code: def generate_inputs(self):
      x = numpy.random.uniform(-1.0, 1.0, self.shape).astype(self.dtype)
      divisor = numpy.random.uniform(-1.0, 1.0, self.shape).astype(
          self.dtype
      )
      # division with too small divisor is unstable.
      for i in numpy.ndindex(self.shape):
          if math.fabs(divisor[i]) < 0.1:
              divisor[i] += 1.0
      # make enough margin
      for i in numpy.ndindex(self.shape):
          m = math.fabs(x[i] % divisor[i])
          if m < 0.01 or m > (divisor[i] - 0.01):
              x[i] = 0.5
              divisor[i] = 0.3
      return x, divisor
  
file_path: chainer/tests/chainer_tests/functions_tests/math_tests/test_fmod.py
imports: import math
  import numpy
  from chainer import functions
  from chainer import testing
label_desc: Use image node_id 2 for calling the TestFmod obj's underlying member method code with example usage: obj.generate_inputs() and returns: x,  divisor