Error prompt
urllib.error.URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:833)>Error reason
Global cancel certificate validation
Solution:
import ssl
ssl._create_default_https_context = ssl._create_unverified_contextThe following error occurred when compiling pytorch by Jetson:
/usr/include/c++/7/cmath: In static member function ‘static scalar_t at::native::div_floor_kernel_cuda(at::TensorIterator&)::<lambda()>::<lambda()>::<lambda(scalar_t, scalar_t)>::_FUN(scalar_t, scalar_t)’:
/usr/include/c++/7/cmath:1302:38: internal compiler error: Segmentation fault
{ return __builtin_copysignf(__x, __y); }
This is because compiling STD::copysign() is too expensive for the Jetson platform.
There are two solutions:
1. upgrade pytorch to version 1.9. Pytorch 1.9 uses the C10::CUDA::compat::copysign()function instead of the STD::copysign()function.
2. Submit and modify the code according to this:
Workaround arm64 gcc error in std::copysign on Jetson platforms
ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index) RuntimeError: expected scalar type Long but found Float
Solution: Just convert label to torch.LongTensor.
label = label.type(torch.LongTensor)
**
Error (s) in loading state_dict for GeneratorResNet
**
cause of the problem: check whether we use dataparallel for multi GPU during training. The model generated by this method will automatically add key: module
observe the error message:
you can find that the key values in the model are more modules
Solution:
1. Delete the module
gentmps=torch.load("./saved_models/generator_%d.pth" % opt.epoch)
distmps = torch.load("./saved_models/discriminator_%d.pth" % opt.epoch)
from collections import OrderedDict
new_gens = OrderedDict()
new_diss = OrderedDict()
for k, v in gentmps.items():
name = k.replace('module.','') # remove 'module.'
new_gens[name] = v #The value corresponding to the key value of the new dictionary is a one-to-one value.
for k, v in distmps.items():
name = k.replace('module.','') # remove 'module.'
new_diss[name] = v #The value corresponding to the key value of the new dictionary is a one-to-one value.
generator.load_state_dict(new_gens)
discriminator.load_state_dict(new_diss)
This error occurred when installing git + GitHub web page. The full name is
Collecting git+https://github.com/pytorch/tnt.git@master
Cloning https://github.com/pytorch/tnt.git (to revision master) to c:\users\lee\appdata\local\temp\pip-req-build-lbtbze6v
Running command git clone -q https://github.com/pytorch/tnt.git 'C:\Users\lee\AppData\Local\Temp\pip-req-build-lbtbze6v'
fatal: unable to access 'https://github.com/pytorch/tnt.git/': OpenSSL SSL_read: Connection was reset, errno 10054
WARNING: Discarding git+https://github.com/pytorch/tnt.git@master. Command errored out with exit status 128: git clone -q https://github.com/pytorch/tnt.git 'C:\Users\lee\AppData\Local\Temp\pip-req-build-lbtbze6v' Check the logs for fu
ll command output.
ERROR: Command errored out with exit status 128: git clone -q https://github.com/pytorch/tnt.git 'C:\Users\lee\AppData\Local\Temp\pip-req-build-lbtbze6v' Check the logs for full command output.
Solution:
pip install git+git://github.com/ildoonet/pytorch-gradual-warmup-lr.git
Successfully installed
Collecting git+git://github.com/ildoonet/pytorch-gradual-warmup-lr.git
Cloning git://github.com/ildoonet/pytorch-gradual-warmup-lr.git to c:\users\lee\appdata\local\temp\pip-req-build-ncz3svwe
Running command git clone -q git://github.com/ildoonet/pytorch-gradual-warmup-lr.git 'C:\Users\lee\AppData\Local\Temp\pip-req-build-ncz3svwe'
Resolved git://github.com/ildoonet/pytorch-gradual-warmup-lr.git to commit 6b5e8953a80aef5b324104dc0c2e9b8c34d622bd
Building wheels for collected packages: warmup-scheduler
Building wheel for warmup-scheduler (setup.py) ... done
Created wheel for warmup-scheduler: filename=warmup_scheduler-0.3.2-py3-none-any.whl size=3917 sha256=4cef133c28685f1e5a70364fd6546a3d4d995fe49584781b1024d3707f9f222f
Stored in directory: C:\Users\lee\AppData\Local\Temp\pip-ephem-wheel-cache-m6_t0cfl\wheels\d2\57\4d\3adb5d109151933485f2b4387f61a90ff8e669f50fc8f1fa14
Successfully built warmup-scheduler
Installing collected packages: warmup-scheduler
Successfully installed warmup-scheduler-0.3.2
Failed environment install leads to “unable to create process using” error
Maybe it’s because there are too many environments installed in CONDA, and you copy them yourself. Suddenly, CONDA fails.
