def test_dumpFileArgsError(self):
try:
ujson.dump([], '')
except TypeError:
pass
else:
assert False, 'expected TypeError'
def test_dumpFileArgsError(self):
try:
ujson.dump([], '')
except TypeError:
pass
else:
assert False, 'expected TypeError'
def test_dumpToFileLikeObject(self):
class filelike:
def __init__(self):
self.bytes = ''
def write(self, bytes):
self.bytes += bytes
f = filelike()
ujson.dump([1, 2, 3], f)
self.assertEquals("[1,2,3]", f.bytes)
def test_dumpToFileLikeObject(self):
class filelike:
def __init__(self):
self.bytes = ''
def write(self, bytes):
self.bytes += bytes
f = filelike()
ujson.dump([1, 2, 3], f)
self.assertEqual("[1,2,3]", f.bytes)
def main(unused_args):
config = SmallConfig()
model_path = FLAGS.model
output_path = FLAGS.output
np.random.seed()
# data_loader
if FLAGS.num_sample:
config.batch_size = FLAGS.num_sample
with tf.Graph().as_default(), tf.Session() as session:
config.num_steps = 1
model, model_validate = build_model(session, config, model_path)
sequence_list = simulate_sequence(session, model_validate)
if output_path:
ensure_base_dir(output_path)
with open(output_path, 'w') as f:
json.dump(sequence_list, f)
else:
json.dumps(sequence_list)
def test_dumpToFile(self):
f = StringIO()
ujson.dump([1, 2, 3], f)
self.assertEquals("[1,2,3]", f.getvalue())
def on_epoch_end(self, epoch, logs={}):
"""
Args:
epoch:
logs:
"""
self.epoch_number += 1
current_val_loss = logs.get("val_loss")
current_loss = logs.get("loss")
if (self.last_loss - current_loss) > 0.01:
current_weights_name = "weights" + str(
self.current_model_number) + ".h5"
print("loss improved from " + str(self.last_loss) + " to " +
str(current_loss) + ", Saving model to " +
current_weights_name)
self.model.save_weights("models/" + current_weights_name)
self.model.save_weights("models/last_weight.h5")
self.current_model_number += 1
self.last_loss = current_loss
with open("log.txt", "a+") as logfile:
logfile.write(
"________________________________________________________\n"
)
logfile.write("EPOCH =")
logfile.write(str(epoch) + "\n")
logfile.write("TRAIN_LOSS =")
logfile.write(str(current_loss) + "\n")
logfile.write("VAL_LOSS =")
logfile.write(str(current_val_loss) + "\n")
logfile.write(
"---------------------------------------------------------\n"
)
logfile.write("TRAIN_Age_LOSS =")
logfile.write(str(logs.get("age_estimation_loss")) + "\n")
logfile.write("TRAIN_GENDER_LOSS =")
logfile.write(str(logs.get("gender_probablity_loss")) + "\n")
logfile.write(
"---------------------------------------------------------\n"
)
logfile.write("TRAIN_Age_ACC =")
logfile.write(str(logs.get("age_estimation_acc")) + "\n")
logfile.write("TRAIN_GENDER_ACC =")
logfile.write(str(logs.get("gender_probablity_acc")) + "\n")
logfile.write(
"---------------------------------------------------------\n"
)
logfile.write("VAL_Age_LOSS =")
logfile.write(str(logs.get("val_age_estimation_loss")) + "\n")
logfile.write("VAL_GENDER_LOSS =")
logfile.write(
str(logs.get("val_gender_probablity_loss")) + "\n")
logfile.write(
"---------------------------------------------------------\n"
)
logfile.write("VAL_Age_ACC =")
logfile.write(str(logs.get("val_age_estimation_acc")) + "\n")
logfile.write("VAL_GENDER_ACC =")
logfile.write(
str(logs.get("val_gender_probablity_acc")) + "\n")
logfile.write(
"********************************************************\n"
)
with open("epoch_number.json", "w+") as json_file:
data = {"epoch_number": self.epoch_number}
json.dump(data, json_file, indent=4)
def test_dumpToFile(self):
f = io.StringIO()
ujson.dump([1, 2, 3], f)
self.assertEqual("[1,2,3]", f.getvalue())
