Module burn::module

Module for the neural network module.

Structs

• Attribute
  Attribute to print in the display method.
• ConstantRecord
  Record used for constant type implementing the module trait.
• Content
  Struct to store the attributes of a module for formatting.
• DisplaySettings
  Custom module display settings.
• Ignored
  Container to satisfy the Module trait for types that are not modules.
• Param
  Parameters are the fundamental building blocks of modules where they serve as containers for tensors that can be updated during training, and loaded during inference. If you don’t want to save the tensors with a record and/or don’t want to update it during training, you don’t need this type to wrap your tensor.
• ParamId
  Parameter ID.
• Quantizer
  Describes how to quantize a module.
• RunningState
  A state that can be updated during the forward pass while being thread safe.

Traits

• AutodiffModule
  Module with auto-differentiation backend.
• Module
  Trait for all neural network modules.
• ModuleDisplay
  Trait to implement custom display settings for a module.
• ModuleDisplayDefault
  Default display settings for a module.
• ModuleMapper
  Module mapper trait.
• ModuleVisitor
  Module visitor trait.
• Parameter
  Trait that defines what is necessary for a type to be a parameter.

Functions

• extract_type_name
  Extracts the short name of a type T
• list_param_ids
  List all the parameter ids in a module.

Type Aliases

• Devices
  Type alias to Vec<B::Device> which supports no_std environments, but automatically using the alloc crate.

Derive Macros

• Module
  Derive macro for the module.