首先我们定义一个v3变量
v3 = tf.get_variable('v3', shape=[4,9],initializer=tf.constant_initializer())
查看v3的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
定义v4更改v3的形状
v4 = tf.reshape(v3, [2,2,3,1,3,1,1,1,1])
查看v4的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
>>>v4.shape
TensorShape([Dimension(2), Dimension(2), Dimension(3), Dimension(1), Dimension(3), Dimension(1), Dimension(1), Dimension(1), Dimension(1)])
定义v5更改v3的形状(带有-1)
v5 = tf.reshape(v3, [2,2,-1,3])
查看v5的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
>>>v5.shape
TensorShape([Dimension(2), Dimension(2), Dimension(3), Dimension(3)])
增加v3长度为1的维度
v7 = tf.expand_dims(v3,axis=-1)
查看v7的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
>>>v7.shape
TensorShape([Dimension(4), Dimension(9), Dimension(1)])
在指定的位置增加v3的维度
v8 = tf.expand_dims(v3,axis=1)
查看v8的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
>>>v8.shape
TensorShape([Dimension(4), Dimension(1), Dimension(9)])
进行矩阵的转置
v9 = tf.transpose(v3)
查看v9的形状
>>>v3.shape
TensorShape([Dimension(4), Dimension(9)])
>>>v9.shape
TensorShape([Dimension(9), Dimension(4)])