New error with `embeddigns = torch.tensor(embeddins)
C:/w/1/s/tmp_conda_3.7_100118/conda/conda-bld/pytorch_1579082551706/work/aten/src/THC/THCTensorIndex.cu:307: block: [0,0,0], thread: [0,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
C:/w/1/s/tmp_conda_3.7_100118/conda/conda-bld/pytorch_1579082551706/work/aten/src/THC/THCTensorIndex.cu:307: block: [0,0,0], thread: [1,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
Traceback (most recent call last):
  File "inspection_model.py", line 550, in <module>
    train_losses, test_losses = roof_run()
  File "inspection_model.py", line 504, in roof_run
    outputs = roof_model(image, numerical_data, categorical_data)
  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Local\Continuum\anaconda3\envs\torch_env\lib\site-packages\torch\nn\modules\module.py", line 532, in __call__
    result = self.forward(*input, **kwargs)
  File "inspection_model.py", line 455, in forward
    embeddings = torch.tensor(embeddings)
ValueError: only one element tensors can be converted to Python scalars

The output is that I want to combine my concatenate my categorical and numerical columns with the output from my VGG19 image model to give more lift.