Intercepts the execution of your Python code (PEP 523) and transforms it into FX intermediate representation (IR), and stores it in a special data structure called FX Graph
ATen IR > Core ATen IR > Prism IR
a list of operators supported by the ATen library
tensor.is_contiguous()
view(): Does NOT make a copy of the original tensor. It changes the dimensional interpretation (striding) on the original data. In other words, it uses the same chunk of data with the original tensor, so it ONLY works with contiguous data.reshape(): Returns a view while possible (i.e., when the data is contiguous). If not (i.e., the data is not contiguous), then it copies the data into a contiguous data chunk, and as a copy, it would take up memory space, and also the change in the new tensor would not affect the value in the original tensor.
https://medium.com/analytics-vidhya/pytorch-contiguous-vs-non-contiguous-tensor-view-understanding-view-reshape-73e10cdfa0dd
Stride (one of the tensor representations)
https://medium.com/analytics-vidhya/pytorch-contiguous-vs-non-contiguous-tensor-view-understanding-view-reshape-73e10cdfa0dd
Tensor Representation
http://blog.ezyang.com/img/pytorch-internals
