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cb74ede59e
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/29364 Currently, we use `torch::nn::*Options` both as module options and functional options. However, this makes it very hard to manage the parameters in `torch::nn::*Options`, because a module's constructor can take a different set of arguments than the module's equivalent functional (e.g. `torch.nn.BatchNorm1d` takes `num_features, eps=1e-5, momentum=0.1, affine=True, track_running_stats=True`, while `F::batch_norm` takes `running_mean, running_var, weight=None, bias=None, training=False, momentum=0.1, eps=1e-5`). This PR resolves the above problem by making `F::*FuncOptions` a different class from `torch::nn::*Options` when necessary (i.e. when a module's constructor takes a different set of arguments than the module's equivalent functional). In the rest of the cases where the module constructor takes the same set of arguments as the module's equivalent functional, `F::*FuncOptions` is an alias of `torch::nn::*Options`. Also as part of this PR, we change all functional options to pass-by-value, to make the semantics consistent across all functionals. Test Plan: Imported from OSS Differential Revision: D18376977 Pulled By: yf225 fbshipit-source-id: 8d9c240d93bfd5af0165b6884fdc912476b1d06b |
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| api | ||
| common | ||
| dist_autograd | ||
| jit | ||
| __init__.py | ||