Python 使用flask时,培训和预测模块API不会同时运行

Python 使用flask时,培训和预测模块API不会同时运行,python,tensorflow,flask,keras,faster-rcnn,Python,Tensorflow,Flask,Keras,Faster Rcnn,我用过烧瓶 当我不添加K.clear_session()时,我将在训练和预测模块中遇到此错误 错误无法将提要dict键解释为张量:张量张量(\“占位符:0\”,shape=(7,7,3,64),dtype=float32)不是此图的元素。“} 如果我使用K.clear_session()运行文件,它会停止当前工作模块并启动我要运行的模块,就像预测模块正在运行一样,然后我点击训练模块它会停止预测并运行训练 请帮帮我似乎你正在尝试在不同的课程中进行训练和预测 由于您尚未共享源代码,我可以向您提出以下

我用过烧瓶

当我不添加
K.clear_session()
时,我将在训练和预测模块中遇到此错误

错误无法将提要dict键解释为张量:张量张量(\“占位符:0\”,shape=(7,7,3,64),dtype=float32)不是此图的元素。“}

如果我使用
K.clear_session()
运行文件,它会停止当前工作模块并启动我要运行的模块,就像预测模块正在运行一样,然后我点击训练模块它会停止预测并运行训练


请帮帮我

似乎你正在尝试在不同的课程中进行训练和预测

由于您尚未共享源代码,我可以向您提出以下建议

  • 为培训和预测创建不同的占位符
  • 将sess设为全局变量,以便对于Flask GET/POST decorator函数,共享同一个会话对象

  • 你好Rajan,如果你能格式化你的问题,使其易于阅读,这将对每个人都有帮助。我正在使用coco预训练模型与keras。请检查此链接,他们在代码中没有使用会话变量,所以我在哪里添加这个?
    Weights:  coco
    Dataset:  ./files/coco/dataset
    Logs:  ./files/coco/log1/
    ..........................config.........................
    
    Configurations:
    BACKBONE                       resnet101
    BACKBONE_STRIDES               [4, 8, 16, 32, 64]
    BATCH_SIZE                     1
    BBOX_STD_DEV                   [0.1 0.1 0.2 0.2]
    DETECTION_MAX_INSTANCES        100
    DETECTION_MIN_CONFIDENCE       0.744
    DETECTION_NMS_THRESHOLD        0.3
    GPU_COUNT                      1
    GRADIENT_CLIP_NORM             5.0
    IMAGES_PER_GPU                 1
    IMAGE_MAX_DIM                  1024
    IMAGE_META_SIZE                24
    IMAGE_MIN_DIM                  800
    IMAGE_MIN_SCALE                0
    IMAGE_RESIZE_MODE              square
    IMAGE_SHAPE                    [1024 1024    3]
    LEARNING_MOMENTUM              0.9
    LEARNING_RATE                  0.001
    LOSS_WEIGHTS                   {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0}
    MASK_POOL_SIZE                 14
    MASK_SHAPE                     [28, 28]
    MAX_GT_INSTANCES               100
    MEAN_PIXEL                     [123.7 116.8 103.9]
    MINI_MASK_SHAPE                (56, 56)
    NAME                           surgery
    NUM_CLASSES                    12
    POOL_SIZE                      7
    POST_NMS_ROIS_INFERENCE        1000
    POST_NMS_ROIS_TRAINING         2000
    ROI_POSITIVE_RATIO             0.33
    RPN_ANCHOR_RATIOS              [0.5, 1, 2]
    RPN_ANCHOR_SCALES              (32, 64, 128, 256, 512)
    RPN_ANCHOR_STRIDE              1
    RPN_BBOX_STD_DEV               [0.1 0.1 0.2 0.2]
    RPN_NMS_THRESHOLD              0.7
    RPN_TRAIN_ANCHORS_PER_IMAGE    256
    STEPS_PER_EPOCH                100
    TRAIN_BN                       False
    TRAIN_ROIS_PER_IMAGE           200
    USE_MINI_MASK                  True
    USE_RPN_ROIS                   True
    VALIDATION_STEPS               20
    WEIGHT_DECAY                   0.0001
    
    
    Loading weights  ./routeDefine/coco/mrcnn/mask_rcnn_coco.h5
    Exception in thread Thread-4:
    Traceback (most recent call last):
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1092, in _run
        subfeed, allow_tensor=True, allow_operation=False)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3490, in as_graph_element
        return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3569, in _as_graph_element_locked
        raise ValueError("Tensor %s is not an element of this graph." % obj)
    ValueError: Tensor Tensor("Placeholder:0", shape=(7, 7, 3, 64), dtype=float32) is not an element of this graph.
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/threading.py", line 916, in _bootstrap_inner
        self.run()
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/threading.py", line 864, in run
        self._target(*self._args, **self._kwargs)
      File "/home/ubuntu/AI_Project6/routeDefine/coco/saveModelmn.py", line 111, in model
        main()
      File "/home/ubuntu/AI_Project6/routeDefine/coco/saveModelmn.py", line 108, in main
        trainmodel()
      File "/home/ubuntu/AI_Project6/routeDefine/coco/savemodel.py", line 342, in trainmodel
        "mrcnn_bbox", "mrcnn_mask"])
      File "/home/ubuntu/AI_Project6/routeDefine/coco/mrcnn/modelsave.py", line 2101, in load_weights
        saving.load_weights_from_hdf5_group_by_name(f, layers)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/keras/engine/saving.py", line 1022, in load_weights_from_hdf5_group_by_name
        K.batch_set_value(weight_value_tuples)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2440, in batch_set_value
        get_session().run(assign_ops, feed_dict=feed_dict)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 929, in run
        run_metadata_ptr)
      File "/home/ubuntu/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1095, in _run
        'Cannot interpret feed_dict key as Tensor: ' + e.args[0])
    TypeError: Cannot interpret feed_dict key as Tensor: Tensor Tensor("Placeholder:0", shape=(7, 7, 3, 64), dtype=float32) is not an element of this graph.