def testDedupeDenseTensorPerRow(self, values, expected_indices,
expected_output):
dense_input = tf.constant(values)
output_tensor = mappers.deduplicate_tensor_per_row(dense_input)
with tf.compat.v1.Session():
output = output_tensor.eval()
self.assertAllEqual(output.indices, expected_indices)
self.assertAllEqual(output.values, expected_output)
def testDedupeSparseTensorPerRow(self, indices, values, dense_shape,
expected_output_indices,
expected_output_values,
expected_output_shape):
sp_input = tf.SparseTensor(
indices=indices, values=values, dense_shape=dense_shape)
output_tensor = mappers.deduplicate_tensor_per_row(sp_input)
with tf.compat.v1.Session():
output = output_tensor.eval()
self.assertAllEqual(output.indices, expected_output_indices)
self.assertAllEqual(output.values, expected_output_values)
self.assertAllEqual(output.dense_shape, expected_output_shape)
def testDedup3dInputRaises(self):
dense_input = tf.constant([[[b'a', b'a'], [b'b', b'b']],
[[b'a', b'a'], [b'd', b'd']]])
with self.assertRaises(ValueError):
mappers.deduplicate_tensor_per_row(dense_input)
