def testWarmStartVarWithVocabBothVarsPartitioned(self):
prev_vocab_path = self._write_vocab(["apple", "banana", "guava", "orange"],
"old_vocab")
self._create_prev_run_var(
"fruit_weights",
shape=[4, 1],
initializer=[[0.5], [1.], [1.5], [2.]],
partitioner=lambda shape, dtype: [2, 1])
# New vocab with elements in reverse order and two new elements.
new_vocab_path = self._write_vocab(
["orange", "guava", "banana", "apple", "raspberry",
"blueberry"], "new_vocab")
# New session and new graph.
with ops.Graph().as_default() as g:
with self.test_session(graph=g) as sess:
fruit_weights = variable_scope.get_variable(
"fruit_weights",
shape=[6, 1],
initializer=[[0.], [0.], [0.], [0.], [0.], [0.]],
partitioner=lambda shape, dtype: [2, 1])
ws_util._warmstart_var_with_vocab(fruit_weights, new_vocab_path, 6,
self.get_temp_dir(), prev_vocab_path)
sess.run(variables.global_variables_initializer())
self.assertTrue(
isinstance(fruit_weights, variables.PartitionedVariable))
fruit_weights_vars = fruit_weights._get_variable_list()
self.assertAllEqual([[2.], [1.5], [1.]],
fruit_weights_vars[0].eval(sess))
self.assertAllEqual([[0.5], [0.], [0.]],
fruit_weights_vars[1].eval(sess))
def testWarmStartVarWithVocabConstrainedOldVocabSize(self):
prev_vocab_path = self._write_vocab(["apple", "banana", "guava", "orange"],
"old_vocab")
self._create_prev_run_var(
"fruit_weights", initializer=[[0.5], [1.], [1.5], [2.]])
# New vocab with elements in reverse order and one new element.
new_vocab_path = self._write_vocab(
["orange", "guava", "banana", "apple", "raspberry"], "new_vocab")
# New session and new graph.
with ops.Graph().as_default() as g:
with self.test_session(graph=g) as sess:
fruit_weights = variable_scope.get_variable(
"fruit_weights", initializer=[[0.], [0.], [0.], [0.], [0.]])
ws_util._warmstart_var_with_vocab(
fruit_weights,
new_vocab_path,
5,
self.get_temp_dir(),
prev_vocab_path,
previous_vocab_size=2)
sess.run(variables.global_variables_initializer())
# Old vocabulary limited to ['apple', 'banana'].
self.assertAllEqual([[0.], [0.], [1.], [0.5], [0.]],
fruit_weights.eval(sess))
