Keras model working fine locally but won't wor

Question

I'm working on this heart disease detection problem using different classifiers. What I'm doing is i'm saving my model in h5 file & creating an object of it & returning the response in json format.

but the same model won't work on flask api that ran perfectly on my terminal.

here is my Neural network:

def ANN():
    global x_train,x_test,y_train,y_test
    model = Sequential()

    #implicit input layer combined with hidden layer
    model.add(Dense(units = 13, kernel_initializer = 'uniform', activation = 'relu', input_dim = 13))

    #hidden layer 2
    model.add(Dense(units = 13, kernel_initializer = 'uniform', activation = 'relu', input_dim = 13))

    #output layer
    model.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))

    model.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])

    #fitting with optimal hyperparameters
    model.fit(x_train, y_train, batch_size = 25, nb_epoch = 287)

    return {'model':model,
            'accuracy':accuracy_score(model.predict(x_test) > 0.5,y_test)*100}

after saving the model in .h5 file, In my flask api,

ann = load_model('ann8524.h5')
print(ann.predict(x_test)) #test set, for just checking.

here's the error message:

* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit) [2018-12-20 23:37:43,548] 
ERROR in app: Exception on /heart/predict

[GET] Traceback (most recent call last):   
File "C:\python_installation\lib\site-packages\flask\app.py", line 1813, in full_dispatch_request
    rv = self.dispatch_request()   
File "C:\python_installation\lib\site-packages\flask\app.py", line 1799, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)   
File "C:\python_installation\lib\site-packages\flask_restful\__init__.py", line 458, in wrapper
    resp = resource(*args, **kwargs)   
File "C:\python_installation\lib\site-packages\flask\views.py", line 88, in view
    return self.dispatch_request(*args, **kwargs)   
File "C:\python_installation\lib\site-packages\flask_restful\__init__.py", line 573, in dispatch_request
    resp = meth(*args, **kwargs)   
File "app.py", line 41, in get
    print(ann.predict(x_test))   
File "C:\python_installation\lib\site-packages\keras\engine\training.py", line 1164, in predict
    self._make_predict_function()   
File "C:\python_installation\lib\site-packages\keras\engine\training.py", line 554, in _make_predict_function
    **kwargs)   
File "C:\python_installation\lib\site-packages\keras\backend\tensorflow_backend.py", line 2744, in function
    return Function(inputs, outputs, updates=updates, **kwargs)   
File "C:\python_installation\lib\site-packages\keras\backend\tensorflow_backend.py", line 2546, in __init__
    with tf.control_dependencies(self.outputs):   
File "C:\python_installation\lib\site-packages\tensorflow\python\framework\ops.py", line 5004, in control_dependencies
    return get_default_graph().control_dependencies(control_inputs)   
File "C:\python_installation\lib\site-packages\tensorflow\python\framework\ops.py", line 4543, in control_dependencies
    c = self.as_graph_element(c)   
File "C:\python_installation\lib\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 "C:\python_installation\lib\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("dense_3/Sigmoid:0", shape=(?, 1), dtype=float32) is not an element of this graph.

127.0.0.1 - - [20/Dec/2018 23:37:43] "[1m[35mGET /heart/predict HTTP/1.1[0m" 500 -

But it works perfectly fine in Spyder. (exact same code)

Answer 1

You need to get default graph from Tensorflow, following these steps should solve this issue:

import tensorflow as tf
ann = load_model('ann8524.h5')
graph = tf.get_default_graph()

def your_handler():
    global graph
    with graph.as_default():
        print(ann.predict(x_test))