class_docstr: See github issue #2091. These are tests to ensure that the prior is kept if A is already given as Parameter.
class_docstr_tok: ["See","github","issue","#","2091",".","These","are","tests","to","ensure","that","the","prior","is","kept","if","A","is","already","given","as","Parameter","."]
docstr: Check that Linear copies the prior from a correctly shaped A Parameter
docstr_tok: ["Check","that","Linear","copies","the","prior","from","a","correctly","shaped","A","Parameter"]
code: def test_parameter_with_correct_shape(self) -> None:
      "Check that Linear copies the prior from a correctly shaped A Parameter"
      A = gpflow.Parameter(
          np.ones((1, 1)),
          dtype=np.float64,
          prior=tfp.distributions.Normal(0.0, 1.0),
      )
      linear_function = Linear(A, 1)
      assert linear_function.A.prior is not None
  
imports: from typing import Any, Sequence, Tuple, Type
  import numpy
  import pytest
  import tensorflow_probability
  from check_shapes import check_shapes
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow.base import AnyNDArray, TensorType
  from gpflow.config import default_int
  from gpflow.functions import Additive, Constant, Linear, MeanFunction, Polynomial, Product, SwitchedMeanFunction, Zero
  from gpflow.inducing_variables import InducingPoints
label_desc: Use image node_id 1 for calling the TestIssue2091EnsureParameterTypeForLinearMeanFunction obj's underlying member method code with example usage: obj.test_parameter_with_correct_shape() without return types