pytorch自定义backend

使用PrivateUse1定义out-of-tree backend

pytorch tutotial Facilitating New Backend Integration by PrivateUse1

相关api:
torch.utils.rename_privateuse1_backend

distributed backend

pytorch tutorial Customize Process Group Backends Using Cpp Extensions

相关api:
torch.distributed.Backend.register_backend
torch.distributed.init_process_group
ProcessGroup::allreduce
fallback example1
fallback example2

分布式算子fallback处理

Flaggems
FlagCX

报错:

NotImplementedError: Could not run 'c10d::allreduce_' with arguments from the 'Autogradtxda' backend.

解决

参考CPU,为DispatchKey AutogradCPU(_表示整个module?)设置fallback:

以上修改会让此接口返回True:

python 复制代码
print("AutogradCPU backend fallback registered:", torch._C._dispatch_has_backend_fallback(
            torch._C.DispatchKey.AutogradCPU
        ))
调试代码段
python 复制代码
print(f"! rank {MY_RANK} privateuse1_backend_name: {torch._C._get_privateuse1_backend_name()}")

# 查看 c10d::allreduce_ 是否在 多个 dispatch key 上有 kernel
print("AutogradPrivateUse1 kernel registered:", torch._C._dispatch_has_kernel_for_dispatch_key(
    "c10d::allreduce_",
    torch._C.DispatchKey.AutogradPrivateUse1
))  # 应为 False
print("AutogradCPU kernel registered:", torch._C._dispatch_has_kernel_for_dispatch_key(
    "c10d::allreduce_",
    torch._C.DispatchKey.AutogradCPU
))  # 应为 False
print("CPU kernel registered:", torch._C._dispatch_has_kernel_for_dispatch_key(
    "c10d::allreduce_",
    torch._C.DispatchKey.CPU
))  # 应为 True
print("PrivateUse1 kernel registered:", torch._C._dispatch_has_kernel_for_dispatch_key(
    "c10d::allreduce_",
    torch._C.DispatchKey.PrivateUse1
))  # 应为 True

# 查看AutogradPrivateUse1, AutogradCPU, 是否有 backend fallback
print("AutogradPrivateUse1 backend fallback registered:", torch._C._dispatch_has_backend_fallback(
    torch._C.DispatchKey.AutogradPrivateUse1
))  # 应为 True

print("AutogradCPU backend fallback registered:", torch._C._dispatch_has_backend_fallback(
    torch._C.DispatchKey.AutogradCPU
))  # 应为 True

# export TORCH_LOGS=all IS NEEDED
print(torch._C._dispatch_dump("c10d::allreduce_"))
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