把csdn上一个颜值打分程序放到jupyter notebook上跑，程序如下：
from keras.applications import ResNet50
from keras import optimizers
from keras.layers import Dense, Dropout
from keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint
from keras.backend.tensorflow_backend import set_session
os.environ['CUDA_VISIBLE_DEVICES'] = '1'
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
set_session(tf.Session(config=config))
batch_size = 32
target_size = (224, 224)
resnet = ResNet50(include_top=False, pooling='avg')
resnet.trainable = False
# keras.backend.clear_session()
# tf.reset_default_graph()
model = Sequential()
model.add(resnet)
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))
print(model.summary())
model.compile(optimizer=optimizers.SGD(lr=0.001), loss='mse')
callbacks = [EarlyStopping(monitor='val_loss',
patience=5,
verbose=1,
min_delta=1e-4),
ReduceLROnPlateau(monitor='val_loss',
patience=3,
factor=0.1,
epsilon=1e-4),
ModelCheckpoint(monitor='val_loss',
filepath='weights/resnet50_weights.hdf5',
save_best_only=True,
save_weights_only=True)]
train_file_list, test_file_list = read_data_list()
train_steps_per_epoch = math.ceil(len(train_file_list) / batch_size)
test_steps_per_epoch = math.ceil(len(test_file_list) / batch_size)
train_data = DataGenerator(train_file_list, target_size,batch_size)
test_data = DataGenerator(test_file_list, target_size, batch_size)
model.fit_generator(train_data,
steps_per_epoch=train_steps_per_epoch,
epochs=30,
verbose=1,
callbacks=callbacks,
validation_data=test_data,
validation_steps=test_steps_per_epoch,
use_multiprocessing=True)
结果引发如下错误：
ValueError Traceback (most recent call last)
in ()
20 # tf.reset_default_graph()
21 model = Sequential()
---> 22 model.add(resnet)
23 model.add(Dropout(0.5))
24 model.add(Dense(1, activation='sigmoid'))
...Ignoring many tracing lines...
ValueError: Variable bn_conv1/moving_mean/biased already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:
File "xxxx\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1269, in init
self._traceback = _extract_stack()
File "xxxx\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "xxxx\anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
op_def=op_def)
我按照网上说法在model语句前加了tf.reset_default_graph() ，结果又产生新的error：
ValueError: Tensor("conv1_1/kernel:0", shape=(7, 7, 3, 64), dtype=float32_ref) must be from the same graph as Tensor("resnet50/conv1_pad/Pad:0", shape=(?, ?, ?, 3), dtype=float32).
又按照网上说法加了keras.backend.clear_session()，总共加的两句前前后后在很多地方放了测试，结果都会有新的问题：
ValueError: Tensor("conv1/kernel:0", shape=(7, 7, 3, 64), dtype=float32_ref) must be from the same graph as Tensor("resnet50/conv1_pad/Pad:0", shape=(?, ?, ?, 3), dtype=float32).
请教大牛究竟该如何彻底解决问题。
