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c58709b7bb
Summary: This PR introduces a helper function named `torch.nn.utils.skip_init()` that accepts a module class object + `args` / `kwargs` and instantiates the module while skipping initialization of parameter / buffer values. See discussion at https://github.com/pytorch/pytorch/issues/29523 for more context. Example usage: ```python import torch m = torch.nn.utils.skip_init(torch.nn.Linear, 5, 1) print(m.weight) m2 = torch.nn.utils.skip_init(torch.nn.Linear, 5, 1, device='cuda') print(m2.weight) m3 = torch.nn.utils.skip_init(torch.nn.Linear, in_features=5, out_features=1) print(m3.weight) ``` ``` Parameter containing: tensor([[-3.3011e+28, 4.5915e-41, -3.3009e+28, 4.5915e-41, 0.0000e+00]], requires_grad=True) Parameter containing: tensor([[-2.5339e+27, 4.5915e-41, -2.5367e+27, 4.5915e-41, 0.0000e+00]], device='cuda:0', requires_grad=True) Parameter containing: tensor([[1.4013e-45, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00]], requires_grad=True) ``` Bikeshedding on the name / namespace is welcome, as well as comments on the design itself - just wanted to get something out there for discussion. Pull Request resolved: https://github.com/pytorch/pytorch/pull/57555 Reviewed By: zou3519 Differential Revision: D28640613 Pulled By: jbschlosser fbshipit-source-id: 5654f2e5af5530425ab7a9e357b6ba0d807e967f |
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| .. | ||
| _static | ||
| _templates | ||
| community | ||
| elastic | ||
| notes | ||
| rpc | ||
| scripts | ||
| __config__.rst | ||
| amp.rst | ||
| autograd.rst | ||
| backends.rst | ||
| benchmark_utils.rst | ||
| bottleneck.rst | ||
| checkpoint.rst | ||
| complex_numbers.rst | ||
| conf.py | ||
| cpp_extension.rst | ||
| cpp_index.rst | ||
| cuda.rst | ||
| cudnn_persistent_rnn.rst | ||
| cudnn_rnn_determinism.rst | ||
| data.rst | ||
| ddp_comm_hooks.rst | ||
| distributed.elastic.rst | ||
| distributed.optim.rst | ||
| distributed.rst | ||
| distributions.rst | ||
| dlpack.rst | ||
| docutils.conf | ||
| fft.rst | ||
| futures.rst | ||
| fx.rst | ||
| hub.rst | ||
| index.rst | ||
| jit.rst | ||
| jit_builtin_functions.rst | ||
| jit_language_reference.rst | ||
| jit_language_reference_v2.rst | ||
| jit_python_reference.rst | ||
| jit_unsupported.rst | ||
| linalg.rst | ||
| math-quantizer-equation.png | ||
| mobile_optimizer.rst | ||
| model_zoo.rst | ||
| multiprocessing.rst | ||
| name_inference.rst | ||
| named_tensor.rst | ||
| nn.functional.rst | ||
| nn.init.rst | ||
| nn.rst | ||
| onnx.rst | ||
| optim.rst | ||
| package.rst | ||
| pipeline.rst | ||
| profiler.rst | ||
| quantization-support.rst | ||
| quantization.rst | ||
| random.rst | ||
| rpc.rst | ||
| sparse.rst | ||
| special.rst | ||
| storage.rst | ||
| tensor_attributes.rst | ||
| tensor_view.rst | ||
| tensorboard.rst | ||
| tensors.rst | ||
| testing.rst | ||
| torch.nn.intrinsic.qat.rst | ||
| torch.nn.intrinsic.quantized.rst | ||
| torch.nn.intrinsic.rst | ||
| torch.nn.qat.rst | ||
| torch.nn.quantized.dynamic.rst | ||
| torch.nn.quantized.rst | ||
| torch.overrides.rst | ||
| torch.quantization.rst | ||
| torch.rst | ||
| type_info.rst | ||
