This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2
pip install pyradox
or
pip install git+https://github.com/Ritvik19/pyradox.git
| 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 |
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| 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 |
| 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 |
| Seg Net | Generalised Implementation of SegNet for Image Segmentation Applications | 4D tensor with shape (batch_shape, rows, cols, channels) | 4D tensor with shape (batch_shape, rows, cols, channels) | check here |
| U Net | Generalised Implementation of UNet for Image Segmentation Applications | 4D tensor with shape (batch_shape, rows, cols, channels) | 4D tensor with shape (batch_shape, rows, cols, channels) | check here |
| 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 |