c2b3a13e70
- Remove parameter serialization in the scikit-learn interface. The scikit-lear interface `save_model` will save only the model and discard all hyper-parameters. This is to align with the native XGBoost interface, which distinguishes the hyper-parameter and model parameters. With the scikit-learn interface, model parameters are attributes of the estimator. For instance, `n_features_in_`, `n_classes_` are always accessible with `estimator.n_features_in_` and `estimator.n_classes_`, but not with the `estimator.get_params`. - Define a `load_model` method for classifier to load its own attributes. - Set n_estimators to None by default.
103 lines
2.3 KiB
Python
103 lines
2.3 KiB
Python
# pylint: disable=protected-access
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"""Shared typing definition."""
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import ctypes
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import os
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from typing import (
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TYPE_CHECKING,
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Any,
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Callable,
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Dict,
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List,
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Sequence,
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Type,
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TypeVar,
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Union,
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)
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# os.PathLike/string/numpy.array/scipy.sparse/pd.DataFrame/dt.Frame/
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# cudf.DataFrame/cupy.array/dlpack
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import numpy as np
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DataType = Any
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# xgboost accepts some other possible types in practice due to historical reason, which is
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# lesser tested. For now we encourage users to pass a simple list of string.
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FeatureInfo = Sequence[str]
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FeatureNames = FeatureInfo
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FeatureTypes = FeatureInfo
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BoosterParam = Union[List, Dict[str, Any]] # better be sequence
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ArrayLike = Any
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PathLike = Union[str, os.PathLike]
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CupyT = ArrayLike # maybe need a stub for cupy arrays
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NumpyOrCupy = Any
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NumpyDType = Union[str, Type[np.number]]
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PandasDType = Any # real type is pandas.core.dtypes.base.ExtensionDtype
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FloatCompatible = Union[float, np.float32, np.float64]
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# callables
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FPreProcCallable = Callable
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# ctypes
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# c_bst_ulong corresponds to bst_ulong defined in xgboost/c_api.h
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c_bst_ulong = ctypes.c_uint64 # pylint: disable=C0103
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ModelIn = Union[str, bytearray, os.PathLike]
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CTypeT = TypeVar(
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"CTypeT",
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ctypes.c_void_p,
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ctypes.c_char_p,
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ctypes.c_int,
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ctypes.c_float,
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ctypes.c_uint,
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ctypes.c_size_t,
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)
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# supported numeric types
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CNumeric = Union[
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ctypes.c_float,
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ctypes.c_double,
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ctypes.c_uint,
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ctypes.c_uint64,
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ctypes.c_int32,
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ctypes.c_int64,
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]
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# c pointer types
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if TYPE_CHECKING:
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CStrPtr = ctypes._Pointer[ctypes.c_char]
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CStrPptr = ctypes._Pointer[ctypes.c_char_p]
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CFloatPtr = ctypes._Pointer[ctypes.c_float]
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CNumericPtr = Union[
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ctypes._Pointer[ctypes.c_float],
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ctypes._Pointer[ctypes.c_double],
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ctypes._Pointer[ctypes.c_uint],
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ctypes._Pointer[ctypes.c_uint64],
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ctypes._Pointer[ctypes.c_int32],
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ctypes._Pointer[ctypes.c_int64],
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]
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else:
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CStrPtr = ctypes._Pointer
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CStrPptr = ctypes._Pointer
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CFloatPtr = ctypes._Pointer
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CNumericPtr = Union[
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ctypes._Pointer,
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ctypes._Pointer,
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ctypes._Pointer,
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ctypes._Pointer,
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ctypes._Pointer,
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ctypes._Pointer,
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]
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# template parameter
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_T = TypeVar("_T")
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_F = TypeVar("_F", bound=Callable[..., Any])
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