Keras模型似乎没有加载重量

Question

我的模型是keras和tensorflow的组合，如下所示：

with tf.Session(config=config) as sess:
    with tf.device("/device:GPU:0"):


        raw_img_float = tf.placeholder(tf.float32, shape=(None,512,640,3)) #tf.divide(tf.cast(raw_img, tf.float32),tf.constant(255.0))



        bbox_tensor = tf.stack([by1,bx1,by2,bx2],axis=1)

        cropped_img = tf.image.crop_and_resize(image=raw_img_float, # (n, 512, 640, 3)
                                                   boxes=bbox_tensor,# (n,4)
                                                   box_ind=list(range(BATCH)),#[0,1], # (n)
                                                   crop_size=[int(NETWORK_INPUT_SIZE),int(NETWORK_INPUT_SIZE)])

    crop_width = tf.cast(tf.subtract(bx2,bx1), tf.float32)
    new_crop_width = tf.reshape(crop_width, [-1, 1])

    crop_height = tf.cast(tf.subtract(by2,by1), tf.float32)
    new_crop_height = tf.reshape(crop_height, [-1, 1])

    x_coords = tf.placeholder(tf.float32, shape=(None,5))
    y_coords = tf.placeholder(tf.float32, shape=(None,5))

    with tf.device("/device:GPU:1"):
         inception = InceptionV3(weights='imagenet', include_top=False,
                           input_shape=(299,299,3))
         inception_transfer = inception(cropped_img)
         inception_transfer_flatten = Flatten(name='flatten')(inception_transfer)

         inception_do1 = Dropout(0.5)(inception_transfer_flatten)
         inception_regress_x = Dense(5, name='inception_regress_x')(inception_do1)
         inception_regress_y = Dense(5, name='inception_regress_y')(inception_do1)

saver = tf.train.Saver(var_list=tf.trainable_variables())
ckpt = tf.train.get_checkpoint_state('checkpoint1')

sess.run(tf.global_variables_initializer())


if ckpt and ckpt.model_checkpoint_path:
    saver.restore(sess, ckpt.model_checkpoint_path)
    print('RESTORED')

....

if global_step.eval(session=sess) % 200 == 0:
     model_path = 
     os.path.join(os.path.join(os.getcwd(),'checkpoint1'),'model.ckpt')
            saver.save(sess, model_path, global_step=global_step)

我训练了上面的模型，看到成本下降得很顺利。在

但在对权重进行加载和执行时，却显示了完全没有经过训练的模型的结果。。。在

如何保存定义为kerasapi的模型的权重？在

提前谢谢。。。在