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### Parameter groups
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PyTorch optimizers group parameters into sets called groups.
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- Each group can have it's own hyper-parameters like learning rates.
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+ Each group can have its own hyper-parameters like learning rates.
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In most common cases there will be only one group.
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This is when you initialize your optimizer with,
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Optimizer([{'params': model1.parameters()}, {'params': model2.parameters(), 'lr': 2}])
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```
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- Here we pass a list of groups. Each group is a dictionary with it's parameters under the key 'params'.
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+ Here we pass a list of groups. Each group is a dictionary with its parameters under the key 'params'.
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You specify any hyper-parameters as well. If the hyper parameters are not defined they will default
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to the optimizer level defaults.
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