diff --git a/networks/layers/layer.py b/networks/layers/layer.py index c51b045..463e097 100644 --- a/networks/layers/layer.py +++ b/networks/layers/layer.py @@ -203,7 +203,10 @@ def loss_reg(self): def backprop(self,dOut=None): return self.dx - + + def accuracy(self,scores,y): + return 1.0*np.sum(np.argmax(scores,axis=1)==y)/y.shape[0] + class SVM(): def __init__(self): @@ -222,6 +225,9 @@ def loss_reg(self): def backprop(self,dOut=None): return self.dx + + def accuracy(self,scores,y): + return 1.0*np.sum(np.argmax(scores,axis=1)==y)/y.shape[0] def MSE(): @@ -241,6 +247,9 @@ def loss_reg(self): def backprop(self,dOut=None): return self.dx + + def accuracy(self,scores,y): + return rel_error(scores,y) class CrossEntropy(): @@ -260,7 +269,10 @@ def loss_reg(self): def backprop(self,dOut=None): return self.dx - + + def accuracy(self,scores,y): + return 1.0*np.sum(round(scores,0)==y)/y.shape[0] + class BatchNormalization(object): def __init__(self,gamma,beta,params,update_params): diff --git a/networks/network.py b/networks/network.py index 3269b85..efc12bb 100644 --- a/networks/network.py +++ b/networks/network.py @@ -211,10 +211,7 @@ def batch_test(self,X,y): loss += layer.loss_reg() scores,inp = self.layers[-1].forward(inp,y) - return self.accuracy(scores,y),inp+loss - - def accuracy(self,scores,y): - return 1.0*np.sum(np.argmax(scores,axis=1)==y)/y.shape[0] + return self.layers[-1].accuracy(scores,y),inp+loss def predict(self,X): inp = X diff --git a/setup.py b/setup.py index 1a5c60c..b8a0c08 100644 --- a/setup.py +++ b/setup.py @@ -3,12 +3,12 @@ setup( name = 'networks', packages = ['networks','networks/layers','networks/layers/util/','networks/layers/descent/'], - version = '0.3.5', # Ideally should be same as your GitHub release tag varsion + version = '0.3.6', # Ideally should be same as your GitHub release tag varsion description = 'Allows to create NN models', author = 'Shharrnam Chhatpar', author_email = 'sharnam19.nc@gmail.com', url = 'https://github.com/sharnam19/Networks', - download_url = 'https://github.com/sharnam19/Networks/archive/v0.3.5.tar.gz', + download_url = 'https://github.com/sharnam19/Networks/archive/v0.3.6.tar.gz', keywords = ['machine-learning', 'deep-learning','neural-networks','linear regression', 'logistic regression'], classifiers = [],