import tensorflow as tf

hypothesis indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) 
hypothesis values = tf.constant(0, shape=[3], dtype=tf.int64)
hypothesis shape = tf.constant(0, shape=[3], dtype=tf.int64)

truth indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64)
truth values = tf.constant(2, shape=[3], dtype=tf.int64)
truth shape = tf.constant(2, shape=[3], dtype=tf.int64) 

tf.raw ops.EditDistance(
 hypothesis indices=hypothesis indices,
 hypothesis values=hypothesis values,
 hypothesis shape=hypothesis shape,
 truth indices=truth indices,
 truth values=truth values,
 truth shape=truth shape)

if (g truth == g hypothesis) {
 auto loc = std::inner product(g truth.begin(), g truth.end(),
                output strides.begin(), int64 t{0});
 OP REQUIRES(
   ctx, loc < output elements,
   errors::Internal("Got an inner product ", loc,
            " which would require in writing to outside of "
            "the buffer for the output tensor (max elements ",
            output elements, ")"));
 output t(loc) =
   gtl::LevenshteinDistance<T>(truth seq, hypothesis seq, cmp);
 // ...
}