You’re Welcome.
mrfabulous1 
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Hi goldenflatulence hope all is well!
1. Have you tried a different browser?
2. What errors do you have in the render console?
3. On which platform did you train your model?
With the above information the problem should be easier to solve.
Cheers mrfabulous1
- I just tried a different browser, same result.
- I haven’t noticed any errors since I assumed that deployment meant no errors.
- On GCP.
Hi goldenflatulence hope you are well.
As you say you haven’t noticed any errors, it makes things a little bit more difficult to find the fault.
Please check the following.
-
can you check the versions of libraries used on GCP and the ones used on render? See posts on using the command “!pip list” in this. thread to do this. If any are different change your library version numbers in requirements.txt file in the render app.
-
Can you confirm that your model file (.pkl) is being accessed correctly?
-
Can you check the network in the developer tools of the browser you may find some information when you try to analyze an image?
-
How large is your model (.pkl) file?
-
Does the same thing happen with very small images?
Hope these suggestions help!
Cheers mrfabulous1
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So, I followed you directions and also read a lot of this thread and its finally working.
Thank you so much.
Hi, guys!
I have next problem: when deploy teddybears - everything is fine. As soon as I change export.pkl file and labels - get net error in log console
Any ideas how to deal with that problem?
Hi volcanoflash hope you are well!
- I have next problem: when deploy teddybears - everything is fine.
Do you mean you have deployed the teddy repository and it works fine on Render?
- As soon as I change export.pkl file and labels
Do you mean that you have trained a new model and created a export.pkl file on a different platform like your desktop or a service provider like Google Colab?
and you have put your export.pkl on google shared drive.
- get net error in log console
You get get the error when you have done 1. and 2. and try to deploy the app.
If you have done exactly what I describe in steps 1,2 and 3 a good start would be to see posts in this thread which contain ‘pip list’ and do as they say.
Cheers mrfabulous1
if your answer two both tho
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Does anyone know what the URI is for torchvision 0.2.1? It’s the version I used to export my pkl on Paperspace and I can’t seem to find it on the Pytorch website. I’m having the same issues with the teddy bear classifier repo and version numbers not matching up
Hi korlandril hope all is well!
I haven’t found a specific URL for torchvision 0.2.1
However here are some things you can try,
-
pip install torchvision==0.2.1
or you can add the following line
-
RUN pip install torchvision==0.2.1
After the requirements line in the file called “Dockerfile” located in the repository.
- As there are lots of dependencies, in some cases where my model was trained months previous, I have just had to retrain it on the current versions of fastai and update all the associated libraries etc in my requirements.txt. In this case this is usally the version installed on Google Colab.
One app uses the following requirements.txt however sometimes minor changes are made in one library, which affects another library and its not always documented, so I have quite a few versions of requirements.txt.
numpy==1.16.1
torchvision==0.2.1
https://download.pytorch.org/whl/cpu/torch-1.0.1.post2-cp37-cp37m-linux_x86_64.whl
fastai==1.0.54
starlette==0.12.0
uvicorn==0.4.6
python-multipart==0.0.5
aiofiles==0.4.0
aiohttp==3.5.4
Hope this helps mrfabulous1 `
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Hi, I’m getting the same error message as several people above:
Sep 12 09:04:31 AM ERROR: Exception in ASGI application
Sep 12 09:04:31 AM Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/uvicorn/protocols/http/httptools_impl.py", line 378, in run_asgi
asgi = app(self.scope)
TypeError: __call__() missing 2 required positional arguments: 'receive' and 'send'
Sep 12 09:04:31 AM INFO: ('10.104.25.59', 58920) - "GET /favicon.ico HTTP/1.1" 500
I’ve edited my requirements.txt, but when I run ! pip list, the list does not contain entries for starlette, aiofiles, or aoihttp. I’ve tried leaving those blank, and as a shot in the dark also tried the values in the most recent post above.
Any insight as to whether their absence from my pip list causing this error, or whether it might be something else would be much appreciated!
Hi go_go_gadget hope all is well!
I’ve edited my requirements.txt, but when I run
! pip list, the list does not contain entries for starlette, aiofiles, or aoihttp. I’ve tried leaving those blank, and as a shot in the dark also tried the values in the most recent post above.
What platform did you train your model on?
Any insight as to whether their absence from my pip list causing this error, or whether it might be something else would be much appreciated!
Can you show the !pip list of the platform you trained the model on?
Also the client part of the app is written using the starlette library, without this it is impossible for your app to work.
I believe aiofiles, is required if you want to use FileResponse or StaticFiles .
and aoihttp is an Async http client/server framework (asyncio).
