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Chengyang Gu
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import ctypes | ||
import os | ||
from typing import Optional, List, Any, TypeVar, Union, Dict | ||
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import numpy as np | ||
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# os.PathLike/string/numpy.array/scipy.sparse/pd.DataFrame/dt.Frame/cudf.DataFrame/cupy.array/dlpack | ||
DataType = Any | ||
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# xgboost accepts some other possible types in practice due to historical reason, which is | ||
# lesser tested. For now we encourage users to pass a simple list of string. | ||
FeatNamesT = Optional[List[str]] | ||
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ArrayLike = Any | ||
PathLike = Union[str, os.PathLike] | ||
cupy_t = ArrayLike # maybe need a stub for cupy arrays | ||
numpy_or_cupy_t = Union[np.ndarray, cupy_t] | ||
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# ctypes | ||
c_bst_ulong = ctypes.c_uint64 | ||
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ctype_t = Union[ | ||
ctypes.c_void_p, ctypes.c_char_p, ctypes.c_int, | ||
ctypes.c_float, ctypes.c_uint, ctypes.c_size_t | ||
] | ||
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# supported numeric types | ||
c_numeric_t = Union[ | ||
ctypes.c_float, ctypes.c_double, ctypes.c_uint, | ||
ctypes.c_uint64, ctypes.c_int32, ctypes.c_int64 | ||
] | ||
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# c pointer types | ||
c_str_ptr_t = ctypes.pointer[ctypes.c_char] | ||
c_str_pptr_t = ctypes.pointer[ctypes.c_char_p] | ||
c_float_ptr_t = ctypes.pointer[ctypes.c_float] | ||
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c_numeric_ptr_t = Union[ | ||
ctypes.pointer[ctypes.c_float], ctypes.pointer[ctypes.c_double], | ||
ctypes.pointer[ctypes.c_uint], ctypes.pointer[ctypes.c_uint64], | ||
ctypes.pointer[ctypes.c_int32], ctypes.pointer[ctypes.c_int64] | ||
] | ||
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# template parameter | ||
T = TypeVar("T") |