As long as you enter CONDA activate, it will report
Fatal error in launcher: Unable to create process using '"d:\project\gae_gan\ddgk\venv\scripts\python.exe" "D:\Programs\Anaconda3\Scripts\conda.exe" '
Error.
Finally found a very simple solution
Enter directly in the console
***\Anaconda3\Scripts\activate
Then restart console to be fine!
Referenec:
https://stackoverflow.com/questions/59721699/anaconda-is-unable-to-create-process-on-windows10
Error Messages: RuntimeError: version_ <= kMaxSupportedFileFormatVersion INTERNAL ASSERT FAILED at /pytorch/caffe2/serialize/inline_container.cc:132, please report a bug to PyTorch. Attempted to read a PyTorch file with version 3, but the maximum supported version for reading is 2. Your PyTorch installation may be too old. (init at /pytorch/caffe2/serialize/inline_container.cc:132) frame #0: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x33 (0x7fdcd0189193 in /home/a430/intel/intelpython3/envs/zayn/lib/python3.6/site-packages/torch/lib/libc10.so) frame #1: caffe2::serialize::PyTorchStreamReader::init() + 0x1f5b (0x7fdcd33119eb in /home/a430/intel/intelpython3/envs/zayn/lib/python3.6/site-packages/torch/lib/libtorch.so) frame #2: caffe2::serialize::PyTorchStreamReader::PyTorchStreamReader(std::string const&) + 0x64 (0x7fdcd3312c04 in /home/a430/intel/intelpython3/envs/zayn/lib/python3.6/site-packages/torch/lib/libtorch.so) frame #3: <unknown function> + 0x6c53a6 (0x7fdd1b2423a6 in /home/a430/intel/intelpython3/envs/zayn/lib/python3.6/site-packages/torch/lib/libtorch_python.so) frame #4: <unknown function> + 0x2961c4 (0x7fdd1ae131c4 in /home/a430/intel/intelpython3/envs/zayn/lib/python3.6/site-packages/torch/lib/libtorch_python.so) <omitting python frames>
Some people say there is a problem with the torch version. My torch version is 1.4.0, try upgrading to 1.6.0, torchvision was upgraded to 0.7.0, this problem will be reported:
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.
