调试经验——Tensorflow中生成独热编码（One-hot encoding）

在学习吴恩达深度学习的过程中，出现了独热编码这一概念。

说明：

代码：

def one_hot_matrix(labels, C):
    """
    Creates a matrix where the i-th row corresponds to the ith class number and the jth column
                     corresponds to the jth training example. So if example j had a label i. Then entry (i,j) 
                     will be 1. 
                     
    Arguments:
    labels -- vector containing the labels 
    C -- number of classes, the depth of the one hot dimension
    
    Returns: 
    one_hot -- one hot matrix
    """
    
    ### START CODE HERE ###
    
    # Create a tf.constant equal to C (depth), name it 'C'. (approx. 1 line)
    C = tf.constant(C, name='C')
    
    # Use tf.one_hot, be careful with the axis (approx. 1 line)
    one_hot_matrix = tf.one_hot(labels, C, axis=0)
    
    # Create the session (approx. 1 line)
    sess = tf.compat.v1.Session()
    
    # Run the session (approx. 1 line)
    one_hot = sess.run(one_hot_matrix)
    
    # Close the session (approx. 1 line). See method 1 above.
    sess.close()
    
    ### END CODE HERE ###
    
    return one_hot

测试代码：

labels = np.array([1,2,3,0,2,1])
one_hot = one_hot_matrix(labels, C = 4)
print ("one_hot = " + str(one_hot))

测试结果：

备注：本来想在Excel中实现这个功能，尝试了一下，没有成功，暂时放弃！