Swap recurrence

This commit is contained in:
James Betker 2020-10-17 08:40:28 -06:00
parent 6141aa1110
commit c1c9c5681f
2 changed files with 19 additions and 20 deletions

View File

@ -3,7 +3,7 @@ from torch import nn
from models.archs.SPSR_arch import ImageGradientNoPadding
from models.archs.arch_util import ConvGnLelu, ExpansionBlock2, ConvGnSilu, ConjoinBlock, MultiConvBlock, \
FinalUpsampleBlock2x
FinalUpsampleBlock2x, ReferenceJoinBlock
from models.archs.spinenet_arch import SpineNet
from utils.util import checkpoint
@ -69,10 +69,10 @@ class ChainedEmbeddingGenWithStructure(nn.Module):
def __init__(self, depth=10, recurrent=False):
super(ChainedEmbeddingGenWithStructure, self).__init__()
self.recurrent = recurrent
self.initial_conv = ConvGnLelu(3, 64, kernel_size=7, bias=True, norm=False, activation=False)
if recurrent:
self.initial_conv_rec = ConvGnLelu(6, 64, kernel_size=7, bias=True, norm=False, activation=False)
else:
self.initial_conv = ConvGnLelu(3, 64, kernel_size=7, bias=True, norm=False, activation=False)
self.recurrent_process = ConvGnLelu(3, 64, kernel_size=3, stride=2, norm=False, bias=True, activation=False)
self.recurrent_join = ReferenceJoinBlock(64, residual_weight_init_factor=.01, final_norm=False, kernel_size=1, depth=3, join=False)
self.spine = SpineNet(arch='49', output_level=[3, 4], double_reduce_early=False)
self.blocks = nn.ModuleList([BasicEmbeddingPyramid() for i in range(depth)])
self.structure_joins = nn.ModuleList([ConjoinBlock(64) for i in range(3)])
@ -83,11 +83,10 @@ class ChainedEmbeddingGenWithStructure(nn.Module):
def forward(self, x, recurrent=None):
emb = checkpoint(self.spine, x)
fea = self.initial_conv(x)
if self.recurrent:
fea = torch.cat([x,recurrent], dim=1)
fea = self.initial_conv_rec(x)
else:
fea = self.initial_conv(x)
rec = self.recurrent_process(recurrent)
fea, _ = self.recurrent_join(fea, rec)
grad = fea
for i, block in enumerate(self.blocks):
fea = fea + checkpoint(block, fea, *emb)

View File

@ -1,24 +1,24 @@
import functools
import logging
from collections import OrderedDict
import munch
import torch
import logging
import torchvision
from munch import munchify
import models.archs.SRResNet_arch as SRResNet_arch
import models.archs.discriminator_vgg_arch as SRGAN_arch
import models.archs.DiscriminatorResnet_arch as DiscriminatorResnet_arch
import models.archs.DiscriminatorResnet_arch_passthrough as DiscriminatorResnet_arch_passthrough
import models.archs.RRDBNet_arch as RRDBNet_arch
import models.archs.feature_arch as feature_arch
import models.archs.SwitchedResidualGenerator_arch as SwitchedGen_arch
import models.archs.SPSR_arch as spsr
import models.archs.SRResNet_arch as SRResNet_arch
import models.archs.StructuredSwitchedGenerator as ssg
import models.archs.rcan as rcan
import models.archs.SwitchedResidualGenerator_arch as SwitchedGen_arch
import models.archs.discriminator_vgg_arch as SRGAN_arch
import models.archs.feature_arch as feature_arch
import models.archs.panet.panet as panet
from collections import OrderedDict
import torchvision
import functools
from models.archs.ChainedEmbeddingGen import ChainedEmbeddingGen, ChainedEmbeddingGenWithStructure, \
ChainedEmbeddingGenWithStructureR2
import models.archs.rcan as rcan
from models.archs.ChainedEmbeddingGen import ChainedEmbeddingGen, ChainedEmbeddingGenWithStructure
logger = logging.getLogger('base')