def testSparseCountSparseOutputNegativeValue(self):
indices = [[0, 0], [0, 1], [1, 0], [1, 2]]
values = [1, 1, -1, 10]
dense_shape = [2, 3]
with self.assertRaisesRegex(errors.InvalidArgumentError,
"Input values must all be non-negative"):
self.evaluate(
gen_count_ops.SparseCountSparseOutput(
indices=indices,
values=values,
dense_shape=dense_shape,
binary_output=False))
def testSparseCountSparseOutputBadIndicesShapeTooSmall(self):
indices = [1]
values = [[1]]
weights = []
dense_shape = [10]
with self.assertRaisesRegex(ValueError,
"Shape must be rank 2 but is rank 1 for"):
self.evaluate(
gen_count_ops.SparseCountSparseOutput(indices=indices,
values=values,
dense_shape=dense_shape,
weights=weights,
binary_output=True))
def testSparseCountSparseOutputBadNumberOfValues(self):
indices = [[0, 0], [0, 1], [1, 0]]
values = [1, 1, 1, 10]
weights = [1, 2, 4, 6]
dense_shape = [2, 3]
with self.assertRaisesRegex(
errors.InvalidArgumentError,
"Number of values must match first dimension of indices"):
self.evaluate(
gen_count_ops.SparseCountSparseOutput(indices=indices,
values=values,
dense_shape=dense_shape,
weights=weights,
binary_output=False))
def testSparseCountSparseOutputBadWeightsShape(self):
indices = [[0, 0], [0, 1], [1, 0], [1, 2]]
values = [1, 1, 1, 10]
weights = [1, 2, 4]
dense_shape = [2, 3]
with self.assertRaisesRegex(
errors.InvalidArgumentError,
"Weights and values must have the same shape"):
self.evaluate(
gen_count_ops.SparseCountSparseOutput(indices=indices,
values=values,
dense_shape=dense_shape,
weights=weights,
binary_output=False))
def testSparseCountSparseOutputBadIndicesShape(self):
indices = [[[0], [0]], [[0], [1]], [[1], [0]], [[1], [2]]]
values = [1, 1, 1, 10]
weights = [1, 2, 4, 6]
dense_shape = [2, 3]
with self.assertRaisesRegex(
errors.InvalidArgumentError,
"Input indices must be a 2-dimensional tensor"):
self.evaluate(
gen_count_ops.SparseCountSparseOutput(indices=indices,
values=values,
dense_shape=dense_shape,
weights=weights,
binary_output=False))
