- paddle. vsplit ( x, num_or_sections, name=None )
Split the input tensor into multiple sub-Tensors along the vertical axis, which is equivalent to
x (Tensor) – A Tensor whose dimension must be greater than 1. The data type is bool, float16, float32, float64, uint8, int8, int32 or int64.
num_or_sections (int|list|tuple) – If
num_or_sectionsis an int, then
num_or_sectionsindicates the number of equal sized sub-Tensors that the
xwill be divided into. If
num_or_sectionsis a list or tuple, the length of it indicates the number of sub-Tensors and the elements in it indicate the sizes of sub-Tensors’ dimension orderly. The length of the list must not be larger than the
x‘s size of axis 0.
name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name .
list[Tensor], The list of segmented Tensors.
import paddle # x is a Tensor of shape [8, 6, 7] x = paddle.rand([8, 6, 7]) out0, out1 = paddle.vsplit(x, num_or_sections=2) print(out0.shape) # [4, 6, 7] print(out1.shape) # [4, 6, 7] out0, out1, out2 = paddle.vsplit(x, num_or_sections=[1, 3, 4]) print(out0.shape) # [1, 6, 7] print(out1.shape) # [3, 6, 7] print(out2.shape) # [4, 6, 7] out0, out1, out2 = paddle.vsplit(x, num_or_sections=[2, 3, -1]) print(out0.shape) # [2, 6, 7] print(out1.shape) # [3, 6, 7] print(out2.shape) # [3, 6, 7]