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gpleiss
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efficient_densenet_pytorch
A memory-efficient implementation of DenseNets
MIT License
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Fix syntax error.
#78
irryden
closed
1 year ago
0
Excuse me, what is the cause of this problem?
#77
SzLSzC
opened
1 year ago
1
Question about the place of checkpoint (shared memory allocation)
#76
mert-kurttutan
closed
1 year ago
1
will the inference memory reduced too?
#75
emergencyd
opened
1 year ago
1
Correct normalization values for CIFAR-10
#74
abduallahmohamed
closed
3 years ago
0
The BN running mean&var with torch.utils.checkpoint.checkpoint
#73
ljn114514
closed
3 years ago
2
The function received no value for the required argument: data
#72
June-Luo
closed
3 years ago
2
AttributeError: module 'fire' has no attribute 'Fire'
#71
MRLQ-Q
opened
3 years ago
8
How can I apply this to my own model?
#70
CXMANDTXW
opened
3 years ago
1
test error interpretation
#69
abduallahmohamed
closed
4 years ago
1
Is the normalizatin values for CIFAR-10 correct?
#68
abduallahmohamed
closed
3 years ago
1
Fixed number of parameters for DenseNet-BC
#67
vinhtq115
closed
4 years ago
0
Is this really memory efficient?
#66
leonardishere
opened
4 years ago
1
Is it possible to provide ImageNet pre-trained models?
#65
zc3945
closed
4 years ago
2
use adaptive_avg_pool2d instead of avg_pool2d
#64
aneeshnema
closed
4 years ago
1
网络内存消耗?
#63
long2double
closed
3 years ago
0
What is bn_size?
#62
w32zhong
closed
4 years ago
3
dropout not in 3x3 convolutional layer
#61
lizhenstat
opened
4 years ago
0
Question: why use bn_function on 1x1 conv, not on 3x3 conv
#60
lizhenstat
closed
4 years ago
1
How about the version of the torchvision, project killer and pyhon-fire?
#59
jwnirvana
closed
4 years ago
1
Unable to run demo.
#58
frost26k
closed
4 years ago
0
Fixed a bug in demo.py.
#57
zyh911
closed
5 years ago
1
New adaptive pooling layer.
#56
CielAl
closed
4 years ago
1
Inference time issue
#55
youngwanLEE
closed
5 years ago
1
Can we test using the trained model.
#54
TJstory
closed
5 years ago
1
Should there be a global average pooling layer before the classifier?
#53
yangzy-yzy
closed
5 years ago
0
What is the minimum GPU memory required? Still breaks for me in a single GPU
#52
PabloRR100
opened
5 years ago
1
Validation dataset is being augmented as well
#51
garyfanhku
closed
5 years ago
1
does this code support pytorch1.0 and the jit feature for c++ online deployment?
#50
mmxuan18
opened
5 years ago
3
Create LICENSE
#49
gpleiss
closed
5 years ago
0
Could you add a License?
#48
csrhddlam
closed
5 years ago
1
Segmentation fault (core dumped) error for multiple GPUs
#47
theonegis
opened
5 years ago
6
Number of parameters doesn't match with naïve implementation
#46
PabloRR100
closed
5 years ago
3
Is there any option to run ImageNet in this demo?
#45
jugol
closed
5 years ago
1
torch.utils.checkpoint cost too much memory than previous 0.3 version
#44
mingminzhen
closed
5 years ago
1
Softmax layer is missing in the code.
#43
srinidhiPY
closed
5 years ago
2
Can't not train when using a 256*256 dataset
#42
nessieyang
closed
5 years ago
2
[Trivial] Fix a typo in demo.py doc string.
#41
grapeot
closed
5 years ago
1
pretrained densenet169 weights
#40
Kexiii
opened
6 years ago
8
Fix multigpu issue: denselayer's input and weights are not in same gpu
#39
ZhengRui
closed
6 years ago
1
FP become slower after upgrade to 0.4
#38
DesertsP
closed
6 years ago
5
not worked in python3 environment
#37
tengshaofeng
closed
6 years ago
3
MultiGPU efficient densenets are slow
#36
wandering007
opened
6 years ago
14
Pytorch 0.4 compatibility (uses checkpointing)
#35
gpleiss
closed
6 years ago
2
The final test accuracy
#34
ustctf-zz
closed
6 years ago
6
Test failed on PyTorch 0.3.1 with CUDA 9.0
#33
DesertsP
closed
6 years ago
3
Compatibility with PyTorch 0.4
#32
seyiqi
closed
6 years ago
11
Multi-GPU model in pytorch0.3 consumes much more memory than pytorch0.1 version
#31
ZhengRui
closed
6 years ago
8
Input data size
#30
g5996706
closed
6 years ago
3
Update densenet_efficient.py
#29
wandering007
closed
6 years ago
8
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