versions/1.6.0/api/r/docs/_sources/api/mx.symbol.sgd_update.rst

``mx.symbol.sgd_update``
================================================

Description
----------------------

Update function for Stochastic Gradient Descent (SGD) optimizer.

It updates the weights using::

	 weight = weight - learning_rate * (gradient + wd * weight)
	 
	 However, if gradient is of ``row_sparse`` storage type and ``lazy_update`` is True,
only the row slices whose indices appear in grad.indices are updated::

	 for row in gradient.indices:
	 weight[row] = weight[row] - learning_rate * (gradient[row] + wd * weight[row])
	 
	 
	 

Usage
----------

.. code:: r

	mx.symbol.sgd_update(...)

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).                                           |
+----------------------------------------+------------------------------------------------------------+
| ``lazy.update``                        | boolean, optional, default=1.                              |
|                                        |                                                            |
|                                        | If true, lazy updates are applied if gradient's stype is   |
|                                        | row_sparse.                                                |
+----------------------------------------+------------------------------------------------------------+
| ``name``                               | string, optional.                                          |
|                                        |                                                            |
|                                        | Name of the resulting symbol.                              |
+----------------------------------------+------------------------------------------------------------+

Value
----------

``out`` The result mx.symbol


Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/optimizer_op.cc#L524