Source code for torch.nn.utils.init

import inspect
import torch

[docs]def skip_init(module_cls, *args, **kwargs): r""" Given a module class object and args / kwargs, instantiates the module without initializing parameters / buffers. This can be useful if initialization is slow or if custom initialization will be performed, making the default initialization unnecessary. There are some caveats to this, due to the way this function is implemented: 1. The module must accept a `device` arg in its constructor that is passed to any parameters or buffers created during construction. 2. The module must not perform any computation on parameters in its constructor except initialization (i.e. functions from :mod:`torch.nn.init`). If these conditions are satisfied, the module can be instantiated with parameter / buffer values uninitialized, as if having been created using :func:`torch.empty`. Args: module_cls: Class object; should be a subclass of :class:`torch.nn.Module` args: args to pass to the module's constructor kwargs: kwargs to pass to the module's constructor Returns: Instantiated module with uninitialized parameters / buffers Example:: >>> # xdoctest: +IGNORE_WANT("non-deterministic") >>> import torch >>> m = torch.nn.utils.skip_init(torch.nn.Linear, 5, 1) >>> m.weight Parameter containing: tensor([[0.0000e+00, 1.5846e+29, 7.8307e+00, 2.5250e-29, 1.1210e-44]], requires_grad=True) >>> m2 = torch.nn.utils.skip_init(torch.nn.Linear, in_features=6, out_features=1) >>> m2.weight Parameter containing: tensor([[-1.4677e+24, 4.5915e-41, 1.4013e-45, 0.0000e+00, -1.4677e+24, 4.5915e-41]], requires_grad=True) """ if not issubclass(module_cls, torch.nn.Module): raise RuntimeError(f'Expected a Module; got {module_cls}') if 'device' not in inspect.signature(module_cls).parameters: raise RuntimeError('Module must support a \'device\' arg to skip initialization') final_device = kwargs.pop('device', 'cpu') kwargs['device'] = 'meta' return module_cls(*args, **kwargs).to_empty(device=final_device)


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources