np.tile(A,reps)建立一個重複數/陣列A reps 次的陣列;tensor轉換為numpy陣列:
阿新 • • 發佈:2018-11-05
>>> a = np.array([0, 1, 2]) >>> np.tile(a, 2) array([0, 1, 2, 0, 1, 2]) >>> np.tile(a, (2, 2)) array([[0, 1, 2, 0, 1, 2], [0, 1, 2, 0, 1, 2]]) >>> np.tile(a, (2, 1, 2)) array([[[0, 1, 2, 0, 1, 2]], [[0, 1, 2, 0, 1, 2]]]) >>> >>> b = np.array([[1, 2], [3, 4]]) >>> np.tile(b, 2) array([[1, 2, 1, 2], [3, 4, 3, 4]]) >>> np.tile(b, (2, 1)) array([[1, 2], [3, 4], [1, 2], [3, 4]]) >>> >>> c = np.array([1,2,3,4]) >>> np.tile(c,(4,1)) array([[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]])
2.tensor轉換為numpy陣列:
對於tensorflow中的tensor “T”,可以用:
T.eval() 函式來轉換為np陣列, 也可以用tf.convert_to_tensor(numpy陣列)來把一個numpy陣列轉換為一個tensor。如: import tensorflow as tf img1 = tf.constant(value=[[[[1],[2],[3],[4]],[[1],[2],[3],[4]],[[1],[2],[3],[4]],[[1],[2],[3],[4]]]],dtype=tf.float32) img2 = tf.constant(value=[[[[1],[1],[1],[1]],[[1],[1],[1],[1]],[[1],[1],[1],[1]],[[1],[1],[1],[1]]]],dtype=tf.float32) img = tf.concat(values=[img1,img2],axis=3) sess=tf.Session() #sess.run(tf.initialize_all_variables()) sess.run(tf.global_variables_initializer()) print("out1=",type(img)) #轉化為numpy陣列 img_numpy=img.eval(session=sess) print("out2=",type(img_numpy)) #轉化為tensor img_tensor= tf.convert_to_tensor(img_numpy) print("out2=",type(img_tensor)) --------------------- 本文來自 ljs_a 的CSDN 部落格 ,全文地址請點選:https://blog.csdn.net/ljs_a/article/details/78758116?utm_source=copy