def testApplyBucketsWithKeys(self):
with tf.compat.v1.Graph().as_default():
values = tf.constant([
-100, -0.05, 0.05, 0.25, 0.15, 100, -100, 0, 4.3, 4.5, 4.4, 4.6, 100
],
dtype=tf.float32)
keys = tf.constant([
'a', 'a', 'a', 'a', 'a', 'a', 'b', 'missing', 'b', 'b', 'b', 'b', 'b'
])
key_vocab = tf.constant(['a', 'b'])
# Pre-normalization boundaries: [[0, 0.1, 0.2], [4.33, 4.43, 4.53]]
bucket_boundaries = tf.constant([0.0, 0.5, 1.0, 1.5, 2.0],
dtype=tf.float32)
scales = 1.0 / (
tf.constant([0.2, 4.53], dtype=tf.float32) -
tf.constant([0, 4.33], dtype=tf.float32))
shifts = tf.constant([0, 1.0 - (4.33 * 5)], dtype=tf.float32)
num_buckets = tf.constant(4, dtype=tf.int64)
buckets = mappers._apply_buckets_with_keys(values, keys, key_vocab,
bucket_boundaries, scales,
shifts, num_buckets)
with self.test_session() as sess:
sess.run(tf.compat.v1.tables_initializer())
output = sess.run(buckets)
self.assertAllEqual([0, 0, 1, 3, 2, 3, 0, -1, 0, 2, 1, 3, 3], output)
def testApplyBucketsWithKeys(self):
values = tf.constant(
[-100, -0.05, 0.05, 0.25, 0.15, 100, -100, 4.3, 4.5, 4.4, 4.6, 100],
dtype=tf.float32)
keys = tf.constant(
['a', 'a', 'a', 'a', 'a', 'a', 'b', 'b', 'b', 'b', 'b', 'b'])
key_vocab = tf.constant(['a', 'b'])
bucket_boundaries = tf.constant([[0, .1, .2], [4.33, 4.43, 4.53]],
dtype=tf.float32)
buckets = mappers._apply_buckets_with_keys(values, keys, key_vocab,
bucket_boundaries)
with self.test_session() as sess:
sess.run(tf.tables_initializer())
output = sess.run(buckets)
self.assertAllEqual([0, 0, 1, 3, 2, 3, 0, 0, 2, 1, 3, 3], output)
