class_docstr: Linear mean function for Gaussian process.
  
  Parameters
  ----------
  coeffs: variables
      Linear coefficients
  intercept: variable, array or integer
      Intercept for linear function (Defaults to zero)
class_docstr_tok: ["Linear","mean","function","for","Gaussian","process",".","Parameters","--","--","--","--","--","coeffs",":","variables","Linear","coefficients","intercept",":","variable",",","array","or","integer","Intercept","for","linear","function","(","Defaults","to","zero",")"]
code: def __call__(self, X):
      return pt.squeeze(pt.dot(X, self.A) + self.b)
  
imports: import pytensor.tensor
label_desc: Use image node_id 2 for calling the Linear obj's underlying member method code with example usage: obj.__call__(X) and returns: pt