This package contains various models, architectures, and building blocks covered in the Kadenze Academy program including: Autoencoders Character Level Recurrent Neural Network (CharRNN) Conditional Pixel CNN CycleGAN Deep Convolutional Generative Adversarial Networks (DCGAN) Deep Dream Deep Recurrent Attentive Writer (DRAW) Gated Convolution Generative Adversarial Networks (GAN) Global Vector Embeddings (GloVe) Illustration2Vec Inception Mixture Density Networks (MDN) PixelCNN NSynth Residual Networks Sequence2Seqeuence (Seq2Seq) w/ Attention (both bucketed and dynamic rnn variants available) Style Net Variational Autoencoders (VAE) Variational Autoencoding Generative Adversarial Networks (VAEGAN) Video Style Net VGG16 WaveNet / Fast WaveNet Generation w/ Queues / WaveNet Autoencoder (NSynth) Word2Vec and more. It also includes various datasets, preprocessing, batch generators, input pipelines, and plenty more for datasets such as: CELEB CIFAR Cornell MNIST TedLium LibriSpeech VCTK and plenty of utilities for working with images, GIFs, sound (wave) files, MIDI, video, text, TensorFlow, TensorBoard, and their graphs. Examples of each module's use can be found in the tests folder.
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