Tacotron2+Waveglow/PyT * AMP support * Data preprocessing for Tacotron 2 training * Fixed dropouts on LSTMCells SSD/PyT * script and notebook for inference * AMP support * README update * updates to examples/* BERT/PyT * initial release GNMT/PyT * Default container updated to NGC PyTorch 19.05-py3 * Mixed precision training implemented using APEX AMP * Added inference throughput and latency results on NVIDIA Tesla V100 16G * Added option to run inference on user-provided raw input text from command line NCF/PyT * Updated performance tables. * Default container changed to PyTorch 19.06-py3. * Caching validation negatives between runs Transformer/PyT * new README * jit support added UNet Medical/TF * inference example scripts added * inference benchmark measuring latency added * TRT/TF-TRT support added * README updated GNMT/TF * Performance improvements Small updates (mostly README) for other models.
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5 lines
294 B
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# This script evaluates SSD300 model in FP16 using 32 batch size on 1 GPU
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# Usage: ./SSD300_FP16_EVAL.sh <path to this repository> <path to dataset> <path to checkpoint> <additional flags>
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python $1/main.py --backbone resnet50 --amp --ebs 32 --data $2 --mode evaluation --checkpoint $3 ${@:4}
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