DeepLearningExamples/PyTorch/Detection/SSD/examples/SSD300_FP16_EVAL.sh
Przemek Strzelczyk a644350589 Updating models and adding BERT/PyT
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.
2019-07-16 21:13:08 +02:00

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# This script evaluates SSD300 model in FP16 using 32 batch size on 1 GPU
# Usage: ./SSD300_FP16_EVAL.sh <path to this repository> <path to dataset> <path to checkpoint> <additional flags>
python $1/main.py --backbone resnet50 --amp --ebs 32 --data $2 --mode evaluation --checkpoint $3 ${@:4}