自定义层
为深度学习定义自定义层
对于大多数任务,您可以使用内置层。如果没有您的任务所需的内置层,则可以定义您自己的自定义层。您可以定义具有可学习参数和状态参数的自定义层。定义自定义层后,您可以检查该层是否有效,是否与 GPU 兼容,以及是否输出正确定义的梯度。要查看支持的层的列表,请参阅深度学习层列表。
函数
主题
自定义层概述
- 定义自定义深度学习层
了解如何定义自定义深度学习层。 - Check Custom Layer Validity
Learn how to check the validity of custom deep learning layers.
定义自定义层
- Define Custom Deep Learning Layer with Learnable Parameters
This example shows how to define a SReLU layer and use it in a convolutional neural network. - Define Custom Deep Learning Layer with Multiple Inputs
This example shows how to define a custom weighted addition layer and use it in a convolutional neural network. - Define Custom Deep Learning Layer with Formatted Inputs
This example shows how to define a custom layer with formatteddlarray
inputs. - Define Custom Recurrent Deep Learning Layer
This example shows how to define a peephole LSTM layer and use it in a neural network. - Specify Custom Layer Backward Function
This example shows how to define a SReLU layer and specify a custom backward function. - Custom Layer Function Acceleration
Accelerate custom layer forward and predict functions by caching and reusing traces. - Define Custom Deep Learning Layer for Code Generation
This example shows how to define a SReLU layer that supports code generation.
网络合成和嵌套层
- Deep Learning Network Composition
Define custom layers that contain neural networks. - Define Nested Deep Learning Layer Using Network Composition
This example shows how to define a nested custom deep learning layer. - Train Network with Custom Nested Layers
This example shows how to create and train a network with nested layers defined using network composition. - Weight Tying Using Nested Layer
This example shows how to implement weight tying using a nested layer.