import torch.nn as nn
import torch
import util.util as util
from .innerPatchSoftShiftTripleModule import InnerPatchSoftShiftTripleModule
# TODO: Make it compatible for show_flow.
#
class InnerPatchSoftShiftTriple(nn.Module):
def __init__(self, shift_sz=1, stride=1, mask_thred=1, triple_weight=1, fuse=True, layer_to_last=3):
super(InnerPatchSoftShiftTriple, self).__init__()
self.shift_sz = shift_sz
self.stride = stride
self.mask_thred = mask_thred
self.triple_weight = triple_weight
self.show_flow = False # default false. Do not change it to be true, it is computation-heavy.
self.flow_srcs = None # Indicating the flow src(pixles in non-masked region that will shift into the masked region)
self.fuse = fuse
self.layer_to_last = layer_to_last
self.softShift = InnerPatchSoftShiftTripleModule()
def set_mask(self, mask_global):
mask = util.cal_feat_mask(mask_global, self.layer_to_last)
self.mask = mask
return self.mask
# If mask changes, then need to set cal_fix_flag true each iteration.
def forward(self, input):
_, self.c, self.h, self.w = input.size()
# Just pass self.mask in, instead of self.flag.
final_out = self.softShift(input, self.stride, self.triple_weight, self.mask, self.mask_thred, self.shift_sz, self.show_flow, self.fuse)
if self.show_flow:
self.flow_srcs = self.softShift.get_flow_src()
return final_out
def get_flow(self):
return self.flow_srcs
def set_flow_true(self):
self.show_flow = True
def set_flow_false(self):
self.show_flow = False
def __repr__(self):
return self.__class__.__name__+ '(' \
+ ' ,triple_weight ' + str(self.triple_weight) + ')'
