pyradox

This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2

Installation

pip install git+https://github.com/Ritvik19/pyradox.git

Usage

Modules

Module	Description	Input Shape	Output Shape	Usage
Rescale	A layer that rescales the input: `x_out = (x_in -mu) / sigma`	Arbitrary	Same shape as input	check here
Convolution 2D	Applies 2D Convolution followed by Batch Normalization (optional) and Dropout (optional)	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Densely Connected	Densely Connected Layer followed by Batch Normalization (optional) and Dropout (optional)	2D tensor with shape (batch_size, input_dim)	2D tensor with shape (batch_size, n_units)	check here
DenseNet Convolution Block	A Convolution block for DenseNets	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
DenseNet Convolution Block	A Convolution block for DenseNets	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
DenseNet Transition Block	A Transition block for DenseNets	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Dense Skip Connection	Implementation of a skip connection for densely connected layer	2D tensor with shape (batch_size, input_dim)	2D tensor with shape (batch_size, n_units)	check here
VGG Module	Implementation of VGG Modules with slight modifications, Applies multiple 2D Convolution followed by Batch Normalization (optional), Dropout (optional) and MaxPooling	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inception Conv	Implementation of 2D Convolution Layer for Inception Net, Convolution Layer followed by Batch Normalization, Activation and optional Dropout	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inception Block	Implementation on Inception Mixing Block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Xception Block	A customised implementation of Xception Block (Depthwise Separable Convolutions)	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net Block	Implementation of Efficient Net Block (Depthwise Separable Convolutions)	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Conv Skip Connection	Implementation of Skip Connection for Convolution Layer	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net Block	Customized Implementation of ResNet Block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net V2 Block	Customized Implementation of ResNetV2 Block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res NeXt Block	Customized Implementation of ResNeXt Block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inception Res Net Conv 2D	Implementation of Convolution Layer for Inception Res Net: Convolution2d followed by Batch Norm	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inception Res Net Block	Implementation of Inception-ResNet block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	block 8 Block 17 Block 35
NAS Net Separable Conv Block	Adds 2 blocks of Separable Conv Batch Norm	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
NAS Net Adjust Block	Adjusts the input `previous path` to match the shape of the `input`
NAS Net Normal A Cell	Normal cell for NASNet-A
NAS Net Reduction A Cell	Reduction cell for NASNet-A
Mobile Net Conv Block	Adds an initial convolution layer with batch normalization and activation	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Mobile Net Depth Wise Conv Block	Adds a depthwise convolution block. A depthwise convolution block consists of a depthwise conv, batch normalization, activation, pointwise convolution, batch normalization and activation	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inverted Res Block	Adds an Inverted ResNet block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
SEBlock	Adds a Squeeze Excite Block	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here

ConvNets

Module	Description	Input Shape	Output Shape	Usage
Generalized Dense Nets	A generalization of Densely Connected Convolutional Networks (Dense Nets)	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Densely Connected Convolutional Network 121	A modified implementation of Densely Connected Convolutional Network 121	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Densely Connected Convolutional Network 169	A modified implementation of Densely Connected Convolutional Network 169	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Densely Connected Convolutional Network 201	A modified implementation of Densely Connected Convolutional Network 201	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Generalized VGG	A generalization of VGG network	4D tensor with shape (batch_shape, rows, cols, channels)	4D or 2D tensor	usage 1 usage 2
VGG 16	A modified implementation of VGG16 network	4D tensor with shape (batch_shape, rows, cols, channels)	2D tensor with shape (batch_shape, new_dim)	usage 1 usage 2
VGG 19	A modified implementation of VGG19 network	4D tensor with shape (batch_shape, rows, cols, channels)	2D tensor with shape (batch_shape, new_dim)	usage 1 usage 2
Inception V3	Customized Implementation of Inception Net	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Generalized Xception	Generalized Implementation of XceptionNet (Depthwise Separable Convolutions)	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Xception Net	A Customised Implementation of XceptionNet	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net	Generalized Implementation of Effiecient Net	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B0	Customized Implementation of Efficient Net B0	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B1	Customized Implementation of Efficient Net B1	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B2	Customized Implementation of Efficient Net B2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B3	Customized Implementation of Efficient Net B3	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B4	Customized Implementation of Efficient Net B4	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B5	Customized Implementation of Efficient Net B5	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B6	Customized Implementation of Efficient Net B6	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Efficient Net B7	Customized Implementation of Efficient Net B7	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net	Customized Implementation of Res Net	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 50	Customized Implementation of Res Net 50	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 101	Customized Implementation of Res Net 101	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 152	Customized Implementation of Res Net 152	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net V2	Customized Implementation of Res Net V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 50 V2	Customized Implementation of Res Net 50 V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 101 V2	Customized Implementation of Res Net 101 V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res Net 152 V2	Customized Implementation of Res Net 152 V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res NeXt	Customized Implementation of Res NeXt	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res NeXt 50	Customized Implementation of Res NeXt 50	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res NeXt 101	Customized Implementation of Res NeXt 101	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Res NeXt 152	Customized Implementation of Res NeXt 152	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
Inception Res Net V2	Customized Implementation of Inception Res Net V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
NAS Net	Generalised Implementation of NAS Net	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
NAS Net Mobile	Customized Implementation of NAS Net Mobile	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
NAS Net Large	Customized Implementation of NAS Net Large	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	check here
MobileNet	Customized Implementation of MobileNet	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	usage 1 usage 2
Mobile Net V2	Customized Implementation of Mobile Net V2	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	usage 1 usage 2
Mobile Net V3	Customized Implementation of Mobile Net V3	4D tensor with shape (batch_shape, rows, cols, channels)	4D tensor with shape (batch_shape, new_rows, new_cols, new_channels)	usage 1 usage 2

DenseNets

Module	Description	Input Shape	Output Shape	Usage
Densely Connected Network	Network of Densely Connected Layers followed by Batch Normalization (optional) and Dropout (optional)	2D tensor with shape (batch_size, input_dim)	2D tensor with shape (batch_size, new_dim)	check here
Densely Connected Resnet	Network of skip connections for densely connected layer	2D tensor with shape (batch_size, input_dim)	2D tensor with shape (batch_size, new_dim)	check here

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55 Oct 25, 2022

Fix for _pooling_factor of GeneralizedUNet

if len(encoder_config) > 1 an exception was raised in GeneralizedUNet._pooling_factor: only 1st iteration will be an array.

btw great repo, big thx for it!

opened by p4vv37 1

State of the Art Neural Networks for Deep Learning

Related tags

Overview

pyradox

Installation

Usage

Modules

ConvNets

DenseNets

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Comments

Fix for _pooling_factor of GeneralizedUNet

Releases(v1.0.1)

v1.0.1(Apr 9, 2021)

v0.18.10(Apr 9, 2021)

v0.17.10(Jan 9, 2021)

Owner

Ritvik Rastogi

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