正确地在Django中加载Keras模型，支持多租户。

I am try to write a REST api in django that uses a Keras model to return a prediction. However the load_model() function takes some time to load the model and I don't want my users to have to wait so long (each time the model is initialized). What would be the correct way to initialize the model so that is is loaded once and the predictions are done using that same model?

我尝试在django中编写一个REST api，它使用Keras模型来返回一个预测。但是load_model()函数需要一些时间来加载模型，而且我不希望我的用户需要等待这么长时间(每次模型初始化)。初始化模型的正确方法是什么，这样就加载了一次，并且预测是用相同的模型完成的?

On a side note one method that I thought cold be possible was to initialize the model in settings.py as below :

另一方面，我认为冷的一个方法是在设置中初始化模型。py如下:

settings.py

settings.py

json_file=open("model.json","r")
loaded_json=json_file.read()
json_file.close()

model=model_from_json(loaded_json)
model.load_weights("model.h5")
MODEL=model

And then in my views.py I use this variable MODEL as :

然后在我的观点中。py我使用这个变量模型为:

views.py

views.py

from django.conf import settings
model=settings.MODEL
def index():
    print "Predicting"
    res=model.predict(numpy.stack([test_img]))
    print res

This works great if only one user is active at a time ( model is initialized once and all subsequent predictions are done using that model). However if multiple users are active at a time then it works good for the call that came first but the latter call gives the error

如果一个用户每次都是活动的(模型被初始化一次，并且所有后续的预测都是使用该模型完成的)，这种方法就非常有效。但是，如果多个用户同时处于活动状态，那么它对最先出现的调用有效，但是后一个调用给出了错误。

'NoneType' object has no attribute 'shape'
Apply node that caused the error: ConvOp{('imshp', (31, 31, 32)),('kshp', (3, 3)),('nkern', 64),('bsize', None),('dx', 1),('dy', 1),('out_mode', 'valid'),('unroll_batch', None),('unroll_kern', None),('unroll_patch', True),('imshp_logical', (31, 31, 32)),('kshp_logical', (3, 3)),('kshp_logical_top_aligned', True)}(InplaceDimShuffle{0,2,3,1}.0, InplaceDimShuffle{3,2,0,1}.0)
Toposort index: 13
Inputs types: [TensorType(float32, 4D), TensorType(float32, 4D)]
Inputs shapes: [(1L, 31L, 31L, 32L), 'No shapes']
Inputs strides: [(123008L, 124L, 4L, 3844L), 'No strides']
Inputs values: ['not shown', None]
Outputs clients: [[Elemwise{Composite{(i0 * ((i1 + i2) + Abs((i1 + i2))))}}[(0, 1)](TensorConstant{(1L, 1L, 1..1L) of 0.5}, ConvOp{('imshp', (31, 31, 32)),('kshp', (3, 3)),('nkern', 64),('bsize', None),('dx', 1),('dy', 1),('out_mode', 'valid'),('unroll_batch', None),('unroll_kern', None),('unroll_patch', True),('imshp_logical', (31, 31, 32)),('kshp_logical', (3, 3)),('kshp_logical_top_aligned', True)}.0, InplaceDimShuffle{x,0,x,x}.0)]]

How should i load the model properly so that it can be accessed simultaneously?

我应该如何正确加载模型以便同时访问它?

Thank you for your time.

谢谢你抽出时间来。

1 个解决方案

#1

Look here please https://github.com/keras-team/keras/issues/2397#issuecomment-254919212

看这里请https://github.com/keras-team/keras/issues/2397 # issuecomment - https://github.com/keras-team/keras/issues/2397

eg. in Django settings construct the model...

如。在Django设置中构建模型…

modelFile = 'path_to_my_model.h5'    
pipe = joblib.load(modelFile.replace('.h5','.pkl'))
model = models.load_model(modelFile)
pipe.steps.append(('nn', model))    
graph = tensorflow.get_default_graph()

and then reuse like this in Django REST method:

然后再用Django REST方法进行重用:

import myDjango.settings as sett
# ...

@csrf_exempt
def evaluate(request):
    """
    Do the evaluation.
    """
    if request.method == 'POST':
        data = JSONParser().parse(request)
        i = data['inputs']

        outputs = MyMlClass.PredictArray( sett.graph, sett.pipe , i, 'model.h5' )

        return JsonResponse(outputs, status=201, safe=False)

Works for me very well (VisualStudio Django project, Python 3.6). Construction of the model in REST handler is not recommended and in fact won't work - it will work just in the very first invocation.

非常适合我(VisualStudio Django项目，Python 3.6)。不建议在REST处理程序中构建模型，实际上也不会起作用——它将在第一次调用中起作用。

#1