# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. # pylint: disable=invalid-name, line-too-long, unused-variable, too-many-locals """Space to depth in python""" import numpy as np def space_to_depth_python(data, block_size): """Space to Depth operator in python for NCHW layout. Parameters ---------- data : np.ndarray 4-D with shape [batch, in_channel, in_height, in_width] block_size : int Size of spatial blocks to decompose into channels. Returns ------- d2s_out : np.ndarray 4-D with shape [batch, in_channel * (block_size * block_size), out_height / block_size, out_width / block_size] """ in_n, in_c, in_h, in_w = data.shape new_h = int(in_h / block_size) new_w = int(in_h / block_size) new_c = int(in_c * (block_size * block_size)) expanded = np.reshape(data, newshape=[in_n, in_c, new_h, block_size, new_w, block_size]) transposed = np.transpose(expanded, axes=[0, 3, 5, 1, 2, 4]) newshape = [in_n, new_c, new_h, new_w] d2s_out = np.reshape(transposed, newshape=newshape) return d2s_out