PyTorch1.9发布了！torchvision支持SSD模型！
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近日，PyTorch1.9发布了，主要更新如下：
Major improvements to support scientific computing, including torch.linalg, torch.special, and Complex Autograd
Major improvements in on-device binary size with Mobile Interpreter
Native support for elastic-fault tolerance training through the upstreaming of TorchElastic into PyTorch Core
Major updates to the PyTorch RPC framework to support large scale distributed training with GPU support
New APIs to optimize performance and packaging for model inference deployment
Support for Distributed training, GPU utilization and SM efficiency in the PyTorch Profiler
另外torchvision更新至0.10版本，新增SSD模型：
import torch
import torchvision
# Original SSD variant
x = [torch.rand(3, 300, 300), torch.rand(3, 500, 400)]
m_detector = torchvision.models.detection.ssd300_vgg16(pretrained=True)
m_detector.eval()
predictions = m_detector(x)
# Mobile-friendly SSDlite variant
x = [torch.rand(3, 320, 320), torch.rand(3, 500, 400)]
m_detector = torchvision.models.detection.ssdlite320_mobilenet_v3_large(pretrained=True)
m_detector.eval()
predictions = m_detector(x)
更多详情访问：https://pytorch.org/blog/pytorch-1.9-released/
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