Add test case for sparse_dense_cwise shape validation.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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@ -22,6 +22,7 @@ import numpy as np
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import errors
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from tensorflow.python.framework import ops
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from tensorflow.python.framework import ops
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from tensorflow.python.framework import sparse_tensor
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from tensorflow.python.framework import sparse_tensor
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from tensorflow.python.framework import test_util
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from tensorflow.python.framework import test_util
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@ -798,6 +799,17 @@ class SparseMathOpsTest(test_util.TensorFlowTestCase):
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result_tensor.values).eval()
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result_tensor.values).eval()
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self.assertAllEqual(result_np, res_densified)
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self.assertAllEqual(result_np, res_densified)
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@test_util.run_deprecated_v1
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def testCwiseShapeValidation(self):
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# Test case for GitHub 24072.
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with self.session(use_gpu=False):
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a = array_ops.ones([3, 4, 1], dtype=dtypes.int32)
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b = sparse_tensor.SparseTensor([[0, 0, 1, 0], [0, 0, 3, 0]], [10, 20], [1, 1, 4, 2])
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c = a * b
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with self.assertRaisesRegexp(errors.InvalidArgumentError,
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"broadcasts dense to sparse only; got incompatible shapes"):
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c.eval()
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@test_util.run_deprecated_v1
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@test_util.run_deprecated_v1
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def testCwiseDivAndMul(self):
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def testCwiseDivAndMul(self):
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np.random.seed(1618)
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np.random.seed(1618)
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