Oh wow, I had used a RandomSplitter. Thanks will do that 
Oh shoot wait @barnacl that fixed half the problem, sorry 
I was running my course notebook and hit another issue first. Let me get to yours 
How old is your version? 04_Segmentation trains for me and we use ranger rather than adam. I can’t recreate the issue. If possible could you recreate it in google colab and save it as a gist for me to look at? 
Hmm weird, let me check again give me a sec
So this is where i’m cloning from - https://github.com/muellerzr/Practical-Deep-Learning-for-Coders-2.0, just did a new clone to my Drive. The current 04_Segmentation has a config too - config = unet_config(self_attention=True, act_cls=Mish) which i guess has changed?
To make things simple I just used learn = unet_learner(dls, resnet34, metrics=acc_camvid), so i removed ranger and mish.
here is the gist
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Yeah I need to update the notebooks. We got rid of config for cnn and unet so you can just pass them into the learner now
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What does pip show fastai and pip show fastcore give you?
Shoot, should have added that:
Name: fastai
Version: 2.1.7
Summary: fastai simplifies training fast and accurate neural nets using modern best practices
Home-page: https://github.com/fastai/fastai/tree/master/
Author: Jeremy Howard, Sylvain Gugger, and contributors
Author-email: info@fast.ai
License: Apache Software License 2.0
Location: /usr/local/lib/python3.6/dist-packages
Requires: torchvision, pillow, matplotlib, scipy, spacy, torch, pandas, requests, fastcore, scikit-learn, pip, packaging, fastprogress, pyyaml
Required-by:
Name: fastcore
Version: 1.3.9
Summary: Python supercharged for fastai development
Home-page: https://github.com/fastai/fastcore/tree/master/
Author: Jeremy Howard and Sylvain Gugger
Author-email: infos@fast.ai
License: Apache Software License 2.0
Location: /usr/local/lib/python3.6/dist-packages
Requires: packaging, pip
Required-by: fastai
1 Like
Are you not able to reproduce it ? @muellerzr
No, I’m actually not. It runs for me
The only other thing I can think of is what does pip show torch return? I have 1.7.0+cu101
wow i’m confused.
mine is also
Name: torch
Version: 1.7.0+cu101
This is going to be extremely long, but what does pip list give you?
so we are both on colab pro and the only pip install is - !pip install fastai -q --upgrade
Package Version
----------------------------- ---------------
absl-py 0.10.0
alabaster 0.7.12
albumentations 0.1.12
altair 4.1.0
argon2-cffi 20.1.0
asgiref 3.3.1
astor 0.8.1
astropy 4.1
astunparse 1.6.3
async-generator 1.10
atari-py 0.2.6
atomicwrites 1.4.0
attrs 20.3.0
audioread 2.1.9
autograd 1.3
Babel 2.9.0
backcall 0.2.0
beautifulsoup4 4.6.3
bleach 3.2.1
blis 0.4.1
bokeh 2.1.1
Bottleneck 1.3.2
branca 0.4.1
bs4 0.0.1
CacheControl 0.12.6
cachetools 4.1.1
catalogue 1.0.0
certifi 2020.11.8
cffi 1.14.3
chainer 7.4.0
chardet 3.0.4
click 7.1.2
cloudpickle 1.3.0
cmake 3.12.0
cmdstanpy 0.9.5
colorlover 0.3.0
community 1.0.0b1
contextlib2 0.5.5
convertdate 2.3.0
coverage 3.7.1
coveralls 0.5
crcmod 1.7
cufflinks 0.17.3
cupy-cuda101 7.4.0
cvxopt 1.2.5
cvxpy 1.0.31
cycler 0.10.0
cymem 2.0.4
Cython 0.29.21
daft 0.0.4
dask 2.12.0
dataclasses 0.8
datascience 0.10.6
debugpy 1.0.0
decorator 4.4.2
defusedxml 0.6.0
descartes 1.1.0
dill 0.3.3
distributed 1.25.3
Django 3.1.3
dlib 19.18.0
dm-tree 0.1.5
docopt 0.6.2
docutils 0.16
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easydict 1.9
ecos 2.0.7.post1
editdistance 0.5.3
en-core-web-sm 2.2.5
entrypoints 0.3
ephem 3.7.7.1
et-xmlfile 1.0.1
fa2 0.3.5
fancyimpute 0.4.3