We will need to resolve these issues, then it will either work or we will resolve any other issues if there are any
Cheers mrfabulous
So much for the response, @mrfabulous1! I’m using GCP, and here’s my !pip list:
Package Version
alabaster 0.7.12
anaconda-client 1.7.2
anaconda-project 0.8.3
ansiwrap 0.8.4
arrow 0.14.5
asn1crypto 0.24.0
astroid 2.2.5
astropy 3.2.1
atomicwrites 1.3.0
attrs 19.1.0
Babel 2.7.0
backcall 0.1.0
backports.os 0.1.1
backports.shutil-get-terminal-size 1.0.0
bcolz 1.2.1
beautifulsoup4 4.8.0
binaryornot 0.4.4
bitarray 1.0.1
bkcharts 0.2
bleach 3.1.0
bokeh 1.3.4
boto 2.49.0
Bottleneck 1.2.1
cachetools 3.1.1
certifi 2019.6.16
cffi 1.12.3
chardet 3.0.4
Click 7.0
cloudpickle 1.2.1
clyent 1.2.2
colorama 0.4.1
conda 4.7.11
conda-package-handling 1.3.11
configparser 3.8.1
confuse 1.0.0
contextlib2 0.5.5
cookiecutter 1.6.0
cryptography 2.7
cycler 0.10.0
cymem 2.0.2
Cython 0.29.13
cytoolz 0.9.0.1
dask 2.3.0
dataclasses 0.6
datalab 1.1.5
ddt 1.2.1
decorator 4.4.0
defusedxml 0.6.0
dill 0.2.9
distributed 2.3.0
docker 4.0.2
docutils 0.15.2
entrypoints 0.3
enum34 1.1.6
et-xmlfile 1.0.1
fairing 0.5.3
fastai 1.0.57
fastcache 1.1.0
fastprogress 0.1.21
filelock 3.0.12
Flask 1.1.1
fsspec 0.4.0
future 0.17.1
gcsfs 0.3.0
gevent 1.4.0
gitdb2 2.0.5
GitPython 3.0.1
glob2 0.7
gmpy2 2.0.8
google-api-core 1.14.2
google-api-python-client 1.7.11
google-auth 1.6.3
google-auth-httplib2 0.0.3
google-auth-oauthlib 0.4.0
google-cloud-bigquery 1.18.0
google-cloud-core 1.0.3
google-cloud-dataproc 0.5.0
google-cloud-datastore 1.9.0
google-cloud-language 1.3.0
google-cloud-logging 1.12.1
google-cloud-monitoring 0.31.1
google-cloud-spanner 1.10.0
google-cloud-storage 1.18.0
google-cloud-translate 1.6.0
google-resumable-media 0.3.2
googleapis-common-protos 1.6.0
greenlet 0.4.15
grpc-google-iam-v1 0.12.3
grpcio 1.23.0
h5py 2.9.0
heapdict 1.0.0
html5lib 1.0.1
htmlmin 0.1.12
httplib2 0.13.1
idna 2.8
imageio 2.5.0
imagesize 1.1.0
importlib-metadata 0.19
ipykernel 5.1.2
ipython 7.7.0
ipython-genutils 0.2.0
ipython-sql 0.3.9
ipywidgets 7.5.1
isort 4.3.21
itsdangerous 1.1.0
jdcal 1.4.1
jedi 0.15.1
jeepney 0.4
Jinja2 2.10.1
jinja2-time 0.2.0
joblib 0.13.2
json5 0.8.5
jsonschema 3.0.2
jupyter 1.0.0
jupyter-aihub-deploy-extension 0.1
jupyter-client 5.3.1
jupyter-console 6.0.0
jupyter-contrib-core 0.3.3
jupyter-contrib-nbextensions 0.5.1
jupyter-core 4.5.0
jupyter-highlight-selected-word 0.2.0
jupyter-http-over-ws 0.0.6
jupyter-latex-envs 1.4.6
jupyter-nbextensions-configurator 0.4.1
jupyterlab 1.0.2
jupyterlab-git 0.8.1
jupyterlab-server 1.0.0
keyring 18.0.0
kiwisolver 1.1.0
kubernetes 10.0.1
lazy-object-proxy 1.4.1
libarchive-c 2.8
lief 0.9.0
llvmlite 0.29.0
locket 0.2.0
lxml 4.4.1
Markdown 3.1.1
MarkupSafe 1.1.1
matplotlib 3.1.0
mccabe 0.6.1
missingno 0.4.2
mistune 0.8.4
mkl-fft 1.0.14
mkl-random 1.0.2
mkl-service 2.0.2
mock 3.0.5
more-itertools 7.2.0
mpmath 1.1.0
msgpack 0.6.1
msgpack-numpy 0.4.3.2
multipledispatch 0.6.0
murmurhash 1.0.2
nb-conda 2.2.1
nb-conda-kernels 2.2.2
nbconvert 5.6.0
nbdime 1.1.0
nbformat 4.4.0
nbpresent 3.0.2
networkx 2.3
nltk 3.4.4
nose 1.3.7
notebook 6.0.0
notebook-executor 0.1
numba 0.45.1
numexpr 2.7.0
numpy 1.16.4
numpydoc 0.9.1
oauth2client 4.1.3
oauthlib 3.1.0
olefile 0.46
opencv-python 4.1.0.25
openpyxl 2.6.2
packaging 19.1
pandas 0.25.0
pandas-profiling 2.3.0
pandocfilters 1.4.2
