class_docstr: Tests for LAX-backed Numpy reduction operations.
class_docstr_tok: ["Tests","for","LAX-backed","Numpy","reduction","operations","."]
code: def testReducerNoDtype(
      self,
      name,
      rng_factory,
      shape,
      dtype,
      axis,
      keepdims,
      inexact,
      tolerance,
  ):
      np_op = getattr(np, name)
      jnp_op = getattr(jnp, name)
      rng = rng_factory(self.rng())
      is_bf16_nan_test = (
          dtype == jnp.bfloat16
          and rng_factory.__name__ == "rand_some_nan"
      )
  
      @jtu.ignore_warning(
          category=RuntimeWarning,
          message="Degrees of freedom <= 0 for slice.*",
      )
      @jtu.ignore_warning(
          category=RuntimeWarning,
          message="All-NaN (slice|axis) encountered.*",
      )
      def np_fun(x):
          x = np.asarray(x)
          if inexact:
              x = x.astype(dtypes.to_inexact_dtype(x.dtype))
          x_cast = x if not is_bf16_nan_test else x.astype(np.float32)
          res = np_op(x_cast, axis, keepdims=keepdims)
          res = (
              res if not is_bf16_nan_test else res.astype(jnp.bfloat16)
          )
          return res
  
      jnp_fun = lambda x: jnp_op(x, axis, keepdims=keepdims)
      args_maker = lambda: [rng(shape, dtype)]
      tol = jtu.join_tolerance(
          {np.float16: 0.002}, tolerance or jtu.default_tolerance()
      )
      self._CheckAgainstNumpy(np_fun, jnp_fun, args_maker, tol=tol)
      self._CompileAndCheck(jnp_fun, args_maker, rtol=tol, atol=tol)
  
imports: import collections
  from functools import partial
  import itertools
  import unittest
  from absl.testing import absltest
  from absl.testing import parameterized
  import numpy
  import jax
  from jax import numpy
  from jax._src import config
  from jax._src import dtypes
  from jax._src import test_util
  from jax._src.util import NumpyComplexWarning
label_desc: Use image node_id 3 for calling the JaxNumpyReducerTests obj's underlying member method code with example usage: obj.testReducerNoDtype(name, rng_factory, shape, dtype, axis, keepdims, inexact, tolerance) and returns: res