ValueError: the image you passed in is not of the correct dimensions

[Aabie]

Hey i trying to train this model using my dataset, but i got this error in second step, how can i solve this problem?

---

ValueError Traceback (most recent call last)
Cell In[22], line 2
1 if name == "main":
----> 2 main()

Cell In[21], line 526
524 # Train the model!
525 accelerator.print("Starting training!")
--> 526 trainer.train()
528 # Clean up and wait for other processes to finish (loggers etc.)
529 if accelerator.is_main_process:

File e:\Tugas Akhir\muse2\muse_maskgit_pytorch\trainers\maskgit_trainer.py:165, in MaskGitTrainer.train(self)
160 text_embeds = t5_encode_text_from_encoded(
161 input_ids, attn_mask, self.model.transformer.t5, self.accelerator.device
162 )
164 with self.accelerator.accumulate(self.model), self.accelerator.autocast():
--> 165 loss = self.model(imgs, text_embeds=text_embeds)
166 self.accelerator.backward(loss)
167 if self.max_grad_norm is not None and self.accelerator.sync_gradients:

File e:\Anaconda3\Lib\site-packages\torch\nn\modules\module.py:1511, in Module._wrapped_call_impl(self, *args, **kwargs)
1509 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1510 else:
-> 1511 return self._call_impl(*args, **kwargs)

File e:\Anaconda3\Lib\site-packages\torch\nn\modules\module.py:1520, in Module._call_impl(self, *args, **kwargs)
1515 # If we don't have any hooks, we want to skip the rest of the logic in
1516 # this function, and just call forward.
1517 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1518 or _global_backward_pre_hooks or _global_backward_hooks
1519 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1520 return forward_call(*args, **kwargs)
1522 try:
1523 result = None

File e:\Anaconda3\Lib\site-packages\accelerate\utils\operations.py:825, in convert_outputs_to_fp32..forward(*args, **kwargs)
824 def forward(*args, **kwargs):
--> 825 return model_forward(*args, **kwargs)

File e:\Anaconda3\Lib\site-packages\accelerate\utils\operations.py:813, in ConvertOutputsToFp32.call(self, *args, **kwargs)
812 def call(self, *args, **kwargs):
--> 813 return convert_to_fp32(self.model_forward(*args, **kwargs))

File e:\Anaconda3\Lib\site-packages\torch\amp\autocast_mode.py:16, in autocast_decorator..decorate_autocast(*args, **kwargs)
13 @functools.wraps(func)
14 def decorate_autocast(*args, **kwargs):
15 with autocast_instance:
---> 16 return func(*args, **kwargs)

File <@beartype(muse_maskgit_pytorch.muse_maskgit_pytorch.MaskGit.forward) at 0x207570d2ac0>:134, in forward(__beartype_object_2230262900624, __beartype_get_violation, __beartype_conf, __beartype_object_2230548286144, __beartype_object_140704628379520, __beartype_getrandbits, __beartype_func, *args, **kwargs)

File e:\Tugas Akhir\muse2\muse_maskgit_pytorch\muse_maskgit_pytorch.py:640, in MaskGit.forward(self, images_or_ids, ignore_index, cond_images, cond_token_ids, texts, text_embeds, cond_drop_prob, train_only_generator, sample_temperature)
638 if not all([height_or_width == self.image_size for height_or_width in images_or_ids.shape[-2:]]):
639 print(images_or_ids.shape[-2:])
--> 640 raise ValueError("the image you passed in is not of the correct dimensions")
642 with torch.no_grad():
643 _, ids, _ = self.vae.encode(images_or_ids)

ValueError: the image you passed in is not of the correct dimensions