#Project Directory

text-to-image-unet/
├── dataset/
│   ├── images/
│   │   ├── image1.jpg
│   │   ├── image2.png
│   │   └── ...
│   └── captions.txt  
├── requirements.txt
├── data_prep.py
├── model.py
├── train.py
├── generate.py
└── app.py 

Errors while Running train.py


PS D:\Text-2-Image> python -u "d:\Text-2-Image\train.py"
Length of Image Paths: 11
Length of Captions: 11
C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
Traceback (most recent call last):
  File "d:\Text-2-Image\train.py", line 69, in <module>
    model = UNet(in_channels=3, out_channels=3, text_input_size=512, text_output_size=256).to(DEVICE)
  File "d:\Text-2-Image\model.py", line 60, in __init__
    sample_processed_text = self.text_module(sample_text_features)      
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl  
    return self._call_impl(*args, **kwargs)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "d:\Text-2-Image\model.py", line 41, in forward
    output = self.fc(reshaped_input)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl  
    return self._call_impl(*args, **kwargs)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\linear.py", line 116, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x60 and 512x256)

After update model.py this error coming


PS D:\Text-2-Image> python -u "d:\Text-2-Image\train.py"

Length of Image Paths: 11
Length of Captions: 11
C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
Traceback (most recent call last):
  File "d:\Text-2-Image\train.py", line 80, in <module> 
    text_features = TextProcessingModule(input_size=60, output_size=256)(caption)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\Users\wbavi\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "d:\Text-2-Image\model.py", line 53, in forward  
    processed_text = output.unsqueeze(-1).unsqueeze(-1).expand_as(x7)
RuntimeError: expand(torch.FloatTensor{[4, 256, 1, 1]}, size=[4, 256]): the number of sizes provided (2) must be greater or equal to the number of dimensions in the tensor (4)

Write your error here

Check model.py very carefully and update the parameters - pull request are welcome..

Solution required...