original_docstring: 
          Individual gradient of prediction at Xnew w.r.t. each sample in Xnew
          
docstring: Individual gradient of prediction at Xnew w.r.t. each sample in Xnew
docstring_tokens: Individual gradient of prediction at Xnew w . r . t . each sample in Xnew
code: def dmu_dXnew(self, Xnew):
          """
          Individual gradient of prediction at Xnew w.r.t. each sample in Xnew
          """
          gradients_X = np.zeros((Xnew.shape[0], self.num_inducing))
          ones = np.ones((1, 1))
          for i in range(self.Z.shape[0]):
              gradients_X[:, i] = self.kern.gradients_X(ones, Xnew, self.Z[i:i + 1, :]).sum(-1)
          return np.dot(gradients_X, self.grad_dict['dL_dpsi1'])
code_tokens: def dmu_dXnew ( self , Xnew ) : gradients_X = np . zeros ( ( Xnew . shape [ 0 ] , self . num_inducing ) ) ones = np . ones ( ( 1 , 1 ) ) for i in range ( self . Z . shape [ 0 ] ) : gradients_X [ : , i ] = self . kern . gradients_X ( ones , Xnew , self . Z [ i : i + 1 , : ] ) . sum ( - 1 ) return np . dot ( gradients_X , self . grad_dict [ 'dL_dpsi1' ] )
short_docstring: Individual gradient of prediction at Xnew w.r.t.
short_docstring_tokens: Individual gradient of prediction at Xnew w . r . t .
comment: """
          Individual gradient of prediction at Xnew w.r.t. each sample in Xnew
          """