Custom Training Loops

Train deep learning networks using custom training loops

If the trainingOptions function does not provide the training options that you need for your task, or custom output layers do not support the loss functions that you need, then you can define a custom training loop. For networks that cannot be created using layer graphs, you can define custom networks as a function. To learn more, see Define Custom Training Loops, Loss Functions, and Networks.

Functions

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Custom Training Loops

`dlnetwork`	Deep learning network for custom training loops (Since R2019b)
`trainingProgressMonitor`	Monitor and plot training progress for deep learning custom training loops (Since R2022b)
`minibatchqueue`	Create mini-batches for deep learning (Since R2020b)
`padsequences`	Pad or truncate sequence data to same length (Since R2021a)
`dlarray`	Deep learning array for customization (Since R2019b)
`dlgradient`	Compute gradients for custom training loops using automatic differentiation (Since R2019b)
`dlfeval`	Evaluate deep learning model for custom training loops (Since R2019b)

Loss Operations

`crossentropy`	Cross-entropy loss for classification tasks (Since R2019b)
`l1loss`	L₁ loss for regression tasks (Since R2021b)
`l2loss`	L₂ loss for regression tasks (Since R2021b)
`huber`	Huber loss for regression tasks (Since R2021a)
`mse`	Half mean squared error (Since R2019b)
`ctc`	Connectionist temporal classification (CTC) loss for unaligned sequence classification (Since R2021a)

Topics

Train Network Using Custom Training Loop
This example shows how to train a network that classifies handwritten digits with a custom learning rate schedule.
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.
Define Custom Training Loops, Loss Functions, and Networks
Learn how to define and customize deep learning training loops, loss functions, and networks using automatic differentiation.
Specify Training Options in Custom Training Loop
Learn how to specify common training options in a custom training loop.
Monitor Custom Training Loop Progress
Track and plot custom training loop progress.
Detect Issues During Deep Neural Network Training
This example shows how to automatically detect issues while training a deep neural network.