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Title: GitHub - GeeCastro/SSDNvidiaDocker: Deep Learning Examples · GitHub

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Description: Deep Learning Examples. Contribute to GeeCastro/SSDNvidiaDocker development by creating an account on GitHub.

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Apache-2.0 licensehttps://github.com/GeeCastro/SSDNvidiaDocker
https://github.com/GeeCastro/SSDNvidiaDocker#ssd512-v11-for-pytorch
https://github.com/GeeCastro/SSDNvidiaDocker#copy-from-nvidia-docker-image-for-ssd300
https://github.com/GeeCastro/SSDNvidiaDocker#table-of-contents
Model overviewhttps://github.com/GeeCastro/SSDNvidiaDocker#model-overview
Model architecturehttps://github.com/GeeCastro/SSDNvidiaDocker#model-architecture
Default configurationhttps://github.com/GeeCastro/SSDNvidiaDocker#default-configuration
Feature support matrixhttps://github.com/GeeCastro/SSDNvidiaDocker#feature-support-matrix
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Mixed precision traininghttps://github.com/GeeCastro/SSDNvidiaDocker#mixed-precision-training
Enabling mixed precisionhttps://github.com/GeeCastro/SSDNvidiaDocker#enabling-mixed-precision
Enabling TF32https://github.com/GeeCastro/SSDNvidiaDocker#enabling-tf32
Setuphttps://github.com/GeeCastro/SSDNvidiaDocker#setup
Requirementshttps://github.com/GeeCastro/SSDNvidiaDocker#requirements
Quick Start Guidehttps://github.com/GeeCastro/SSDNvidiaDocker#quick-start-guide
Advancedhttps://github.com/GeeCastro/SSDNvidiaDocker#advanced
Scripts and sample codehttps://github.com/GeeCastro/SSDNvidiaDocker#scripts-and-sample-code
Parametershttps://github.com/GeeCastro/SSDNvidiaDocker#parameters
Command-line optionshttps://github.com/GeeCastro/SSDNvidiaDocker#command-line-options
Getting the datahttps://github.com/GeeCastro/SSDNvidiaDocker#getting-the-data
Dataset guidelineshttps://github.com/GeeCastro/SSDNvidiaDocker#dataset-guidelines
Data preprocessinghttps://github.com/GeeCastro/SSDNvidiaDocker#data-preprocessing
Data augmentationhttps://github.com/GeeCastro/SSDNvidiaDocker#data-augmentation
Training processhttps://github.com/GeeCastro/SSDNvidiaDocker#training-process
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Inference processhttps://github.com/GeeCastro/SSDNvidiaDocker#inference-process
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Inference performance benchmarkhttps://github.com/GeeCastro/SSDNvidiaDocker#inference-performance-benchmark
https://github.com/GeeCastro/SSDNvidiaDocker#model-overview
SSD: Single Shot MultiBox Detectorhttps://arxiv.org/abs/1512.02325
Speed/accuracy trade-offs for modern convolutional object detectorshttps://arxiv.org/abs/1611.10012
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minuteshttps://arxiv.org/abs/1807.11205
NVIDIA DALIhttps://github.com/NVIDIA/DALI
https://github.com/GeeCastro/SSDNvidiaDocker#model-architecture
https://github.com/GeeCastro/SSDNvidiaDocker/blob/SSD512/img/ssd_diagram.png
Single Shot MultiBox Detector paperhttps://arxiv.org/abs/1512.02325
https://github.com/GeeCastro/SSDNvidiaDocker#default-configuration
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hourhttps://arxiv.org/abs/1706.02677
https://github.com/GeeCastro/SSDNvidiaDocker#feature-support-matrix
APEX AMPhttps://github.com/NVIDIA/apex
APEX DDPhttps://pytorch.org/tutorials/intermediate/ddp_tutorial.html
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DALI documentationhttps://docs.nvidia.com/deeplearning/sdk/dali-developer-guide/docs/index.html
https://github.com/GeeCastro/SSDNvidiaDocker#mixed-precision-training
Mixed precisionhttps://arxiv.org/abs/1710.03740
Tensor Coreshttps://developer.nvidia.com/tensor-cores
CUDA 8https://devblogs.nvidia.com/parallelforall/tag/fp16/
Mixed Precision Traininghttps://arxiv.org/abs/1710.03740
Training With Mixed Precisionhttps://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/index.html
Mixed-Precision Training of Deep Neural Networkshttps://devblogs.nvidia.com/mixed-precision-training-deep-neural-networks/
NVIDIA Apex: Tools for Easy Mixed-Precision Training in PyTorchhttps://devblogs.nvidia.com/apex-pytorch-easy-mixed-precision-training/
https://github.com/GeeCastro/SSDNvidiaDocker#enabling-mixed-precision
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NVIDIA A100https://www.nvidia.com/en-us/data-center/a100/
TensorFloat-32 in the A100 GPU Accelerates AI Training, HPC up to 20xhttps://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-precision-format/
https://github.com/GeeCastro/SSDNvidiaDocker#glossary
C4W3L01 coursehttps://www.youtube.com/watch?v=GSwYGkTfOKk
paper authored by Liu at al.https://arxiv.org/abs/1512.02325
paper authored by He et al.https://arxiv.org/abs/1512.03385
https://github.com/GeeCastro/SSDNvidiaDocker#setup
https://github.com/GeeCastro/SSDNvidiaDocker#requirements
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Getting Started Using NVIDIA GPU Cloudhttps://docs.nvidia.com/ngc/ngc-getting-started-guide/index.html
Accessing And Pulling From The NGC Container Registryhttps://docs.nvidia.com/deeplearning/dgx/user-guide/index.html#accessing_registry
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https://github.com/GeeCastro/SSDNvidiaDocker#quick-start-guide
COCO 2017http://cocodataset.org/#download
Advancedhttps://github.com/GeeCastro/SSDNvidiaDocker#advanced
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https://github.com/GeeCastro/SSDNvidiaDocker#scripts-and-sample-code
https://github.com/GeeCastro/SSDNvidiaDocker#parameters
https://github.com/GeeCastro/SSDNvidiaDocker#the-script-mainpy
https://github.com/GeeCastro/SSDNvidiaDocker#common-parameters
https://github.com/GeeCastro/SSDNvidiaDocker#training-related
https://github.com/GeeCastro/SSDNvidiaDocker#evaluation-related
https://github.com/GeeCastro/SSDNvidiaDocker#utility-parameters
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https://github.com/GeeCastro/SSDNvidiaDocker#getting-the-data
val2017http://cocodataset.org/#download
https://github.com/GeeCastro/SSDNvidiaDocker#dataset-guidelines
the COCO documentationhttp://cocodataset.org/#format-data
https://github.com/GeeCastro/SSDNvidiaDocker#data-preprocessing
https://github.com/GeeCastro/SSDNvidiaDocker#data-augmentation
SSD: Single Shot MultiBox Detectorhttps://arxiv.org/abs/1512.02325
https://github.com/GeeCastro/SSDNvidiaDocker#training-process
https://github.com/GeeCastro/SSDNvidiaDocker#evaluation-process
https://github.com/GeeCastro/SSDNvidiaDocker#inference-process
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