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Fix test failures.
PiperOrigin-RevId: 662703221
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2b3ccce793
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@ -715,7 +715,7 @@ class JaxNumpyReducerTests(jtu.JaxTestCase):
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# TODO(phawkins): we currently set dtype=False because we aren't as
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# aggressive about promoting to float64. It's not clear we want to mimic
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# Numpy here.
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tol_spec = {np.float16: 1E-2, np.float32: 2e-4, np.float64: 5e-6}
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tol_spec = {np.float16: 4e-2, np.float32: 2e-4, np.float64: 5e-6}
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tol = max(jtu.tolerance(a_dtype, tol_spec),
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jtu.tolerance(q_dtype, tol_spec))
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self._CheckAgainstNumpy(np_fun, jnp_fun, args_maker, check_dtypes=False,
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@ -4768,7 +4768,7 @@ class LaxBackedNumpyTests(jtu.JaxTestCase):
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else x.astype(np.float32) for x in choicelist]
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dtype = jnp.result_type(default, *choicelist)
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return np.select(condlist,
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[np.asarray(x, dtype=dtype) for x in choicelist],
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[np.asarray(x).astype(dtype) for x in choicelist],
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np.asarray(default, dtype=dtype))
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with jtu.strict_promotion_if_dtypes_match(dtypes):
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self._CheckAgainstNumpy(np_fun, jnp.select, args_maker,
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@ -226,7 +226,8 @@ class LaxBackedScipyTests(jtu.JaxTestCase):
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rng = jtu.rand_positive(self.rng())
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args_maker = lambda: [rng(shape, dtype) + (d - 1) / 2.]
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self._CheckAgainstNumpy(scipy_fun, lax_fun, args_maker,
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tol={np.float32: 1e-3, np.float64: 1e-14})
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tol={np.float32: 1e-3, np.float64: 1e-14},
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check_dtypes=False)
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self._CompileAndCheck(
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lax_fun, args_maker, rtol={
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np.float32: 5e-5 if jtu.test_device_matches(["tpu"]) else 1e-05,
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