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| ``mx.nd.signsgd.update`` |
| ================================================ |
| |
| Description |
| ---------------------- |
| |
| Update function for SignSGD optimizer. |
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| .. math:: |
| |
| g_t = \nabla J(W_{t-1})\\ |
| W_t = W_{t-1} - \eta_t \text{sign}(g_t) |
| |
| It updates the weights using:: |
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| weight = weight - learning_rate * sign(gradient) |
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| .. note:: - sparse ndarray not supported for this optimizer yet. |
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| |
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| Arguments |
| ------------------ |
| |
| +----------------------------------------+------------------------------------------------------------+ |
| | Argument | Description | |
| +========================================+============================================================+ |
| | ``weight`` | NDArray-or-Symbol. | |
| | | | |
| | | Weight | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``grad`` | NDArray-or-Symbol. | |
| | | | |
| | | Gradient | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``lr`` | float, required. | |
| | | | |
| | | Learning rate | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``wd`` | float, optional, default=0. | |
| | | | |
| | | Weight decay augments the objective function with a | |
| | | regularization term that penalizes large weights. The | |
| | | penalty scales with the square of the magnitude of each | |
| | | weight. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``rescale.grad`` | float, optional, default=1. | |
| | | | |
| | | Rescale gradient to grad = rescale_grad*grad. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``clip.gradient`` | float, optional, default=-1. | |
| | | | |
| | | Clip gradient to the range of [-clip_gradient, | |
| | | clip_gradient] If clip_gradient <= 0, gradient clipping is | |
| | | turned off. grad = max(min(grad, clip_gradient), | |
| | | -clip_gradient). | |
| +----------------------------------------+------------------------------------------------------------+ |
| |
| Value |
| ---------- |
| |
| ``out`` The result mx.ndarray |
| |
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| Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/optimizer_op.cc#L63 |
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