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10/11/2020, · I tried a different number of layers (resnet10, resnet18, and resnet50) and different resolutions, but the ,performance, is still low. I would like to know if there are other parameters in the spec file that could help me improve the ,performance, of ,MaskRCNN, model on Jetson Nano. My spec file looks very much like the one in the link I mentioned above.
facebookresearch / ,maskrcnn-benchmark, Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch. - View it on GitHub Star 7888 Rank 1524 Released by @k0kubun in December 2014.
1080ti 3070 3080 3090 a100 adversarial networks all reduce ampere ,benchmarks, BERT char-rnn cloud clusters CNNs cuda data preparation deep dream deep learning distributed training docker drivers fun GANs generative networks GPT-2 GPT-3 gpu-cloud gpus hardware Horovod hpc hyperplane image classification ImageNet infiniband infrastructure keras lambda stack lambda-stack Language Model …
from ,maskrcnn_benchmark,. utils. comm import synchronize. import time . from ,maskrcnn_benchmark,. config import cfg as test_cfg . from ,maskrcnn_benchmark,. data import make_data_loader . def test (cfg, model, data_loader_val, output_folder = None, distributed = False): if distributed: