With the arrival of the PyTorch 1.0 release and the addition of TorchScript, a JIT-compiled subset of Python combined with a fast C++ runtime, the framework is most definitely ready for prime time. Convert your PyTorch model to PyTorch-Lightning, then change one line of code to get: multi-GPU & distributed training, and float16 training too! Get Python out of the loop. Try out TorchScript (especially for inference). Try Numba to compile your hard-to-vectorize Python code (with the @numba.jit and @numba.cuda.jit decorators).
3.1. Options ¶. The compilation and execution on the IPU can be controlled using poptorch.Options:. See Efficient data batching for a full explanation of how device_iterations greater than 1, gradient_accumulation, and replication_factor interact with the output and input sizes.
PyTorch is a Python package that offers Tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on tape-based autograd system. This project allows for fast, flexible experimentation and efficient production.