[Mypy] Part 3 fix typing for nested directories for most of directory

[rkooo567]

This fixes typing for most of the nested directories.

The remaining one has a lot of changes required for each of them.

Also move --follow-imports to the pyproject.toml

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[simon-mo]

unsure about the nccl's ctypes part.

[simon-mo]

this is weird that mypy can't handle this, it should defenitely return the c_int

[rkooo567]

Hmm when I added a breakpoint, it does return int.

(Pdb) ncclDataType_t.from_torch(tensor.dtype)
7
(Pdb) type(ncclDataType_t.from_torch(tensor.dtype))
<class 'int'>

Do you think it is a bug?

[youkaichao]

Well, technically, this function indeed returns int. ctypes will automatically convert int to c_int . Note that ctypes.c_int is a class/container to hold an int, and itself is not an int.

TL;DR; def from_torch(cls, dtype: torch.dtype) -> int: is correct.

[rkooo567]

# enums
class ncclDataType_t(ctypes.c_int):
    pass


class ncclDataTypeEnum:
    ncclInt8 = ncclDataType_t(0)
    ncclChar = ncclDataType_t(0)
    ncclUint8 = ncclDataType_t(1)
    ncclInt32 = ncclDataType_t(2)
    ncclInt = ncclDataType_t(2)
    ncclUint32 = ncclDataType_t(3)
    ncclInt64 = ncclDataType_t(4)
    ncclUint64 = ncclDataType_t(5)
    ncclFloat16 = ncclDataType_t(6)
    ncclHalf = ncclDataType_t(6)
    ncclFloat32 = ncclDataType_t(7)
    ncclFloat = ncclDataType_t(7)
    ncclFloat64 = ncclDataType_t(8)
    ncclDouble = ncclDataType_t(8)
    ncclBfloat16 = ncclDataType_t(9)
    ncclNumTypes = ncclDataType_t(10)

    @classmethod
    def from_torch(cls, dtype: torch.dtype) -> "ncclDataType_t":
        if dtype == torch.int8:
            return cls.ncclInt8
        if dtype == torch.uint8:
            return cls.ncclUint8
        if dtype == torch.int32:
            return cls.ncclInt32
        if dtype == torch.int64:
            return cls.ncclInt64
        if dtype == torch.float16:
            return cls.ncclFloat16
        if dtype == torch.float32:
            return cls.ncclFloat32
        if dtype == torch.float64:
            return cls.ncclFloat64
        if dtype == torch.bfloat16:
            return cls.ncclBfloat16
        raise ValueError(f"Unsupported dtype: {dtype}")

I fixed this way so that it returns the correct type.

[rkooo567]

oh @youkaichao I just saw your msg. So just returning int makes more sense if there's automatic conversion then ^?

[youkaichao]

I think automatic conversion makes more sense. The above code is difficult to read.

[rkooo567]

I think technically inheriting c_int here is not necessary then? it is just like a simple enum

[youkaichao]

yes, that's ChatGPT's fault 😉

[rkooo567]

Fixed. PTAL!
81313dc

[youkaichao]

This is not intuitive. Let's keep ncclDataType_t and ncclRedOp_t here.

Does mypy understand the call signature of _c_ncclAllReduce? I suppose it will just ignore them. And we can leave a comment here, saying that int will be automatically converted by ctypes.

[rkooo567]

I found ncclDataType_t being a random enum and type at the same time a bit weird though. Why don't we then just

ncclDataType_t(ctype.c_int):
    pass

ncclDataEnum:
    ... = 0
    .... = 1

?

[youkaichao]

Well, that's also doable.

Please use ncclDataType_t = ctype.c_int, and ncclDataTypeEnum

[rkooo567]

sgtm!

[rkooo567]

It is ready to merge!