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Diffstat (limited to 'README.md')
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@@ -30,15 +30,32 @@ We are in an early-release Beta. Expect some adventures and rough edges. At a granular level, PyTorch is a library that consists of the following components: -| \_ | \_ | -| ------------------------ | --- | -| torch | a Tensor library like NumPy, with strong GPU support | -| torch.autograd | a tape based automatic differentiation library that supports all differentiable Tensor operations in torch | -| torch.nn | a neural networks library deeply integrated with autograd designed for maximum flexibility | -| torch.optim | an optimization package to be used with torch.nn with standard optimization methods such as SGD, RMSProp, LBFGS, Adam etc. | -| torch.multiprocessing | python multiprocessing, but with magical memory sharing of torch Tensors across processes. Useful for data loading and hogwild training. | -| torch.utils | DataLoader, Trainer and other utility functions for convenience | -| torch.legacy(.nn/.optim) | legacy code that has been ported over from torch for backward compatibility reasons | +<table> +<tr> + <td><b> torch </b></td> + <td> a Tensor library like NumPy, with strong GPU support </td> +</tr> +<tr> + <td><b> torch.autograd </b></td> + <td> a tape based automatic differentiation library that supports all differentiable Tensor operations in torch </td> +</tr> +<tr> + <td><b> torch.nn </b></td> + <td> a neural networks library deeply integrated with autograd designed for maximum flexibility </td> +</tr> +<tr> + <td><b> torch.multiprocessing </b></td> + <td> python multiprocessing, but with magical memory sharing of torch Tensors across processes. Useful for data loading and hogwild training. </td> +</tr> +<tr> + <td><b> torch.utils </b></td> + <td> DataLoader, Trainer and other utility functions for convenience </td> +</tr> +<tr> + <td><b> torch.legacy(.nn/.optim) </b></td> + <td> legacy code that has been ported over from torch for backward compatibility reasons </td> +</tr> +</table> Usually one uses PyTorch either as: |