th: multiplier to the ResNet width (number of filters)
dropout_rate: dropout rate
include_top: whether to include the fully-connected</p>
<blockquote>
<div>layer at the top of the network.</div></blockquote>
<dl class="docutils">
<dt>weights: one of <cite>None</cite> (random initialization) or</dt>
<dd>&quot;cifar10&quot; (pre-training on CIFAR-10)..</dd>
<dt>input_tensor: optional Keras tensor (i.e. output of <cite>layers.Input()</cite>)</dt>
<dd>to use as image input for the model.</dd>
<dt>input_shape: o