Pytorch Extension Module.


Keywords
deep-learning, deep-neural-networks, machine-learning, ml, neural-network, pytorch
License
MIT
Install
pip install torchex==0.0.16

Documentation

PYTHON version PyPI version Downloads

(WIP) torchex library

torchex library provides advanced Neural Network Layers. You can easily use them like using original pytorch.

Installation

$ pip install torchex

Requirements

  • Pytorch >= 1.0

Documentation

How to use

Lazy Style Model Definition

import torch
import torchex.nn as exnn

net = exnn.Linear(10)
# You don't need to give the size of input for this module.
# This network is equivalent to `nn.Linear(100, 10)`.

x = troch.randn(10, 100)

y = net(x)

torchex.nn list

  • torchex.nn.Pass
  • torchex.nn.Flatten
  • torchex.nn.Linear
    • Lazy style
  • torchex.nn.Conv1d
    • Lazy style
  • torchex.nn.Conv2d
    • Lazy style
  • torchex.nn.Conv3d
    • Lazy style
  • torchex.nn.Conv2dLocal
  • torchex.nn.GlobalAvgPool1d
  • torchex.nn.GlobalAvgPool2d
  • torchex.nn.GlobalMaxPool1d
  • torchex.nn.GlobalMaxPool2d
  • torchex.nn.MaxAvgPool2d
  • torch.nn.Crop2d
  • torch.nn.Crop3d
  • torch.nn.MLPConv2d
  • torch.nn.UpsampleConvLayer
  • torch.nn.CordConv2d
  • torch.nn.DFT1d
  • torch.nn.DFT2d
  • torch.nn.PeriodicPad2d
  • torch.nn.PeriodicPad3d
  • torch.nn.Highway
  • torch.nn.Inception
  • torch.nn.InceptionBN
  • torch.nn.IndRNNCell
  • torch.nn.IndRNNTanhCell
  • torch.nn.IndRNNReLuCell
  • torch.nn.IndRNN
  • torch.nn.GraphLinear
  • torch.nn.GraphConv
  • torch.nn.SparseMM
  • torch.nn.GraphBatchNrom

torchex.data.transforms

  • torchex.data.transforms.PadRandomSift
  • torchex.data.transforms.RandomResize

torchex.data.attribute

for visualization

  • torchex.attribute.IntegratedGradients