mmengine.optim¶
Optimizer¶
A subclass of |
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A subclass of |
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Optimizer wrapper provides a common interface for updating parameters. |
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A dictionary container of |
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Default constructor for optimizers. |
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A wrapper class of |
Build function of OptimWrapper. |
Scheduler¶
Base class for parameter schedulers. |
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Decays the learning rate value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: |
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Decays the momentum value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: |
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Decays the parameter value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: |
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Set the learning rate of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR: |
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Set the momentum of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR: |
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Set the parameter value of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR: |
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Decays the learning rate of each parameter group by gamma every epoch. |
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Decays the momentum of each parameter group by gamma every epoch. |
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Decays the parameter value of each parameter group by gamma every epoch. |
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Decays the learning rate of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: |
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Decays the momentum of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: |
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Decays the parameter value of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: |
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Decays the specified learning rate in each parameter group by gamma once the number of epoch reaches one of the milestones. |
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Decays the specified momentum in each parameter group by gamma once the number of epoch reaches one of the milestones. |
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Decays the specified parameter in each parameter group by gamma once the number of epoch reaches one of the milestones. |
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Sets the learning rate of each parameter group according to the 1cycle learning rate policy. |
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Sets the parameters of each parameter group according to the 1cycle learning rate policy. |
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Decays the learning rate of each parameter group in a polynomial decay scheme. |
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Decays the momentum of each parameter group in a polynomial decay scheme. |
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Decays the parameter value of each parameter group in a polynomial decay scheme. |
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Decays the learning rate of each parameter group by gamma every step_size epochs. |
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Decays the momentum of each parameter group by gamma every step_size epochs. |
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Decays the parameter value of each parameter group by gamma every step_size epochs. |
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Reduce the learning rate of each parameter group when a metric has stopped improving. |
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Reduce the momentum of each parameter group when a metric has stopped improving. |
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Reduce the parameters of each parameter group when a metric has stopped improving. |