mirrors/pytorch-image-models
1
0
Fork 0
mirror of https://github.com/huggingface/pytorch-image-models.git synced 2025-06-03 15:01:08 +08:00
Code Issues Projects Releases Wiki Activity

Merge branch 'metaformer_baselines_for_vision' of https://github.com/fffffgggg54/pytorch-image-models into metaformer_baselines_for_vision

Browse Source
This commit is contained in:
Fredo Guan 2023-01-17 13:23:02 -08:00
commit 7babbfa7a4
1 changed files with 12 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
timm/models/metaformers.py
View File

@ -437,8 +437,9 @@ class MetaFormerBlock(nn.Module):
if res_scale_init_value else nn.Identity()
def forward(self, x):
B, C, H, W = x.shape
x = x.view(B, H, W, C)
#B, C, H, W = x.shape
#x = x.view(B, H, W, C)
x = x.permute(0, 2, 3, 1)
x = self.res_scale1(x) + \
self.layer_scale1(
self.drop_path1(
@ -451,7 +452,8 @@ class MetaFormerBlock(nn.Module):
self.mlp(self.norm2(x))
)
)
x = x.view(B, C, H, W)
#x = x.view(B, C, H, W)
x = x.permute(0, 3, 1, 2)
return x
class MetaFormer(nn.Module):
@ -630,11 +632,12 @@ class MetaFormer(nn.Module):
if pre_logits:
return x
x = self.global_pool(x)
x = x.squeeze()
x = self.norm(x)
#x = self.global_pool(x)
#x = x.squeeze()
#x = self.norm(x)
# (B, H, W, C) -> (B, C)
x = self.head(x)
#x = self.head(x)
x=self.head(self.norm(x.mean([2, 3])))
return x
def forward_features(self, x):
@ -655,6 +658,7 @@ def checkpoint_filter_fn(state_dict, model):
import re
out_dict = {}
for k, v in state_dict.items():
'''
k = k.replace('proj', 'conv')
k = re.sub(r'layer_scale_([0-9]+)', r'layer_scale\1.scale', k)
k = k.replace('network.1', 'downsample_layers.1')
@ -664,6 +668,7 @@ def checkpoint_filter_fn(state_dict, model):
k = k.replace('network.4', 'network.2')
k = k.replace('network.6', 'network.3')
k = k.replace('network', 'stages')
'''
k = re.sub(r'downsample_layers.([0-9]+)', r'stages.\1.downsample', k)
k = re.sub(r'([0-9]+).([0-9]+)', r'\1.blocks.\2', k)
k = k.replace('stages.0.downsample', 'patch_embed')