class_docstr: Tests for LAX-backed scipy.stats implementations
code: def testConvolutions(self, xshape, yshape, dtype, mode, op, method):
      jsp_op = getattr(jsp_signal, op)
      osp_op = getattr(osp_signal, op)
      rng = jtu.rand_default(self.rng())
      args_maker = lambda: [rng(xshape, dtype), rng(yshape, dtype)]
      osp_fun = partial(osp_op, mode=mode, method=method)
      jsp_fun = partial(
          jsp_op,
          mode=mode,
          method=method,
          precision=lax.Precision.HIGHEST,
      )
      if method == "fft":
          tol = {
              np.float16: 1e-2,
              np.float32: 1e-2,
              np.float64: 1e-6,
              np.complex64: 1e-2,
              np.complex128: 1e-6,
          }
      else:
          tol = {
              np.float16: 1e-2,
              np.float32: 1e-2,
              np.float64: 1e-12,
              np.complex64: 1e-2,
              np.complex128: 1e-12,
          }
      self._CheckAgainstNumpy(
          osp_fun, jsp_fun, args_maker, check_dtypes=False, tol=tol
      )
      self._CompileAndCheck(jsp_fun, args_maker, rtol=tol, atol=tol)
  
imports: from functools import partial
  import unittest
  from absl.testing import absltest
  import numpy
  import scipy.signal
  from jax import lax
  import jax.numpy
  from jax._src import dtypes
  from jax._src import test_util
  import jax.scipy.signal
  from jax import config
label_desc: Use image node_id 1 for calling the LaxBackedScipySignalTests obj's underlying member method code with example usage: obj.testConvolutions(xshape, yshape, dtype, mode, op, method) without return types