* Improved Trainer Framework
* Support for multiple Inputs and Outputs
* New utilities for loading images, one-hot encoding and more.
* New Gan Framework with multiple layers of abstraction and implementation of
Hinge GANs, GANs with divergence loss, Wasserstein GANs and Relativistic GANs.
* New GAN Applications with support for spectral normalization, conditional batch normalization, self attention, projection gans and resnet generators and discriminators
* A wider range of Initializers
* Enhanced summary function that not only provides you details about number of parameters, layers, input and output sizes
but also provides the number of Flops(Multiply-Adds) for every Linear and Convolution layer in your network.
Now, you can know the exact computational cost of any CNN architecure with just a single function!!!
* Visdom and Tensorboard Support
* Live metrics and loss visualizations, with option to save them permanently
* Support for persisting logs permanently
* Easy to use callbacks
<b>Note: This version of torchfusion is well tested and research-ready, the core framework is now complete, Future releases of TorchFusion will include more specialized functions that will cut across multiple domains of deep learning
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