针对pulse-transit的工具

dist/client/sklearn/_loss/_loss.pxd

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+# cython: language_level=3
+
+import numpy as np
+cimport numpy as np
+
+np.import_array()
+
+
+# Fused types for y_true, y_pred, raw_prediction
+ctypedef fused Y_DTYPE_C:
+    np.npy_float64
+    np.npy_float32
+
+
+# Fused types for gradient and hessian
+ctypedef fused G_DTYPE_C:
+    np.npy_float64
+    np.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