Getting ValueError: operands could not be broadcast together with shapes (144,144,3) (72,72,3) error

[Greywolf22]

Tried this today and got the error below

Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).
Time to backup: 10 hours
/content
Running trainer.

Loading model...

Model first run. Enter model options as default for each run.
Write preview history? (y/n ?:help skip:n) : y
Target iteration (skip:unlimited/default) : 
0
Batch_size (?:help skip:0) : 
0
Feed faces to network sorted by yaw? (y/n ?:help skip:n) : n
Flip faces randomly? (y/n ?:help skip:y) : n
Src face scale modifier % ( -30...30, ?:help skip:0) : 
0
Resolution ( 64-256 ?:help skip:128) : 144
Half or Full face? (h/f, ?:help skip:f) : 
f
Learn mask? (y/n, ?:help skip:y) : 
y
Optimizer mode? ( 1,2,3 ?:help skip:1) : 
1
AE architecture (df, liae ?:help skip:df) : 
df
AutoEncoder dims (32-1024 ?:help skip:512) : 
512
Encoder dims per channel (21-85 ?:help skip:42) : 
42
Decoder dims per channel (10-85 ?:help skip:21) : 
21
Remove gray border? (y/n, ?:help skip:n) : 
n
Use multiscale decoder? (y/n, ?:help skip:n) : y
Use pixel loss? (y/n, ?:help skip: n ) : 
n
Face style power ( 0.0 .. 100.0 ?:help skip:0.00) : 
0.0
Background style power ( 0.0 .. 100.0 ?:help skip:0.00) : 
0.0
Using TensorFlow backend.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
Loading: 100% 6791/6791 [00:06<00:00, 1049.77it/s]
Loading: 100% 6791/6791 [00:05<00:00, 1145.45it/s]
===== Model summary =====
== Model name: SAE
==
== Current iteration: 0
==
== Model options:
== |== write_preview_history : True
== |== batch_size : 4
== |== sort_by_yaw : False
== |== random_flip : False
== |== resolution : 144
== |== face_type : f
== |== learn_mask : True
== |== optimizer_mode : 1
== |== archi : df
== |== ae_dims : 512
== |== e_ch_dims : 42
== |== d_ch_dims : 21
== |== remove_gray_border : False
== |== multiscale_decoder : True
== |== pixel_loss : False
== |== face_style_power : 0.0
== |== bg_style_power : 0.0
== Running on:
== |== [0 : Tesla T4]
=========================
Starting. Press "Enter" to stop training and save model.
Error: operands could not be broadcast together with shapes (144,144,3) (72,72,3) 
Traceback (most recent call last):
  File "/content/DeepFaceLab/mainscripts/Trainer.py", line 93, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "/content/DeepFaceLab/models/ModelBase.py", line 376, in train_one_iter
    plist += [ (self.get_previews()[0][1], self.get_strpath_storage_for_file('preview.jpg') ) ]
  File "/content/DeepFaceLab/models/ModelBase.py", line 274, in get_previews
    return self.onGetPreview ( self.last_sample )
  File "/content/DeepFaceLab/models/Model_SAE/Model.py", line 411, in onGetPreview
    ar = S[i]*test_S_m[i], SS[i], D[i]*test_D_m[i], DD[i]*DDM[i], SD[i]*(DDM[i]*SDM[i])
ValueError: operands could not be broadcast together with shapes (144,144,3) (72,72,3) 
Done.
/usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown
  len(cache))
/usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown
  len(cache))
/usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown
  len(cache))
/usr/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown
  len(cache))

[chervonij]

Yes, I checked your settings with my dataset. The same mistake. But it's not about DFL-Colab. It seems that this is due to the resolution of 144

[chervonij]

It's bugreport for @iperov

[iperov]

fixed

[Greywolf22]

Thx. Its working now.