InfiniCore/python/infinicore/__init__.py at b2fe8f74b1a5b12f5788ec9b920c1ef54bec010f · 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.aminmax import aminmax
from infinicore.ops.attention import attention
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 .ops.sqrt import sqrt
from .ops.diagflat import diagflat
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",
    "aminmax",
    "attention",
    "matmul",
    "mul",
    "narrow",
    "rearrange",
    "empty",
    "empty_like",
    "from_blob",
    "from_list",
    "from_numpy",
    "from_torch",
    "ones",
    "strided_empty",
    "strided_from_blob",
    "zeros",
    "sqrt",
    "diagflat",
]

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