自定义训练循环
为序列和表格数据自定义深度学习训练循环和损失函数
如果 trainingOptions
函数不提供任务所需的训练选项,或您有 trainnet
函数不支持的损失函数,您可以定义自定义训练循环。对于无法指定为由层组成的网络的模型,可以将模型定义为函数。要了解详细信息,请参阅定义自定义训练循环、损失函数和网络。
函数
主题
自定义训练循环
- Train Deep Learning Model in MATLAB
Learn how to training deep learning models in MATLAB®. - 定义自定义训练循环、损失函数和网络
了解如何定义和自定义深度学习训练循环、损失函数和模型。 - Train Sequence Classification Network Using Custom Training Loop
This example shows how to train a network that classifies sequences with a custom learning rate schedule. - Monitor Custom Training Loop Progress
Track and plot custom training loop progress. - Train Network with Multiple Outputs
This example shows how to train a deep learning network with multiple outputs that predict both labels and angles of rotations of handwritten digits. - Classify Videos Using Deep Learning with Custom Training Loop
This example shows how to create a network for video classification by combining a pretrained image classification model and a sequence classification network. - Train Neural ODE Network
This example shows how to train an augmented neural ordinary differential equation (ODE) network. - Solve Ordinary Differential Equation Using Neural Network
This example shows how to solve an ordinary differential equation (ODE) using a neural network. - Speed Up Deep Neural Network Training
Learn how to accelerate deep neural network training.
自动微分
- Create Bidirectional LSTM (BiLSTM) Function
This example shows how to create a bidirectional long-short term memory (BiLSTM) function for custom deep learning functions. (自 R2023b 起) - List of Functions with dlarray Support
View the list of functions that supportdlarray
objects. - Automatic Differentiation Background
Learn how automatic differentiation works. - Use Automatic Differentiation In Deep Learning Toolbox
How to use automatic differentiation in deep learning.