• Access pre-trained models. »
  • Define and visualize arbitrary nets. »
  • Manipulate neural net symbolically. »
  • Access detailed training information. »
  • Measure net performances. »
  • Train a network on multiple GPUs. »
  • Train networks on text or audio data. »
  • Create attention mechanisms. »
  • Define custom recurrent layers. »
  • Generate sequences from recurrent layers efficiently. »
  • Train convolution nets on sequences. »
  • Train transformer nets. »
  • Train capsule nets. »
  • Train self-normalizing neural nets. »
  • Access reinforcement learning environments. »

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