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‎_downloads/dbcf5e6a5e95bf9f7a0e49e123c13b60/saving_and_loading_a_general_checkpoint.ipynb

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},
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"outputs": [],
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"model = Net()\noptimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)\n\ncheckpoint = torch.load(PATH)\nmodel.load_state_dict(checkpoint['model_state_dict'])\noptimizer.load_state_dict(checkpoint['optimizer_state_dict'])\nepoch = checkpoint['epoch']\nloss = checkpoint['loss']\n\nmodel.eval()\n# - or -\nmodel.train()"
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"model = Net()\noptimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)\n\ncheckpoint = torch.load(PATH)\nmodel.load_state_dict(checkpoint['model_state_dict'])\noptimizer.load_state_dict(checkpoint['optimizer_state_dict'])\nepoch = checkpoint['epoch']\nloss = checkpoint['loss']\n\nmodel.eval()\n# - or -\nmodel.train()"
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{

‎_downloads/f1c4e73325cc32385d0f39145a3d83eb/saving_and_loading_a_general_checkpoint.py

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model = Net()
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optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)
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optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)
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checkpoint = torch.load(PATH)
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model.load_state_dict(checkpoint['model_state_dict'])

‎_images/sphx_glr_char_rnn_classification_tutorial_001.png

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‎_sources/advanced/dynamic_quantization_tutorial.rst.txt

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‎_sources/advanced/neural_style_tutorial.rst.txt

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Downloading: "https://download.pytorch.org/models/vgg19-dcbb9e9d.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/vgg19-dcbb9e9d.pth
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‎_sources/advanced/numpy_extensions_tutorial.rst.txt

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‎_sources/beginner/Intro_to_TorchScript_tutorial.rst.txt

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.. code-block:: none
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(tensor([[0.8625, 0.2666, 0.4852, 0.8900],
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.. _sphx_glr_download_beginner_Intro_to_TorchScript_tutorial.py:

‎_sources/beginner/basics/autogradqs_tutorial.rst.txt

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