docsexp

Subpackages

• docsexp.models
  • docsexp.models.cnn
  • docsexp.models.resnet

Package Contents

Classes

MyClass	Test for MyClass
ConvNet	Convolutional network

Functions

conv3x3(in_channels: int, out_channels: int, stride: int = 1) → torch.nn.Module
calculate()

docsexp.conv3x3(in_channels: int, out_channels: int, stride: int = 1) → torch.nn.Module

docsexp.calculate()

class docsexp.MyClass(num, time, age)

Bases: object

Test for MyClass

Parameters

• num (int) – number

• age (int) – age of class

• time (int) – time of class

class docsexp.ConvNet(num_classes: int = 10)

Bases: torch.nn.Module

Convolutional network

Parameters

num_classes (int) – number of output classes

Example

>>> from docsexp.models import ConvNet
>>> num_classes = 10
>>> model = ConvNet(num_classes)

forward(self, x)

Forward function for CNN.

Parameters

x (torch.Tensor) – input features