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<div class="section" id="optimizer">
<h1>Optimizer<a class="headerlink" href="#optimizer" title="永久链接至标题">¶</a></h1>
<div class="section" id="id1">
<h2>Optimizer<a class="headerlink" href="#id1" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">Optimizer</code><span class="sig-paren">(</span><em>global_step=None</em>, <em>regularization=None</em><span class="sig-paren">)</span></dt>
<dd><p>Optimizer Base class.</p>
<p>Define the common interface of an optimizer.
User should not use this class directly,
but need to use one of it’s implementation.</p>
<dl class="method">
<dt>
<code class="descname">create_optimization_pass</code><span class="sig-paren">(</span><em>parameters_and_grads</em>, <em>loss</em>, <em>startup_program=None</em><span class="sig-paren">)</span></dt>
<dd><p>Add optimization operators to update gradients to variables.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>loss</strong> – the target that this optimization is for.</li>
<li><strong>parameters_and_grads</strong> – a list of (variable, gradient) pair to update.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">a list of operators that will complete one step of
optimization. This will include parameter update ops, global step
update ops and any other custom ops required by subclasses to manage
their internal state.
:param startup_program:</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">返回类型:</th><td class="field-body"><p class="first last">return_op_list</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt>
<code class="descname">minimize</code><span class="sig-paren">(</span><em>loss</em>, <em>startup_program=None</em>, <em>parameter_list=None</em>, <em>no_grad_set=None</em><span class="sig-paren">)</span></dt>
<dd><p>Add operations to minimize <cite>loss</cite> by updating <cite>parameter_list</cite>.</p>
<p>This method combines interface <cite>append_backward_ops()</cite> and
<cite>create_optimization_pass()</cite> into one.</p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="sgdoptimizer">
<h2>SGDOptimizer<a class="headerlink" href="#sgdoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">SGDOptimizer</code><span class="sig-paren">(</span><em>learning_rate</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Simple SGD optimizer without any state.</p>
</dd></dl>
</div>
<div class="section" id="momentumoptimizer">
<h2>MomentumOptimizer<a class="headerlink" href="#momentumoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">MomentumOptimizer</code><span class="sig-paren">(</span><em>learning_rate</em>, <em>momentum</em>, <em>use_nesterov=False</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Simple Momentum optimizer with velocity state</p>
</dd></dl>
</div>
<div class="section" id="adagradoptimizer">
<h2>AdagradOptimizer<a class="headerlink" href="#adagradoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">AdagradOptimizer</code><span class="sig-paren">(</span><em>learning_rate</em>, <em>epsilon=1e-06</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Simple Adagrad optimizer with moment state</p>
</dd></dl>
</div>
<div class="section" id="adamoptimizer">
<h2>AdamOptimizer<a class="headerlink" href="#adamoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">AdamOptimizer</code><span class="sig-paren">(</span><em>learning_rate=0.001</em>, <em>beta1=0.9</em>, <em>beta2=0.999</em>, <em>epsilon=1e-08</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Implements the Adam Optimizer</p>
</dd></dl>
</div>
<div class="section" id="adamaxoptimizer">
<h2>AdamaxOptimizer<a class="headerlink" href="#adamaxoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">AdamaxOptimizer</code><span class="sig-paren">(</span><em>learning_rate=0.001</em>, <em>beta1=0.9</em>, <em>beta2=0.999</em>, <em>epsilon=1e-08</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Implements the Adamax Optimizer</p>
</dd></dl>
</div>
<div class="section" id="decayedadagradoptimizer">
<h2>DecayedAdagradOptimizer<a class="headerlink" href="#decayedadagradoptimizer" title="永久链接至标题">¶</a></h2>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.fluid.optimizer.</code><code class="descname">DecayedAdagradOptimizer</code><span class="sig-paren">(</span><em>learning_rate</em>, <em>decay=0.95</em>, <em>epsilon=1e-06</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Simple Decayed Adagrad optimizer with moment state</p>
</dd></dl>
</div>
</div>
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