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ronzillia/training.py

Created May 14, 2018 14:29
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training.py
# balance data via loss for each batch
x_train, y_train,index = batch_data
label=np.argmax(y_train,axis=1)
num_pos=np.count_nonzero(label)
num_neg=len(label)-num_pos
pos_weight=np.true_divide(num_neg+1,len(label)+1)
neg_weight=np.true_divide(num_pos+1,len(label)+1)
class_weight=np.array([[neg_weight,pos_weight]])
# plus one to avoid all-zero and all-one problem
_ ,train_cost= sess.run([train_op,classification_loss_op], feed_dict={input_x: x_train,input_y_classification: y_train,bs_holder:batch_size,training_flag:True,tf_class_weight:class_weight})
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