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Megvii Engine Team 888c7f1f7a fix(mge/module): fix auto-naming error when there are containers in the module 4 years ago
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qat feat(mge/quantization): use extra act_fakequant to decide whether to do bias fakequant 4 years ago
quantized fix(imperative/quantization): add conditional when passing parameters name 4 years ago
__init__.py feat(functional): add conv3d 4 years ago
activation.py fix(mge/module): add kwargs param for all modules 4 years ago
adaptive_pooling.py fix(mge/module): add kwargs param for all modules 4 years ago
batch_matmul_activation.py docs(mge): add missing docstring and fix sphinx build warnings 4 years ago
batchnorm.py fix(mge/module): add kwargs param for all modules 4 years ago
concat.py docs(mge): add missing docstring and fix sphinx build warnings 4 years ago
conv.py feat(functional): add conv3d 4 years ago
conv_bn.py docs(mge): add missing docstring and fix sphinx build warnings 4 years ago
deformable_psroi_pooling.py feat(mge/quantization): add name for quantized module 4 years ago
dropout.py fix(mge/module): add kwargs param for all modules 4 years ago
elemwise.py docs(mge): add missing docstring and fix sphinx build warnings 4 years ago
embedding.py fix(mge/module): add kwargs param for all modules 4 years ago
external.py feat(imperative/src): python wrapper for cambricon and atlas runtime opr 4 years ago
identity.py refactor(mge/functional): move functional api 4 years ago
init.py chore(mge): update copyright years 4 years ago
linear.py chore(mge): update copyright years 4 years ago
module.py fix(mge/module): fix auto-naming error when there are containers in the module 4 years ago
normalization.py fix(mge/module): add kwargs param for all modules 4 years ago
pooling.py fix(mge/module): add kwargs param for all modules 4 years ago
quant_dequant.py chore(mge): update copyright years 4 years ago
sequential.py feat(mge/utils): add get/set_expand_structure to deal with complex key 4 years ago

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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