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MegEngine/imperative/python/megengine
Megvii Engine Team 1f0436967c refactor(mge/distributed): using nccl as default in distributed training 3 years ago
..
amp feat(mge/amp): add GradScaler support 3 years ago
autodiff feat(mge/amp): add GradScaler support 3 years ago
core fix(imperative): remove convert_inputs 3 years ago
data fix(mge/distributed): fix the mutli dataloader test error 4 years ago
distributed refactor(mge/distributed): using nccl as default in distributed training 3 years ago
dtr feat(dtr): add sqrt sampling 3 years ago
experimental feat(mge/experimental): add WeightScaler support 3 years ago
functional chore(mge): run get_device_count("gpu") in subprocess 3 years ago
hub chore(mge): update copyright years 4 years ago
jit feat(mge/amp): add mix precision autocast support 3 years ago
module feat(opr): add bn backward for inference mode 3 years ago
optimizer feat(imperative/autodiff): add grad clip 4 years ago
quantization Merge pull request #175 from tpoisonooo:fix-spell-error 3 years ago
random feat(mge/random): add some random op and remove random/distrbution.py 3 years ago
tools fix(mge/tools): fix module status error 3 years ago
utils fix(imperative/utils): fix logical error of replace var 3 years ago
__init__.py feat(mge/amp): add mix precision autocast support 3 years ago
device.py fix(device): fix get_device_count for xpu 4 years ago
logger.py fix(mge/logger): fix set_mgb_log_level 4 years ago
serialization.py fix(mge/tensor): fix tensor's serialization behavior 4 years ago
tensor.py feat(mge/amp): add mix precision autocast support 3 years ago
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MegEngine 安装包中集成了使用 GPU 运行代码所需的 CUDA 环境，不用区分 CPU 和 GPU 版。 如果想要运行 GPU 程序，请确保机器本身配有 GPU 硬件设备并安装好驱动。 如果你想体验在云端 GPU 算力平台进行深度学习开发的感觉，欢迎访问 MegStudio 平台

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