InfiniCore/python/infinicore/__init__.py at 1b7f324ee962d5154f6a8c9f8da03e7f45bc26b7 · InfiniTensor/InfiniCore · GitHub

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import contextlib

import infinicore.context as context
import infinicore.nn as nn

# Import context functions
from infinicore.context import (
    get_device,
    get_device_count,
    get_stream,
    set_device,
    sync_device,
    sync_stream,
)
from infinicore.device import device
from infinicore.device_event import DeviceEvent
from infinicore.dtype import (
    bfloat16,
    bool,
    cdouble,
    cfloat,
    chalf,
    complex32,
    complex64,
    complex128,
    double,
    dtype,
    float,
    float16,
    float32,
    float64,
    half,
    int,
    int8,
    int16,
    int32,
    int64,
    long,
    short,
    uint8,
)
from infinicore.ops.add import add
from infinicore.ops.attention import attention
from infinicore.ops.logical_or import logical_or
from infinicore.ops.logical_xor import logical_xor
from infinicore.ops.logsigmoid import logsigmoid
from infinicore.ops.where import where
from infinicore.ops.vdot import vdot
from infinicore.ops.matmul import matmul
from infinicore.ops.mul import mul
from infinicore.ops.narrow import narrow
from infinicore.ops.rearrange import rearrange
from infinicore.tensor import (
    Tensor,
    empty,
    empty_like,
    from_blob,
    from_list,
    from_numpy,
    from_torch,
    ones,
    strided_empty,
    strided_from_blob,
    zeros,
)

__all__ = [
    # Modules.
    "context",
    "nn",
    # Classes.
    "device",
    "DeviceEvent",
    "dtype",
    "Tensor",
    # Context functions.
    "get_device",
    "get_device_count",
    "get_stream",
    "set_device",
    "sync_device",
    "sync_stream",
    # Data Types.
    "bfloat16",
    "bool",
    "cdouble",
    "cfloat",
    "chalf",
    "complex32",
    "complex64",
    "complex128",
    "double",
    "float",
    "float16",
    "float32",
    "float64",
    "half",
    "int",
    "int8",
    "int16",
    "int32",
    "int64",
    "long",
    "short",
    "uint8",
    # Operations.
    "add",
    "attention",
    "logical_or",
    "logical_xor",
    "logsigmoid",
    "where",
    "vdot",
    "matmul",
    "mul",
    "narrow",
    "rearrange",
    "empty",
    "empty_like",
    "from_blob",
    "from_list",
    "from_numpy",
    "from_torch",
    "ones",
    "strided_empty",
    "strided_from_blob",
    "zeros",
]

use_ntops = False

with contextlib.suppress(ImportError, ModuleNotFoundError):
    import sys

    import ntops

    for op_name in ntops.torch.__all__:
        getattr(ntops.torch, op_name).__globals__["torch"] = sys.modules[__name__]

    use_ntops = True