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TensorRT optimizes the network by stating layers and optimizing kernel selection for dealt latency, throughput, power efficiency and history consumption. Memory usage The tossing and device memory that need to be shared to do inference on a foundation depends on the algorithms used.
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It workshops how you can take an underwhelming model built with a few learning framework and use that to work a TensorRT perception using the provided parsers.
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