class_docstr: Testing helper class forked from JaxTestCase.
docstr: Assert that x and y are close (up to numerical tolerances).
docstr_tok: ["Assert","that","x","and","y","are","close","(","up","to","numerical","tolerances",")","."]
code: def assertArraysAllClose(
      self,
      x,
      y,
      *,
      check_dtypes: bool = True,
      atol: Optional[float] = None,
      rtol: Optional[float] = None,
      err_msg: str = "",
  ):
      """Assert that x and y are close (up to numerical tolerances)."""
      self.assertEqual(x.shape, y.shape)
      atol = max(
          _tolerance(_dtype(x), atol), _tolerance(_dtype(y), atol)
      )
      rtol = max(
          _tolerance(_dtype(x), rtol), _tolerance(_dtype(y), rtol)
      )
      _assert_numpy_allclose(
          x, y, atol=atol, rtol=rtol, err_msg=err_msg
      )
  
      if check_dtypes:
          self.assertDtypesMatch(x, y)
  
imports: import dataclasses
  import itertools
  import logging
  import os
  from types import ModuleType
  from typing import Callable, Optional, Sequence
  from absl import flags
  from absl.testing import parameterized
  import jax
  from jax import config
  from jax import dtypes
  from jax import jit
  from jax import vmap
  import jax.numpy
  import numpy
label_desc: Use image node_id 2 for calling the NeuralTangentsTestCase obj's underlying member method code with example usage: obj.assertArraysAllClose(x, y) without return types