[XLA] Slightly change some test inputs/tolerances
PiperOrigin-RevId: 283774638 Change-Id: I9b5bf178dafe02e18d630e0cb2b867448dade7fa
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@ -653,7 +653,13 @@ class BinaryOpsTest(xla_test.XLATestCase):
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divs = np.arange(-3, 3, .25, dtype=dtype).reshape(1, 24)
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np_result = np.true_divide(nums, divs)
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np_result[:, divs[0] == 0] = 0
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self._testBinary(gen_math_ops.div_no_nan, nums, divs, expected=np_result)
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self._testBinary(
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gen_math_ops.div_no_nan,
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nums,
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divs,
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expected=np_result,
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rtol=7e-15 if dtype == np.float64 else None,
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atol=3.9e-15 if dtype == np.float64 else None)
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if dtype not in self.complex_types: # floordiv unsupported for complex.
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self._testBinary(
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@ -164,7 +164,8 @@ class TensorArrayTest(xla_test.XLATestCase):
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dtype=tf_dtype, tensor_array_name="foo", size=3)
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# Unpack a matrix into vectors.
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w1 = ta.unstack(convert([[1.0, 1.1], [2.0, 2.1], [3.0, 3.1]]))
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w1 = ta.unstack(
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convert([[1.0, 1.03125], [2.0, 2.03125], [3.0, 3.03125]]))
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r0 = w1.read(0)
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r1 = w1.read(1)
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r2 = w1.read(2)
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@ -172,9 +173,9 @@ class TensorArrayTest(xla_test.XLATestCase):
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d0, d1, d2 = self.evaluate(xla.compile(fn))
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self.assertAllEqual(convert([1.0, 1.1]), d0)
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self.assertAllEqual(convert([2.0, 2.1]), d1)
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self.assertAllEqual(convert([3.0, 3.1]), d2)
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self.assertAllEqual(convert([1.0, 1.03125]), d0)
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self.assertAllEqual(convert([2.0, 2.03125]), d1)
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self.assertAllEqual(convert([3.0, 3.03125]), d2)
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def fn():
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# Reset ta because we're going to change the shape, else shape
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