Update gather_op_test and unique_op_test to use subTest for easier debugging.
PiperOrigin-RevId: 311595699 Change-Id: I1a8cf8b5b314aada4aeeece2603e975bc8a4ff42
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@ -62,6 +62,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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data = np.array([0, 1, 2, 3, 7, 5])
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for dtype in _TEST_TYPES:
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for indices in 4, [1, 2, 2, 4, 5]:
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with self.subTest(dtype=dtype, indices=indices):
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params_np = self._buildParams(data, dtype)
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params = constant_op.constant(params_np)
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indices_tf = constant_op.constant(indices)
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@ -77,6 +78,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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[9, 10, 11], [12, 13, 14]])
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for dtype in _TEST_TYPES:
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for axis in range(data.ndim):
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with self.subTest(dtype=dtype, axis=axis):
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params_np = self._buildParams(data, dtype)
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params = constant_op.constant(params_np)
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indices = constant_op.constant(2)
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@ -92,6 +94,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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[9, 10, 11], [12, 13, 14]])
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for dtype in _TEST_TYPES:
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for axis in range(data.ndim):
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with self.subTest(dtype=dtype, axis=axis):
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params_np = self._buildParams(data, dtype)
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params = constant_op.constant(params_np)
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# The indices must be in bounds for any axis.
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@ -112,6 +115,8 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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for axis in range(len(shape)):
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params = self._buildParams(np.random.randn(*shape), dtype)
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indices = np.random.randint(shape[axis], size=indices_shape)
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with self.subTest(indices_shape=indices_shape, dtype=dtype, axis=axis,
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indices=indices):
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with self.cached_session(use_gpu=True) as sess:
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tf_params = constant_op.constant(params)
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tf_indices = constant_op.constant(indices)
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@ -177,12 +182,14 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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@test_util.run_deprecated_v1
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def testUInt32AndUInt64(self):
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for unsigned_type in (dtypes.uint32, dtypes.uint64):
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with self.subTest(unsigned_type=unsigned_type):
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params = self._buildParams(
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np.array([[1, 2, 3], [7, 8, 9]]), unsigned_type)
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with self.cached_session():
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self.assertAllEqual([7, 8, 9],
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array_ops.gather(params, 1, axis=0).eval())
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self.assertAllEqual([1, 7], array_ops.gather(params, 0, axis=1).eval())
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self.assertAllEqual([1, 7],
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array_ops.gather(params, 0, axis=1).eval())
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@test_util.run_deprecated_v1
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def testUnknownIndices(self):
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@ -237,6 +244,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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indices = 0
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for bad_axis in (1, 2, -2):
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# Shape inference can validate axis for known params rank.
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with self.subTest(bad_axis=bad_axis):
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with self.assertRaisesWithPredicateMatch(
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ValueError, "Shape must be at least rank . but is rank 1"):
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array_ops.gather(params, indices, axis=bad_axis)
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@ -252,6 +260,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
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for dtype in _TEST_TYPES:
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for itype in np.int32, np.int64:
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# Leading axis gather.
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with self.subTest(dtype=dtype, itype=itype):
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params = np.zeros((7, 0, 0), dtype=dtype.as_numpy_dtype)
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indices = np.array([3, 4], dtype=itype)
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gather = array_ops.gather(params, indices, axis=0)
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@ -61,6 +61,7 @@ class UniqueTest(test.TestCase):
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def testInt32Axis(self):
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for dtype in [np.int32, np.int64]:
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with self.subTest(dtype=dtype):
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x = np.array([[1, 0, 0], [1, 0, 0], [2, 0, 0]])
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y0, idx0 = gen_array_ops.unique_v2(x, axis=np.array([0], dtype))
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self.assertEqual(y0.shape.rank, 2)
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@ -144,11 +145,13 @@ class UniqueWithCountsTest(test.TestCase):
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for i in range(len(x)):
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self.assertEqual(x[i], tf_y[tf_idx[i]].decode('ascii'))
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for value, count in zip(tf_y, tf_count):
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with self.subTest(value=value, count=count):
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v = [1 if x[i] == value.decode('ascii') else 0 for i in range(7000)]
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self.assertEqual(count, sum(v))
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def testInt32Axis(self):
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for dtype in [np.int32, np.int64]:
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with self.subTest(dtype=dtype):
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x = np.array([[1, 0, 0], [1, 0, 0], [2, 0, 0]])
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y0, idx0, count0 = gen_array_ops.unique_with_counts_v2(
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x, axis=np.array([0], dtype))
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