State of the Art Neural Networks for Deep Learning

Overview

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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Ritvik Rastogi
I have been writing code since 2016, and taught myself a handful of skills and programming languages. I love solving problems by writing code
Ritvik Rastogi
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