package.experimental.train.optimizer.optimizer.Optimizer Class Reference

Public Member Functions
None	__init__ (self, float learning_rate=0.001, int nums_trainable_ops=trainable_ops.ALL)

Detailed Description

Base class for optimizers.

Definition at line 4 of file optimizer.py.

Constructor & Destructor Documentation

__init__()

None package.experimental.train.optimizer.optimizer.Optimizer.__init__	(		self,
		float	learning_rate = 0.001,
		int	nums_trainable_ops = trainable_ops.ALL
	)

Initialize the optimizer.

Args:
    learning_rate (float): The learning rate for optimization.
    nums_trainable_ops (int or enum): Number of trainable ops or enum mask.

Reimplemented in package.experimental.train.optimizer.adam.Adam, and package.experimental.train.optimizer.sgd.SGD.

Definition at line 8 of file optimizer.py.

                 nums_trainable_ops: int = trainable_ops.ALL) -> None:
        """
        Initialize the optimizer.
 
        Args:
            learning_rate (float): The learning rate for optimization.
            nums_trainable_ops (int or enum): Number of trainable ops or enum mask.
        """
        self.learning_rate: float = learning_rate
        self.nums_trainable_ops: int = nums_trainable_ops

References onert_micro::OMTrainingContext.learning_rate, nnfw_train_info.learning_rate, and onert::ir::train::OptimizerInfo.learning_rate.

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The documentation for this class was generated from the following file:

• runtime/onert/api/python/package/experimental/train/optimizer/optimizer.py