Tensorflow中所有的数据都称为Tensor，可以是一个变量、数组或者多维数组。Tensor 有几个重要的属性:
Rank：纬数，比如scalar rank=0, vector rank=1, matrix rank=2
Shape：形状，比如vector shape=[D0], matrix shape=[D0, D1]
类型：数据类型，比如tf.float32, tc.uint8等
Rank与Shape关系如下表所示
| Rank | Shape | Dimension number | Example |
| 0 | [] | 0-D | A 0-D tensor. A scalar. |
| 1 | [D0] | 1-D | A 1-D tensor with shape [5]. |
| 2 | [D0, D1] | 2-D | A 2-D tensor with shape [3, 4]. |
| 3 | [D0, D1, D2] | 3-D | A 3-D tensor with shape [1, 4, 3]. |
| n | [D0, D1, … Dn-1] | n-D | A tensor with shape [D0, D1, … Dn-1]. |