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mindspore.nn.thor
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==================
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.. py:function:: mindspore.nn.thor(net, learning_rate, damping, momentum, weight_decay=0.0, loss_scale=1.0, batch_size=32, use_nesterov=False, decay_filter=<function <lambda> at 0x0000029724CFA048>, split_indices=None, enable_clip_grad=False, frequency=100)
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.. py:function:: mindspore.nn.thor(net, learning_rate, damping, momentum, weight_decay=0.0, loss_scale=1.0, batch_size=32, use_nesterov=False, decay_filter=lambda x: x.name not in [], split_indices=None, enable_clip_grad=False, frequency=100)
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通过二阶算法THOR更新参数。
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@ -325,9 +325,9 @@ def thor(net, learning_rate, damping, momentum, weight_decay=0.0, loss_scale=1.0
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TypeError: If `loss_scale`, `momentum` or `frequency` is not a float.
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TypeError: If `weight_decay` is neither float nor int.
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TypeError: If `use_nesterov` is not a bool.
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TypeError: If `frequency` is not int.
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ValueError: If `loss_scale` is less than or equal to 0.
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ValueError: If `weight_decay` or `momentum` is less than 0.
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ValueError: If `frequency` is not int.
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ValueError: If `frequency` is less than 2.
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Supported Platforms:
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