split¶

paddle.fluid.layers.nn. split ( input, num_or_sections, dim=- 1, name=None ) [source]

Split the input tensor into multiple sub-Tensors.

Parameters

• input (Tensor) – A N-D Tensor. The data type is bool, float16, float32, float64, int32 or int64.

• num_or_sections (int|list|tuple) – If num_or_sections is int, then the num_or_sections indicates the number of equal sized sub-Tensors that the input will be divided into. If num_or_sections is 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 mustn’t be larger than the input ‘s size of specified dim.

• dim (int|Tensor, optional) – The dimension along which to split, it can be a scalar with type int or a Tensor with shape [1] and data type int32 or int64. If \(dim < 0\), the dimension to split along is \(rank(input) + dim\). Default is -1.

• 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 .

Returns

The list of segmented Tensors.

Return type

list(Tensor)

Example

import paddle.fluid as fluid

# input is a Tensor which shape is [3, 9, 5]
input = fluid.data(
     name="input", shape=[3, 9, 5], dtype="float32")

out0, out1, out2 = fluid.layers.split(input, num_or_sections=3, dim=1)
# out0.shape [3, 3, 5]
# out1.shape [3, 3, 5]
# out2.shape [3, 3, 5]

out0, out1, out2 = fluid.layers.split(input, num_or_sections=[2, 3, 4], dim=1)
# out0.shape [3, 2, 5]
# out1.shape [3, 3, 5]
# out2.shape [3, 4, 5]

out0, out1, out2 = fluid.layers.split(input, num_or_sections=[2, 3, -1], dim=1)
# out0.shape [3, 2, 5]
# out1.shape [3, 3, 5]
# out2.shape [3, 4, 5]

# dim is negative, the real dim is (rank(input) + axis) which real
# value is 1.
out0, out1, out2 = fluid.layers.split(input, num_or_sections=3, dim=-2)
# out0.shape [3, 3, 5]
# out1.shape [3, 3, 5]
# out2.shape [3, 3, 5]