code: def testJaxToTorch(self, shape, dtype):
      if not config.enable_x64.value and dtype in [
          jnp.int64,
          jnp.float64,
          jnp.complex128,
      ]:
          self.skipTest("x64 types are disabled by jax_enable_x64")
      rng = jtu.rand_default(self.rng())
      np = rng(shape, dtype)
      x = jnp.array(np)
      dlpack = jax.dlpack.to_dlpack(x)
      y = torch.utils.dlpack.from_dlpack(dlpack)
      if dtype == jnp.bfloat16:
          # .numpy() doesn't work on Torch bfloat16 tensors.
          self.assertAllClose(
              np, y.cpu().view(torch.int16).numpy().view(jnp.bfloat16)
          )
      else:
          self.assertAllClose(np, y.cpu().numpy())
  
file_path: jax/tests/pytorch_interoperability_test.py
imports: import unittest
  from absl.testing import absltest
  import jax
  import jax.dlpack
  from jax._src import config
  from jax._src import test_util
  from jax._src import xla_bridge
  from jax._src.lib import xla_client
  import jax.numpy
label_desc: Use image node_id 3 for calling the DLPackTest obj's underlying member method code with example usage: obj.testJaxToTorch(shape, dtype) without return types