def testMultipleHashTables(self):
with self.test_session() as sess:
shared_name = ''
default_val = -1
table1 = tf.HashTable(tf.string, tf.int64, default_val,
shared_name)
table2 = tf.HashTable(tf.string, tf.int64, default_val,
shared_name)
table3 = tf.HashTable(tf.string, tf.int64, default_val,
shared_name)
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2], tf.int64)
table1.initialize_from(keys, values)
table2.initialize_from(keys, values)
table3.initialize_from(keys, values)
tf.initialize_all_tables().run()
self.assertAllEqual(3, table1.size().eval())
self.assertAllEqual(3, table2.size().eval())
self.assertAllEqual(3, table3.size().eval())
input_string = tf.constant(['brain', 'salad', 'tank'])
output1 = table1.lookup(input_string)
output2 = table2.lookup(input_string)
output3 = table3.lookup(input_string)
out1, out2, out3 = sess.run([output1, output2, output3])
self.assertAllEqual([0, 1, -1], out1)
self.assertAllEqual([0, 1, -1], out2)
self.assertAllEqual([0, 1, -1], out3)
def testSignatureMismatch(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2], tf.int64)
init = table.initialize_from(keys, values)
init.run()
input_string = tf.constant([1, 2, 3], tf.int64)
with self.assertRaises(TypeError):
table.lookup(input_string)
with self.assertRaises(TypeError):
tf.HashTable(tf.string, tf.int64, 'UNK', shared_name)
def testInitializationWithInvalidDataTypes(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = [0, 1, 2]
values = ['brain', 'salad', 'surgery']
with self.assertRaises(TypeError):
table.initialize_from(keys, values)
def testInitializationWithInvalidDimensions(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2, 3, 4], tf.int64)
with self.assertRaises(ValueError):
table.initialize_from(keys, values)
def testNotInitialized(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
input_string = tf.constant(['brain', 'salad', 'surgery'])
output = table.lookup(input_string)
with self.assertRaisesOpError('Table not initialized'):
output.eval()
def testInitializeTwice(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2], tf.int64)
init = table.initialize_from(keys, values)
init.run()
with self.assertRaisesOpError('Table already initialized'):
init.run()
def testHashTableWithTensorDefault(self):
with self.test_session():
shared_name = ''
default_val = tf.constant(-1, tf.int64)
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2], tf.int64)
init = table.initialize_from(keys, values)
init.run()
input_string = tf.constant(['brain', 'salad', 'tank'])
output = table.lookup(input_string)
result = output.eval()
self.assertAllEqual([0, 1, -1], result)
def testHashTableInitWithNumPyArrays(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = np.array(['brain', 'salad', 'surgery'], dtype=np.str)
values = np.array([0, 1, 2], dtype=np.int64)
init = table.initialize_from(keys, values)
init.run()
self.assertAllEqual(3, table.size().eval())
input_string = tf.constant(['brain', 'salad', 'tank'])
output = table.lookup(input_string)
result = output.eval()
self.assertAllEqual([0, 1, -1], result)
def testHashTableFindHighRank(self):
with self.test_session():
shared_name = ''
default_val = -1
table = tf.HashTable(tf.string, tf.int64, default_val, shared_name)
# Initialize with keys and values tensors.
keys = tf.constant(['brain', 'salad', 'surgery'])
values = tf.constant([0, 1, 2], tf.int64)
init = table.initialize_from(keys, values)
init.run()
self.assertAllEqual(3, table.size().eval())
input_string = tf.constant([['brain', 'salad'], ['tank',
'tarkus']])
output = table.lookup(input_string)
result = output.eval()
self.assertAllEqual([[0, 1], [-1, -1]], result)
def testDTypes(self):
with self.test_session():
shared_name = ''
default_val = -1
with self.assertRaises(TypeError):
tf.HashTable([tf.string], tf.string, default_val, shared_name)
