PyTorch supports dynamic computational graphs, which means the network behavior can be changed programmatically at runtime .
PyTorch is faster than TensorFlow is that writing optimal code in PyTorch is MUCH easier! This is due to PyTorch's excellent documentation, dynamic graph, and easy synchronic data-parallel processing .
Just watch setup your views.py .
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