# concat¶

paddle. concat ( x, axis=0, name=None ) [source]

Concatenates the input along the axis. It doesn’t support 0-D Tensor because it requires a certain axis, and 0-D Tensor doesn’t have any axis.

Parameters
• x (list|tuple) – `x` is a Tensor list or Tensor tuple which is with data type bool, float16, bfloat16, float32, float64, int8, int16, int32, int64, uint8, uint16, complex64, complex128. All the Tensors in `x` must have same data type.

• axis (int|Tensor, optional) – Specify the axis to operate on the input Tensors. Tt should be integer or 0-D int Tensor with shape []. The effective range is [-R, R), where R is Rank(x). When `axis < 0`, it works the same way as `axis+R`. Default is 0.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor, A Tensor with the same data type as `x`.

Examples

```>>> import paddle

>>> x1 = paddle.to_tensor([[1, 2, 3],
...                        [4, 5, 6]])
>>> x2 = paddle.to_tensor([[11, 12, 13],
...                        [14, 15, 16]])
...                        [23, 24]])
>>> zero = paddle.full(shape=[1], dtype='int32', fill_value=0)
>>> # When the axis is negative, the real axis is (axis + Rank(x))
>>> # As follow, axis is -1, Rank(x) is 2, the real axis is 1
>>> out1 = paddle.concat(x=[x1, x2, x3], axis=-1)
>>> out2 = paddle.concat(x=[x1, x2], axis=0)
>>> out3 = paddle.concat(x=[x1, x2], axis=zero)
>>> print(out1)
[[1 , 2 , 3 , 11, 12, 13, 21, 22],
[4 , 5 , 6 , 14, 15, 16, 23, 24]])
>>> print(out2)