fastai 2.1.7
fastcore 1.3.9
fastdtw 0.3.4
fastprogress 1.0.0
fastrlock 0.5
fbprophet 0.7.1
feather-format 0.4.1
filelock 3.0.12
firebase-admin 4.4.0
fix-yahoo-finance 0.0.22
Flask 1.1.2
flatbuffers 1.12
folium 0.8.3
future 0.16.0
gast 0.3.3
GDAL 2.2.2
gdown 3.6.4
gensim 3.6.0
geographiclib 1.50
geopy 1.17.0
gin-config 0.3.0
glob2 0.7
google 2.0.3
google-api-core 1.16.0
google-api-python-client 1.7.12
google-auth 1.17.2
google-auth-httplib2 0.0.4
google-auth-oauthlib 0.4.2
google-cloud-bigquery 1.21.0
google-cloud-bigquery-storage 1.1.0
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google-cloud-datastore 1.8.0
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google-cloud-language 1.2.0
google-cloud-storage 1.18.1
google-cloud-translate 1.5.0
google-colab 1.0.0
google-pasta 0.2.0
google-resumable-media 0.4.1
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googledrivedownloader 0.4
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gspread 3.0.1
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gym 0.17.3
h5py 2.10.0
HeapDict 1.0.1
holidays 0.10.3
holoviews 1.13.5
html5lib 1.0.1
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httplib2shim 0.0.3
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ideep4py 2.0.0.post3
idna 2.10
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imageio 2.4.1
imagesize 1.2.0
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imblearn 0.0
imgaug 0.2.9
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imutils 0.5.3
inflect 2.1.0
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intel-openmp 2020.0.133
intervaltree 2.1.0
ipykernel 4.10.1
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ipython-genutils 0.2.0
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ipywidgets 7.5.1
itsdangerous 1.1.0
jax 0.2.6
jaxlib 0.1.57+cuda101
jdcal 1.4.1
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jieba 0.42.1
Jinja2 2.11.2
joblib 0.17.0
jpeg4py 0.1.4
jsonschema 2.6.0
jupyter 1.0.0
jupyter-client 5.3.5
jupyter-console 5.2.0
jupyter-core 4.7.0
jupyterlab-pygments 0.1.2
kaggle 1.5.9
kapre 0.1.3.1
Keras 2.4.3
Keras-Preprocessing 1.1.2
keras-vis 0.4.1
kiwisolver 1.3.1
knnimpute 0.1.0
korean-lunar-calendar 0.2.1
librosa 0.6.3
lightgbm 2.2.3
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lmdb 0.99
lucid 0.3.8
LunarCalendar 0.0.9
lxml 4.2.6
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missingno 0.4.2
mistune 0.8.4
mizani 0.6.0
mkl 2019.0
mlxtend 0.14.0
more-itertools 8.6.0
moviepy 0.2.3.5
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multitasking 0.0.9
murmurhash 1.0.4
music21 5.5.0
natsort 5.5.0
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nbconvert 5.6.1
nbformat 5.0.8
nest-asyncio 1.4.3
networkx 2.5
nibabel 3.0.2
nltk 3.2.5
notebook 5.3.1
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numexpr 2.7.1
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oauthlib 3.1.0
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opencv-python 4.1.2.30
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opt-einsum 3.3.0
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pandas-gbq 0.13.3
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panel 0.9.7
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pip 19.3.1
pip-tools 4.5.1
plac 1.1.3
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protobuf 3.12.4
psutil 5.4.8
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py 1.9.0
pyarrow 0.14.1
pyasn1 0.4.8
pyasn1-modules 0.2.8
pycocotools 2.0.2
pycparser 2.20
pyct 0.4.8
pydata-google-auth 1.1.0
pydot 1.3.0
pydot-ng 2.0.0
pydotplus 2.0.2
PyDrive 1.3.1
pyemd 0.5.1
pyglet 1.5.0
Pygments 2.6.1
pygobject 3.26.1
pymc3 3.7