Just follow the hint and add map_location=torch.device(‘cpu’) when loading the model, as follows:
best_model = torch.load("../weights/September01-Unet-se_resnext50_32x4d/checkpoint.pth.tar", map_location=torch.device('cpu'))
Error:
runtimeerror: one of the variables needed for gradient computation has been modified by an inplace operation
Analysis: the new version of pytorch integrates variable and tensor into one tensor, and the inplace operation can be used for variable before, but errors will occur when using tensor
Check whether there is the following expression
x += res #error
Change to
x = x + res
No error is reported
When pytorch loads the model, if some judgment is used in the model, the judgment is used as the selection execution condition, but it is also saved in the model. However, when calling, the network in the judgment condition is not selected and load_state_Dict is used will report an error. Some operators cannot find the name. For example:
if backbone == "mobilenet":
self.backbone = mobilenet()
flat_shape = 1024
elif backbone == "inception_resnetv1":
self.backbone = inception_resnet()
else:
raise ValueError('Unsupported backbone - `{}`, Use mobilenet, inception_resnetv1.'.format(backbone))
self.avg = nn.AdaptiveAvgPool2d((1,1))
self.Bottleneck = nn.Linear(flat_shape, embedding_size,bias=False)
self.last_bn = nn.BatchNorm1d(embedding_size, eps=0.001, momentum=0.1, affine=True)
if mode == "train": # Judgment condition, test without loading full connection
self.classifier = nn.Linear(embedding_size, num_classes)The strict = false option can be added to avoid operators not called in the network:
model2.load_state_dict(state_dict2, strict=False)Description: I installed torch vision 0 eight
git clone -b v0.8.1 https://github.com/pytorch/vision.git vision-0.8.1
Installation:
cd vision-0.8.1
sudo /home/nvidia/mambaforge/envs/ultra-fast-lane/bin/python3.6 setup.py install
Note: be sure to make the path and sudo
Error: illegal instruction
Solution: reduce the numpy version. I use numpy = 1.19.3. Success
Install visdom
Switch to the environment corresponding to CONDA and use CONDA install visdom. An error is reported and the installation cannot be performed. After query, it is found that the installation can be successful using pip. For some reason, the command is as follows:
pip install visdomRun visdom
If you want to use visdom in Python code, you must first start the visdom service in the CONDA environment where visdom is installed:
python -m visdom.serverAfter the service is started, the following prompt will be given:
39: DeprecationWarning: zmq.eventloop.ioloop is deprecated in pyzmq 17. pyzmq now works with default tornado and asyncio eventloops.
ioloop.install() # Needs to happen before any tornado imports!
Checking for scripts.
Downloading scripts, this may take a little while
It's Alive!
INFO:root:Application Started
You can navigate to http://localhost:8097
Then you can open it in the browser http://localhost:8097 Address and access visual content
If you do not run the above command, the following error will be reported:
Traceback (most recent call last):
File "D:\program\conda\envs\python36_gan\lib\site-packages\visdom\__init__.py", line 711, in _send
data=json.dumps(msg),
File "D:\program\conda\envs\python36_gan\lib\site-packages\visdom\__init__.py", line 677, in _handle_post
r = self.session.post(url, data=data)
File "D:\program\conda\envs\python36_gan\lib\site-packages\requests\sessions.py", line 581, in post
return self.request('POST', url, data=data, json=json, **kwargs)
File "D:\program\conda\envs\python36_gan\lib\site-packages\requests\sessions.py", line 533, in request
resp = self.send(prep, **send_kwargs)
File "D:\program\conda\envs\python36_gan\lib\site-packages\requests\sessions.py", line 646, in send
r = adapter.send(request, **kwargs)
File "D:\program\conda\envs\python36_gan\lib\site-packages\requests\adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='localhost', port=8097): Max retries exceeded with url: /env/test1 (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x0000025
321093898>: Failed to establish a new connection: [WinError 10061] Unable to connect because the target computer actively refused.',))
[WinError 10061] Unable to connect because the target computer actively refused.
Exception in user code:
------------------------------------------------------------
Traceback (most recent call last):
File "D:\program\conda\envs\python36_gan\lib\site-packages\urllib3\connection.py", line 157, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "D:\program\conda\envs\python36_gan\lib\site-packages\urllib3\util\connection.py", line 84, in create_connection
raise err
File "D:\program\conda\envs\python36_gan\lib\site-packages\urllib3\util\connection.py", line 74, in create_connection
sock.connect(sa)
ConnectionRefusedError: [WinError 10061] Unable to connect because the target computer actively refused.
During handling of the above exception, another exception occurred:
An error is reported when testing pytorch multi card:
store = tcpstore (master_addr, master_port, world_size, start_daemon, timeout)
runtimeerror: address already in use
After investigation, there is another task running with DDP.
Solution:
manually specify an idle port
python -m torch.distributed.launch --master_port 145622
View port occupancy:
terminal input
netstat - nultp