tc.autotune((batch, channels, 64, 64)) # image of size 64 x 64
```
Now the autotuner is tuned for these three specific image sizes 32x32, 48x48 and 64x64.
Lack of loops
If you want to write an RNN, it's easy to see it as a for loop over time. However, the TC language does not have loops yet. If you really want to write RNNs, you can write unrolled loops.
Strided-Tensors
The TC backend does not support non-contiguous Tensors yet. If the inputs you give are not contiguous, they are made contiguous before passing to the TC backend.
Reshaping Tensors within a TC expression
You cannot write this operation in TC: torch.matmul(...).view(...).mean(...). Whenever there is need for a view to change the shape of an input, you have to get the output, view it at the PyTorch level.
Getting Started