paxcalpt

[jinxsfe]

I kept the original structure for your notebook but cause the same error

[jinxsfe]

when I change back to ckpt_name = ckpt_dir + '/' + model_name + '.hdf5'
else:
ckpt_name = ckpt_dir + '/' + model_name + 'epoch{epoch:02d}val_loss{val_loss:.4f}.hdf5'.

and turn these off, it show the error

if I change it to keras, also show the same problem for

[jinxsfe]

sorry I forgot to input .hdf5 but error still occur