Optimization of neural nets using TensorRT

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A deep learning model is optimized to its maximum extent via specifying the optimizers and loss functions. This whole process is carried out before the deployment phase by converting a Network built using the common frameworks like TensorFlow, pytorch, etc to a TensorRT network. Conversion to TensorRT network involves converting the layers/operation native to the framework to layers/operations of a TensorRT network. Currently, TensorRT does not support all layers, we propose to create a custom plugin for one such unsupported layer thus optimizing the TensorRT model.

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  1. TECH YOU CAN
  2. artificial intelligence
  3. machine
  4. learning
  5. AI
  6. Deep learning
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