def load_checkpoint(use_placeholder=False, session=None):
dataset = build("data")
model = build("model")
if use_placeholder:
inputs = dataset.get_placeholders()
else:
inputs = dataset()
info = model.eval(inputs)
if session is None:
session = tf.Session()
saver = tf.train.Saver()
checkpoint_dir = get_checkpoint_dir()
checkpoint_file = tf.train.latest_checkpoint(checkpoint_dir)
saver.restore(session, checkpoint_file)
print('Successfully restored Checkpoint "{}"'.format(checkpoint_file))
# print variables
variables = tf.global_variables() + tf.local_variables()
for row in snt.format_variables(variables, join_lines=False):
print(row)
return {
"session": session,
"model": model,
"info": info,
"inputs": inputs,
"dataset": dataset,
}
def print_model(model: snt.Module):
print(f'{model.__class__.__name__} : {model.name}\n')
print(snt.format_variables(model.variables))
n_params = np.sum([np.prod(v.shape) for v in model.variables])
trainable_params = np.sum(
[np.prod(v.shape) for v in model.trainable_variables])
print(f'\nParams: {trainable_params} trainable out of {n_params}')
def testFormatVariables(self):
with tf.variable_scope("m1"):
v1 = tf.get_variable("v1", shape=[3, 4])
with tf.device("/gpu"):
with tf.variable_scope("m2"):
v2 = tf.get_local_variable("v2", shape=[5, 6])
self.assertEqual(snt.format_variables([v2, v1]),
_EXPECTED_FORMATTED_VARIABLE_LIST)
def testFormatVariables(self, use_resource, expected):
with tf.variable_scope("m1"):
v1 = tf.get_variable("v1", shape=[3, 4], use_resource=use_resource)
with tf.device("/gpu"):
with tf.variable_scope("m2"):
v2 = tf.get_local_variable(
"v2", shape=[5, 6], use_resource=use_resource)
self.assertEqual(snt.format_variables([v2, v1]), expected)
def testFormatVariables(self):
with tf.variable_scope("m1"):
v1 = tf.get_variable("v1", shape=[3, 4])
with tf.device("/gpu"):
with tf.variable_scope("m2"):
v2 = tf.get_local_variable("v2", shape=[5, 6])
self.assertEqual(snt.format_variables([v2, v1]),
_EXPECTED_FORMATTED_VARIABLE_LIST)
def testFormatVariables(self, use_resource, expected):
with tf.variable_scope("m1"):
v1 = tf.get_variable("v1", shape=[3, 4], use_resource=use_resource)
with tf.device("/gpu"):
with tf.variable_scope("m2"):
v2 = tf.get_local_variable(
"v2", shape=[5, 6], use_resource=use_resource)
self.assertEqual(snt.format_variables([v2, v1]), expected)
def testFormatVariables(self):
with tf.variable_scope("m1"):
v1 = tf.get_variable("v1", shape=[3, 4])
with tf.variable_scope("m2"):
v2 = tf.get_variable("v2", shape=[5, 6])
self.assertEquals(snt.format_variables([v2, v1]),
("Variable Shape Type\n"
"m1/v1:0 3x4 tf.float32\n"
"m2/v2:0 5x6 tf.float32"))
