fast-reid/fastreid/layers/batch_drop.py

# encoding: utf-8
"""
@author:  liaoxingyu
@contact: sherlockliao01@gmail.com
"""

import random

from torch import nn


class BatchDrop(nn.Module):
    """ref: https://github.com/daizuozhuo/batch-dropblock-network/blob/master/models/networks.py
    batch drop mask
    """

    def __init__(self, h_ratio, w_ratio):
        super(BatchDrop, self).__init__()
        self.h_ratio = h_ratio
        self.w_ratio = w_ratio

    def forward(self, x):
        if self.training:
            h, w = x.size()[-2:]
            rh = round(self.h_ratio * h)
            rw = round(self.w_ratio * w)
            sx = random.randint(0, h - rh)
            sy = random.randint(0, w - rw)
            mask = x.new_ones(x.size())
            mask[:, :, sx:sx + rh, sy:sy + rw] = 0
            x = x * mask
        return x