#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright 1999-2020 Alibaba Group Holding Ltd. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from ..datasource import tensor as astensor from .split import split [docs]def dsplit(a, indices_or_sections): """ Split tensor into multiple sub-tensors along the 3rd axis (depth). Please refer to the `split` documentation. `dsplit` is equivalent to `split` with ``axis=2``, the array is always split along the third axis provided the tensor dimension is greater than or equal to 3. See Also -------- split : Split a tensor into multiple sub-arrays of equal size. Examples -------- >>> import mars.tensor as mt >>> x = mt.arange(16.0).reshape(2, 2, 4) >>> x.execute() array([[[ 0., 1., 2., 3.], [ 4., 5., 6., 7.]], [[ 8., 9., 10., 11.], [ 12., 13., 14., 15.]]]) >>> mt.dsplit(x, 2).execute() [array([[[ 0., 1.], [ 4., 5.]], [[ 8., 9.], [ 12., 13.]]]), array([[[ 2., 3.], [ 6., 7.]], [[ 10., 11.], [ 14., 15.]]])] >>> mt.dsplit(x, mt.array([3, 6])).execute() [array([[[ 0., 1., 2.], [ 4., 5., 6.]], [[ 8., 9., 10.], [ 12., 13., 14.]]]), array([[[ 3.], [ 7.]], [[ 11.], [ 15.]]]), array([], dtype=float64)] """ ary = a a = astensor(a) if a.ndim < 3: raise ValueError('dsplit only works on tensors of 3 or more dimensions') return split(ary, indices_or_sections, 2)