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test.py
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test.py
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from network import network
import numpy as np
import json
def test(X,y):
global model
accuracies = []
costs = []
for i in range(0,X.shape[0],64):
end = min(i+64,X.shape[0])
model.test(X[i:end],y[i:end],accuracies,costs)
accuracies = np.array(accuracies)
costs = np.array(costs)
print("Accuracy : ",np.mean(accuracies))
print("Cost : ",np.sum(costs))
if __name__ == "__main__":
global model
model = network.load("model.json")
data = json.load(open("data/data.json","rb"))
trainX = np.array(data['trainX'])
trainY = np.array(data['trainY'],dtype=np.int32)
validX = np.array(data['validX'])
validY = np.array(data['validY'],dtype=np.int32)
testX = np.array(data['testX'])
testY = np.array(data['testY'],dtype=np.int32)
print("TRAIN SET")
test(trainX,trainY)
print("\n\nVALIDATION SET")
test(validX,validY)
print("\n\nTEST SET")
test(testX,testY)