def commonly_apply_update_verify_v2(self):
if not context.executing_eagerly():
self.skipTest('Skip graph mode test.')
first_inputs = np.array(range(6), dtype=np.int64)
second_inputs = np.array(range(3, 9), dtype=np.int64)
overdue_features = np.array(range(3), dtype=np.int64)
updated_features = np.array(range(3, 9), dtype=np.int64)
all_features = np.array(range(9), dtype=np.int64)
with self.session(config=default_config):
var = de.get_variable('sp_var',
key_dtype=dtypes.int64,
value_dtype=dtypes.float32,
initializer=-0.1,
dim=2)
embed_w, trainable = de.embedding_lookup(var,
first_inputs,
return_trainable=True,
name='re0212')
policy = de.TimestampRestrictPolicy(var)
self.assertAllEqual(policy.status.size(), 0)
policy.apply_update(first_inputs)
self.assertAllEqual(policy.status.size(), len(first_inputs))
time.sleep(1)
policy.apply_update(second_inputs)
self.assertAllEqual(policy.status.size(), len(all_features))
keys, tstp = policy.status.export()
kvs = sorted(dict(zip(keys.numpy(), tstp.numpy())).items())
tstp = np.array([x[1] for x in kvs])
for x in tstp[overdue_features]:
for y in tstp[updated_features]:
self.assertLess(x, y)
def commonly_apply_update_verify(self):
first_inputs = np.array(range(3), dtype=np.int64)
second_inputs = np.array(range(1, 4), dtype=np.int64)
overdue_features = np.array([0], dtype=np.int64)
updated_features = np.array(range(1, 4), dtype=np.int64)
with session.Session(config=default_config) as sess:
ids = array_ops.placeholder(dtypes.int64)
var = de.get_variable('sp_var',
key_dtype=ids.dtype,
value_dtype=dtypes.float32,
initializer=-0.1,
init_size=256,
dim=2)
embed_w, trainable = de.embedding_lookup(var,
ids,
return_trainable=True,
name='wf7843')
policy = de.TimestampRestrictPolicy(var)
update_op = policy.apply_update(ids)
self.assertAllEqual(sess.run(policy.status.size()), 0)
sess.run(update_op, feed_dict={ids: first_inputs})
self.assertAllEqual(sess.run(policy.status.size()), 3)
time.sleep(1)
sess.run(update_op, feed_dict={ids: second_inputs})
self.assertAllEqual(sess.run(policy.status.size()), 4)
keys, tstp = sess.run(policy.status.export())
kvs = sorted(dict(zip(keys, tstp)).items())
tstp = np.array([x[1] for x in kvs])
for x in tstp[overdue_features]:
for y in tstp[updated_features]:
self.assertLess(x, y)