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

Fix Mobilenet V3 model name for sotabench. Minor res2net cleanup.

Browse Source
This commit is contained in:
rwightman 2019-09-05 15:47:56 -07:00
parent b5a8bb52fd
commit d3ba34ee7e
2 changed files with 5 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
sotabench.py
View File

@ -1,3 +1,4 @@
import torch
from torchbench.image_classification import ImageNet from torchbench.image_classification import ImageNet
from timm import create_model from timm import create_model
from timm.data import resolve_data_config, create_transform from timm.data import resolve_data_config, create_transform
@ -77,7 +78,7 @@ model_list = [
_entry('mixnet_m', 'MixNet-M', '1907.09595'), _entry('mixnet_m', 'MixNet-M', '1907.09595'),
_entry('mixnet_s', 'MixNet-S', '1907.09595'), _entry('mixnet_s', 'MixNet-S', '1907.09595'),
_entry('mnasnet_100', 'MnasNet-B1', '1807.11626'), _entry('mnasnet_100', 'MnasNet-B1', '1807.11626'),
_entry('mobilenetv3_100', 'MobileNet V3(1.0)', '1905.02244', _entry('mobilenetv3_100', 'MobileNet V3-Large 1.0', '1905.02244',
model_desc='Trained in PyTorch with RMSProp, exponential LR decay, and hyper-params matching ' model_desc='Trained in PyTorch with RMSProp, exponential LR decay, and hyper-params matching '
'paper as closely as possible.'), 'paper as closely as possible.'),
_entry('resnet18', 'ResNet-18', '1812.01187'), _entry('resnet18', 'ResNet-18', '1812.01187'),
@ -216,4 +217,6 @@ for m in model_list:
data_root=os.environ.get('IMAGENET_DIR', './imagenet') data_root=os.environ.get('IMAGENET_DIR', './imagenet')
) )
torch.cuda.empty_cache()

2
timm/models/res2net.py
View File

@ -58,7 +58,7 @@ class Bottle2neck(nn.Module):
super(Bottle2neck, self).__init__() super(Bottle2neck, self).__init__()
assert dilation == 1 and previous_dilation == 1 # FIXME support dilation assert dilation == 1 and previous_dilation == 1 # FIXME support dilation
self.scale = scale self.scale = scale
self.is_first = True if stride > 1 or downsample is not None else False self.is_first = stride > 1 or downsample is not None
self.num_scales = max(1, scale - 1) self.num_scales = max(1, scale - 1)
width = int(math.floor(planes * (base_width / 64.0))) * cardinality width = int(math.floor(planes * (base_width / 64.0))) * cardinality
outplanes = planes * self.expansion outplanes = planes * self.expansion