From 14e42b7be5a4fa41fdaa51ead530a4884efcc079 Mon Sep 17 00:00:00 2001
From: Aya SAIDI <aya.saidi@auditeur.ec-lyon.fr>
Date: Fri, 21 Oct 2022 17:05:17 +0100
Subject: [PATCH] Update read_cifar.py
---
read_cifar.py | 19 +++++++++++++------
1 file changed, 13 insertions(+), 6 deletions(-)
diff --git a/read_cifar.py b/read_cifar.py
index 41207b4..362ba3d 100644
--- a/read_cifar.py
+++ b/read_cifar.py
@@ -26,9 +26,9 @@ def read_cifar_batch (batch_path):
data_dict = load_pickle(bp)
data = data_dict['data']
labels = data_dict['labels']
- data = data.reshape(10000,3072)
+ data = data.reshape(len(data),len(data[0]))
data = data.astype('f') #data must be np.float32 array.
- labels = np.array(labels, dtype='i') #labels must be np.int64 array.
+ labels = np.array(labels, dtype='int64') #labels must be np.int64 array.
return data, labels
def read_cifar(directory_path):
@@ -48,7 +48,14 @@ def read_cifar(directory_path):
def split_dataset(data, labels, split):
#This function splits the dataset into a training set and a test set
#It takes as parameter data and labels, two arrays that have the same size in the first dimension. And a split, a float between 0 and 1 which determines the split factor of the training set with respect to the test set.
- data_train, labels_train = shuffle(data.sample(frac=split, random_state=25),)
- data_test = shuffle(data.drop(data_train.index))
-
- return data_train, data_test, labels_train, labels_test
+ data_train=[]
+ data_test=[]
+ labels_train=[]
+ labels_test=[]
+ for i in range(0,len(data)):
+ mask=np.random.randn(len(data[i])) <= split
+ data_train.append(data[i][mask])
+ labels_train.append(labels[i][mask])
+ data_test.append(data[i][~mask])
+ labels_test.append(labels[i][~mask])
+ return data_train, labels_train, data_test, labels_test
--
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