CODEWITHSUNDEEP
pythonnumpymachine-learningneural-network
Ishank Gulati
Ishank Gulati

Reputation: 655

How to save weights of a neural network

I am facing problem in saving weights of a trained neural network in a text file. Here is my code

def nNetwork(trainingData,filename):

    lamda = 1
    input_layer = 1200
    output_layer = 10
    hidden_layer = 25
    X=trainingData[0]
    y=trainingData[1]
    theta1 = randInitializeWeights(1200,25)
    theta2 = randInitializeWeights(25,10)
    m,n = np.shape(X)
    yk = recodeLabel(y,output_layer)
    theta = np.r_[theta1.T.flatten(), theta2.T.flatten()]

    X_bias = np.r_[np.ones((1,X.shape[0])), X.T]
    #conjugate gradient algo
    result = scipy.optimize.fmin_cg(computeCost,fprime=computeGradient,x0=theta,args=(input_layer,hidden_layer,output_layer,X,y,lamda,yk,X_bias),maxiter=100,disp=True,full_output=True )
    print result[1]  #min value
    theta1,theta2 = paramUnroll(result[0],input_layer,hidden_layer,output_layer)
    counter = 0
    for i in range(m):
        prediction = predict(X[i],theta1,theta2)
        actual = y[i]
        if(prediction == actual):
            counter+=1
    print  str(counter *100/m) + '% accuracy'

    data = {"Theta1":[theta1],
            "Theta2":[theta2]}
    op=open(filename,'w')
    json.dump(data,op)
    op.close()

def paramUnroll(params,input_layer,hidden_layer,labels):
    theta1_elems = (input_layer+1)*hidden_layer
    theta1_size = (input_layer+1,hidden_layer)
    theta2_size = (hidden_layer+1,labels)
    theta1 = params[:theta1_elems].T.reshape(theta1_size).T
    theta2 = params[theta1_elems:].T.reshape(theta2_size).T
    return theta1, theta2

I am getting the following error raise TypeError(repr(o) + " is not JSON serializable")

Please give a solution or any other way to save the weights so that I can easily load them In some other code.

Upvotes: 2

Views: 4829

Answers (1)

igordsm
igordsm

Reputation: 464

The easiest way to save numpy arrays to pure text is to execute numpy.savetxt (and load it with numpy.loadtxt). However, if you want to save both using the JSON format you can write the files using a StringIO instance:

with StringIO as theta1IO:
    numpy.savetxt(theta1IO, theta1)
    data = {"theta1": theta1IO.getvalue() }
    # write as JSON as usual

You can do that with the other parameters as well.

To retrieve the data you can do:

# read data from JSON
with StringIO as theta1IO:
    theta1IO.write(data['theta1'])
    theta1 = numpy.loadtxt(theta1IO)

Upvotes: 3

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