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# cython: language_level=3
cimport numpy as cnp
cnp.import_array()
# Fused types for y_true, y_pred, raw_prediction
ctypedef fused Y_DTYPE_C:
cnp.npy_float64
cnp.npy_float32
# Fused types for gradient and hessian
ctypedef fused G_DTYPE_C:
cnp.npy_float64
cnp.npy_float32
# Struct to return 2 doubles
ctypedef struct double_pair:
double val1
double val2
# C base class for loss functions
cdef class CyLossFunction:
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfSquaredError(CyLossFunction):
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyAbsoluteError(CyLossFunction):
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyPinballLoss(CyLossFunction):
cdef readonly double quantile # readonly makes it accessible from Python
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfPoissonLoss(CyLossFunction):
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfGammaLoss(CyLossFunction):
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfTweedieLoss(CyLossFunction):
cdef readonly double power # readonly makes it accessible from Python
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfTweedieLossIdentity(CyLossFunction):
cdef readonly double power # readonly makes it accessible from Python
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
cdef class CyHalfBinomialLoss(CyLossFunction):
cdef double cy_loss(self, double y_true, double raw_prediction) nogil
cdef double cy_gradient(self, double y_true, double raw_prediction) nogil
cdef double_pair cy_grad_hess(self, double y_true, double raw_prediction) nogil
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