accuracy calculation mistake

[Yajiang]

` for i in range(batch_size):
if corr_weight is not None:
loss += tf.reduce_sum(tot_loss[i][inlier_mask[i]]) /
(tf.reduce_sum(corr_weight[i][inlier_mask[i]]) + 1e-6)
else:
loss += tf.reduce_mean(tot_loss[i][inlier_mask[i]])
cnt_err_row = tf.count_nonzero(
err_row[i][inlier_mask[i]], dtype=tf.float32)
cnt_err_col = tf.count_nonzero(
err_col[i][inlier_mask[i]], dtype=tf.float32)
tot_err = cnt_err_row + cnt_err_col
accuracy += 1. -
tf.math.divide_no_nan(tot_err, tf.cast(
inlier_num[i], tf.float32)) / batch_size / 2.

matched_mask = tf.logical_and(tf.equal(err_row, 0), tf.equal(err_col, 0))
matched_mask = tf.logical_and(matched_mask, inlier_mask)

loss /= batch_size
accuracy /= batch_size`

As I noticed, there maybe a little mistake in accuracy calculation. I don't think the accuracy calculation should divide batch_size as in your code.