PyMeeus 0.3.7
pymongo 3.11.1
pymystem3 0.2.0
PyOpenGL 3.1.5
pyparsing 2.4.7
pyrsistent 0.17.3
pysndfile 1.3.8
PySocks 1.7.1
pystan 2.19.1.1
pytest 3.6.4
python-apt 1.6.5+ubuntu0.3
python-chess 0.23.11
python-dateutil 2.8.1
python-louvain 0.14
python-slugify 4.0.1
python-utils 2.4.0
pytz 2018.9
pyviz-comms 0.7.6
PyWavelets 1.1.1
PyYAML 3.13
pyzmq 20.0.0
qtconsole 4.7.7
QtPy 1.9.0
regex 2019.12.20
requests 2.23.0
requests-oauthlib 1.3.0
resampy 0.2.2
retrying 1.3.3
rpy2 3.2.7
rsa 4.6
scikit-image 0.16.2
scikit-learn 0.22.2.post1
scipy 1.4.1
screen-resolution-extra 0.0.0
scs 2.1.2
seaborn 0.11.0
Send2Trash 1.5.0
setuptools 50.3.2
setuptools-git 1.2
Shapely 1.7.1
simplegeneric 0.8.1
six 1.15.0
sklearn 0.0
sklearn-pandas 1.8.0
slugify 0.0.1
smart-open 3.0.0
snowballstemmer 2.0.0
sortedcontainers 2.3.0
spacy 2.2.4
Sphinx 1.8.5
sphinxcontrib-serializinghtml 1.1.4
sphinxcontrib-websupport 1.2.4
SQLAlchemy 1.3.20
sqlparse 0.4.1
srsly 1.0.4
statsmodels 0.10.2
sympy 1.1.1
tables 3.4.4
tabulate 0.8.7
tblib 1.7.0
tensorboard 2.3.0
tensorboard-plugin-wit 1.7.0
tensorboardcolab 0.0.22
tensorflow 2.3.0
tensorflow-addons 0.8.3
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tensorflow-estimator 2.3.0
tensorflow-gcs-config 2.3.0
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thinc 7.4.0
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toml 0.10.2
toolz 0.11.1
torch 1.7.0+cu101
torchsummary 1.5.1
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torchvision 0.8.1+cu101
tornado 5.1.1
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traitlets 4.3.3
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typeguard 2.7.1
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uritemplate 3.0.1
urllib3 1.24.3
vega-datasets 0.8.0
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wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 1.0.1
wheel 0.35.1
widgetsnbextension 3.5.1
wordcloud 1.5.0
wrapt 1.12.1
xarray 0.15.1
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xkit 0.0.0
xlrd 1.1.0
xlwt 1.3.0
yellowbrick 0.9.1
zict 2.0.0
zipp 3.4.0
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There is quite literally nothing different with our environments… I am very perplexted. I hate saying this but could you leave it alone for an hour, factory reset, and then see if it’s still there??
I guess that is the next thing to try, thanks. Will post here in an hour with updates
Thanks for the help @muellerzr . Will shut down the million colab notebooks 
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@muellerzr hi Zach, so I ran it again, ran it from a different account and had a friend run it too. But it all failed with the same error. Is it possible that you are have a local change that is over-riding or not using the fastcore? Or are you using a editable install?
This is the closest I can find ie downgrade fastai to 2.0.19 with torch 1.6. I’m not sure if it would help but hoping to narrow down the versions where the same code would work for you.
This version was released after
2.1.0, and adds fastcore 1.3 compatibility, whilst maintaining PyTorch 1.6 compatibility. It has no new features or bug fixes.
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@barnacl today I’m going to be adding more tests to fastai to see if we can train, I’ll see if anything breaks
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@msivanes thanks for the suggestion. It works with
pytorch=1.6
fastai=2.0.19
fastcore=1.3.1
On colab i did
pip uninstall torch -y
pip uninstall torch -y
# CUDA 10.1
!pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
pip install fastai==2.0.19
pip install fastcore==1.3.1
6 Likes
