package torch

You can search for identifiers within the package.

in-package search v0.2.0

torch
- Torch
  - Checkpointing
  - Cifar_helper
  - Cuda
  - Dataset_helper
  - Device
  - Ivalue
  - Layer
    
    Gru
    
    Lstm
  - Mnist_helper
  - Module
  - Optimizer
    
    Clip_grad
    
    Linear_interpolation
  - Scalar
  - Serialize
  - Tensor
  - Text_helper
  - Var_store
    
    Init
    
    Tensor_id
torch.core
- Torch_core
  - Device
  - Kind
  - Reduction
  - Torch_bindings
    
    C
    
    Cuda
    
    Ivalue
    
    Module
    
    Optimizer
    
    Scalar
    
    Serialize
    
    Tensor
    
    TensorG
  - Torch_bindings_generated
    
    C
    
    C0
    
    C1
    
    C10
    
    C11
    
    C12
    
    C13
    
    C14
    
    C15
    
    C16
    
    C17
    
    C18
    
    C19
    
    C2
    
    C20
    
    C21
    
    C22
    
    C23
    
    C24
    
    C25
    
    C3
    
    C4
    
    C5
    
    C6
    
    C7
    
    C8
    
    C9
  - Torch_generated
  - Wrapper
    
    Cuda
    
    Ivalue
    
    Tag
    
    Module
    
    Optimizer
    
    Scalar
    
    Serialize
    
    Tensor
  - Wrapper_generated
    
    C
    
    Cuda
    
    Ivalue
    
    Module
    
    Optimizer
    
    Scalar
    
    Serialize
    
    Tensor
    
    TensorG
  - Wrapper_generated_intf
    
    S
torch.toplevel
- Torch_toplevel
torch.vision
- Torch_vision
  - Alexnet
  - Densenet
  - Efficientnet
  - Image
    
    Loader
  - Imagenet
    
    Classes
    
    Loader
  - Inception
  - Mobilenet
  - Resnet
  - Squeezenet
  - Stb_image
  - Stb_image_write
  - Vgg

Legend:
Library
Module
Module type
Parameter
Class
Class type

type t

val adam : 
  learning_rate:Base.float ->
  beta1:Base.float ->
  beta2:Base.float ->
  weight_decay:Base.float ->
  eps:Base.float ->
  t

val rmsprop : 
  learning_rate:Base.float ->
  alpha:Base.float ->
  eps:Base.float ->
  weight_decay:Base.float ->
  momentum:Base.float ->
  centered:Base.bool ->
  t

val sgd : 
  learning_rate:Base.float ->
  momentum:Base.float ->
  dampening:Base.float ->
  weight_decay:Base.float ->
  nesterov:Base.bool ->
  t

val set_learning_rate : t -> Base.float -> Base.unit

val set_momentum : t -> Base.float -> Base.unit

val add_parameters : t -> Tensor.t Base.list -> Base.unit

val zero_grad : t -> Base.unit

val step : t -> Base.unit