code: def test_sample_seed():
      x1, x2 = (Indexed("x", i) for i in (1, 2))
      pdf = exp(-(x1**2) / 2 + x1 - x2**2 / 2 - S.Half) / (2 * pi)
      X = JointRV("x", pdf)
  
      libraries = ["scipy", "numpy", "pymc"]
      for lib in libraries:
          try:
              imported_lib = import_module(lib)
              if imported_lib:
                  s0, s1, s2 = [], [], []
                  s0 = sample(X, size=10, library=lib, seed=0)
                  s1 = sample(X, size=10, library=lib, seed=0)
                  s2 = sample(X, size=10, library=lib, seed=1)
                  assert all(s0 == s1)
                  assert all(s1 != s2)
          except NotImplementedError:
              continue
  
imports: from sympy.concrete.products import Product
  from sympy.concrete.summations import Sum
  from sympy.core.numbers import Rational, oo, pi
  from sympy.core.relational import Eq
  from sympy.core.singleton import S
  from sympy.core.symbol import symbols
  from sympy.functions.combinatorial.factorials import RisingFactorial, factorial
  from sympy.functions.elementary.complexes import polar_lift
  from sympy.functions.elementary.exponential import exp
  from sympy.functions.elementary.miscellaneous import sqrt
  from sympy.functions.elementary.piecewise import Piecewise
  from sympy.functions.special.bessel import besselk
  from sympy.functions.special.gamma_functions import gamma
  from sympy.matrices.dense import eye
  from sympy.matrices.expressions.determinant import Determinant
  from sympy.sets.fancysets import Range
  from sympy.sets.sets import Interval, ProductSet
  from sympy.simplify.simplify import simplify
  from sympy.tensor.indexed import Indexed, IndexedBase
  from sympy.core.numbers import comp
  from sympy.integrals.integrals import integrate
  from sympy.matrices import Matrix, MatrixSymbol
  from sympy.matrices.expressions.matexpr import MatrixElement
  from sympy.stats import density, median, marginal_distribution, Normal, Laplace, E, sample
  from sympy.stats.joint_rv_types import JointRV, MultivariateNormalDistribution, JointDistributionHandmade, MultivariateT, NormalGamma, GeneralizedMultivariateLogGammaOmega, MultivariateBeta, GeneralizedMultivariateLogGamma, MultivariateEwens, Multinomial, NegativeMultinomial, MultivariateNormal, MultivariateLaplace
  from sympy.testing.pytest import raises, XFAIL, skip, slow
  from sympy.external import import_module
  from sympy.abc import x, y
label_desc: Use image node_id 17 for calling a global function with example usage: test_sample_seed() without return types