Comments (9)
I've found that this problem (has no field named "ceil_mode") could be solved by changing the "ceil_mode: false" line to "round_mode: FLOOR" in the prototxt file to fit the new version of Caffe. The new version of Caffe use round_mode: CEIL/FLOOR to choose which mode to use (default CEIL).
I have tested this modification on Densenet161 and it didn't seem to affect the performance.
Hope this can help.
from densenet-caffe.
Tnx for the update, now I get the following error:
Cannot copy param 0 weights from layer 'conv1'; shape mismatch. Source param shape is 96 3 7 7 (14112); target param shape is 64 3 7 7 (9408). To learn this layer's parameters from scratch rather than copying from a saved net, rename the layer.
*** Check failure stack trace: ***
Aborted (core dumped)
It seems conv1
should be renamed to something cuz I found similar issue ppl solved this new problem here, but how do we fix it for DenseNet161
?
Did u encounter the same problem?
from densenet-caffe.
Sorry, I didn't encounter this problem. Maybe you can check whether your .caffemodel file matches the .prototxt file correctly... I mean, the conv1 layer of DenseNet_121 and DenseNet_169 is 64 3 7 while the conv1 layer of DenseNet_161 is 96 3 7, maybe you have mismatched DenseNet_169.caffemodel to DenseNet_161.prototxt or something like that I guess?
from densenet-caffe.
Oohh! yes, u're absolutely right!
I had mistakenly had different weight.caffemodel
and deploy.prototxt
files! now it works flawless with modification u suggested: replace ceil_mode: false
in deploy.prototxt
to round_mode: FLOOR
.
Cheers,
from densenet-caffe.
Congrats! Happy to hear that!
from densenet-caffe.
In another PC in which caffe-gpu
is installed via anaconda, I get error for both ceil_mode: false
and round_mode: FLOOR
though!
deploy.prototxt
with ceil_mode: false
:
[libprotobuf ERROR google/protobuf/text_format.cc:307] Error parsing text-format caffe.NetParameter: 54:14: Message type "caffe.PoolingParameter" has no field named "ceil_mode".
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0517 18:27:14.369987 16944 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: MODELS/DenseNet161/ImageNet/deploy.prototxt
*** Check failure stack trace: ***
Aborted
deploy.prototxt
with round_mode: FLOOR
:
[libprotobuf ERROR google/protobuf/text_format.cc:307] Error parsing text-format caffe.NetParameter: 54:15: Message type "caffe.PoolingParameter" has no field named "round_mode".
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0517 18:32:19.467856 17462 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: MODELS/DenseNet161/ImageNet/deploy.prototxt
*** Check failure stack trace: ***
Aborted
This is my python specification and caffe version:
Python 2.7.17 |Anaconda, Inc.| (default, Oct 21 2019, 19:04:46)
[GCC 7.3.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe
>>> caffe.__version__
'1.0.0'
I also noticed #32 is an open issue regarding this but is there any workaround for anaconda version of caffe?
from densenet-caffe.
I don't have any idea about this error message... A possible solution is to check those corresponding lines mentioned by https://github.com/BVLC/caffe/pull/3057/files (see also #1) in caffe-gpu from anaconda to see what params are actually used and modify the .prototxt file.
from densenet-caffe.
Alternatively, you can install another caffe from source code and use sys.path.insert to specify which caffe to use.
eg:
import sys
sys.path.insert(0,"path/to/your/caffe/python")
import caffe
from densenet-caffe.
@LYC-vio I'm afraid installing caffe from source is an option cuz this a univ GPU clusters and we do not get sudo
prriviledge for package installation/manipulation!
from densenet-caffe.
Related Issues (20)
- how to use your deploy.prototoxt to 2 classification HOT 3
- Do you have Network definition in Python? HOT 1
- Where can I get the train_val.prototxt ? HOT 2
- about some details HOT 2
- The shapes in netscope are wrong? HOT 1
- About some computing problem HOT 1
- Scope name problem when conventing from LiuZhuang13's code HOT 3
- DenseNet和Faster R-CNN的结合 HOT 3
- { lr_mult: 1 decay_mult: 1}的含义 HOT 16
- Not achieving your reported performance! HOT 3
- when i train my own dataset,the loss is not decrease and it is always about 6.97 HOT 1
- cuDNN does not allow an eps value less than 1e-5
- Hello, I was using caffe once, using a custom version of Microsoft, I do not know how to solve this problem, I hope you can help me.
- Question about scale=0.017 HOT 1
- problems about the data preprocessing HOT 2
- Fine-tune Dense 201 problem
- 关于densenet训练阶段BN层的设置 HOT 1
- 能不能提供提供训练代码以及测试代码
- Thankyou!
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