papermill 1.1.0
parso 0.5.1
partd 1.0.0
path.py 12.0.1
pathlib2 2.3.4
patsy 0.5.1
pep8 1.7.1
pexpect 4.7.0
phik 0.9.8
pickleshare 0.7.5
Pillow 6.1.0
Pillow-SIMD 6.0.0.post0
pip 19.1.1
pkginfo 1.5.0.1
plac 0.9.6
plotly 4.1.0
pluggy 0.12.0
ply 3.11
poyo 0.5.0
preshed 2.0.1
prettytable 0.7.2
prometheus-client 0.7.1
prompt-toolkit 2.0.9
protobuf 3.9.1
psutil 5.6.3
ptyprocess 0.6.0
py 1.8.0
pyarrow 0.14.1
pyasn1 0.4.6
pyasn1-modules 0.2.6
pycodestyle 2.5.0
pycosat 0.6.3
pycparser 2.19
pycrypto 2.6.1
pycurl 7.43.0.3
pydot 1.4.1
pyflakes 2.1.1
Pygments 2.4.2
pylint 2.3.1
pyodbc 4.0.27
pyOpenSSL 19.0.0
pyparsing 2.4.2
pyrsistent 0.14.11
PySocks 1.7.0
pytest 5.0.1
pytest-arraydiff 0.3
pytest-astropy 0.5.0
pytest-doctestplus 0.3.0
pytest-openfiles 0.3.2
pytest-pylint 0.14.1
pytest-remotedata 0.3.2
python-dateutil 2.8.0
pytz 2019.2
PyWavelets 1.0.3
PyYAML 5.1.2
pyzmq 18.1.0
QtAwesome 0.5.7
qtconsole 4.5.3
QtPy 1.9.0
regex 2018.1.10
requests 2.22.0
requests-oauthlib 1.2.0
retrying 1.3.3
rope 0.14.0
rsa 4.0
ruamel-yaml 0.15.46
scikit-image 0.15.0
scikit-learn 0.21.2
scipy 1.3.1
seaborn 0.9.0
SecretStorage 3.1.1
Send2Trash 1.5.0
setuptools 41.0.1
simplegeneric 0.8.1
singledispatch 3.4.0.3
six 1.12.0
smmap2 2.0.5
snowballstemmer 1.9.0
sortedcollections 1.1.2
sortedcontainers 2.1.0
soupsieve 1.9.2
spacy 2.0.18
Sphinx 2.1.2
sphinxcontrib-applehelp 1.0.1
sphinxcontrib-devhelp 1.0.1
sphinxcontrib-htmlhelp 1.0.2
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.2
sphinxcontrib-serializinghtml 1.1.3
sphinxcontrib-websupport 1.1.2
spyder 3.3.6
spyder-kernels 0.5.1
SQLAlchemy 1.3.7
sqlparse 0.3.0
statsmodels 0.10.1
sympy 1.4
tables 3.5.2
tblib 1.4.0
tenacity 5.1.1
terminado 0.8.2
testpath 0.4.2
textwrap3 0.9.2
thinc 6.12.1
toolz 0.10.0
torch 1.2.0
torchvision 0.4.0a0+6b959ee
tornado 5.1.1
tqdm 4.34.0
traitlets 4.3.2
typed-ast 1.4.0
typing 3.6.4
ujson 1.35
unicodecsv 0.14.1
uritemplate 3.0.0
urllib3 1.24.2
virtualenv 16.7.3
wcwidth 0.1.7
webencodings 0.5.1
websocket-client 0.56.0
Werkzeug 0.15.5
wheel 0.33.4
whichcraft 0.6.0
widgetsnbextension 3.5.1
wrapt 1.10.11
wurlitzer 1.0.3
xlrd 1.2.0
XlsxWriter 1.1.8
xlwt 1.3.0
zict 1.0.0
zipp 0.5.2
Thanks again!
Hi go_go_gadget hope you are having a jolly day.
In my experience the first thing you must do is make sure your all the libraries listed in your requirements.txt of your repository, are set to the same version as in GCP !pip list.
So your requirements.txt should look similar to the one in post 273 but but have the version numbers of your GCP.
I use google Colab so I have similar issues.
Also If you trained your model months ago it may be worth running it again as the libraries sometimes change but the version number doesn’t.
Let me know the outcome.
If you have done this and its not working let me know the error.
Cheers mrfabulous1
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Certainly, but we don’t have an estimate for when. Which option works best for you? PayPal?
Paypal would be great.
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Yes, please add paypal support asap! thanks!
Hi, JamesT, I have successfully deploy fastai code by following instruction from “Deploying on Google App Engine” , but ast last steps, I get error “502 Bad Gateway” from “nginx”. Do you know why? Thanks first!
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