I noticed extremely slow run times on my local machine (3+minutes) versus if I run the same notebook on Colab (7sec). This is running the example tabular.ipynb model (https://github.com/fastai/fastai/blob/master/examples/tabular.ipynb).
I exported the code to a script and profiled with cProfile, and it appears something weird is going on with Pickler as it accounts for over 80% of the total run time, and the total runtime is mostly from the learn.fit() method:
ncalls tottime percall cumtime percall filename:lineno(function)
32 176.021 5.501 176.036 5.501 {method 'dump' of '_pickle.Pickler' objects}
131 13.982 0.107 13.983 0.107 {built-in method _imp.create_dynamic}
5360 5.150 0.001 5.150 0.001 {built-in method nt.stat}
505 2.435 0.005 2.435 0.005 {method 'run_backward' of 'torch._C._EngineBase' objects}
1555 2.264 0.001 2.715 0.002 {method 'to' of 'torch._C._TensorBase' objects}
1039 1.941 0.002 2.091 0.002 <frozen importlib._bootstrap_external>:830(get_data)
73 1.736 0.024 1.736 0.024 {built-in method _winapi.WaitForSingleObject}
28792 1.552 0.000 1.552 0.000 {method 'mul_' of 'torch._C._TensorBase' objects}
1527 1.182 0.001 1.182 0.001 {built-in method batch_norm}
19197 0.954 0.000 0.954 0.000 {method 'add_' of 'torch._C._TensorBase' objects}
Has anyone else experienced similarly slow training times due to the pickler?
Here is my environment (win 10 with quadro m1000m gpu):
beautifulsoup4==4.7.1
Bottleneck==1.2.1
certifi==2019.3.9
chardet==3.0.4
cycler==0.10.0
cymem==2.0.2
cytoolz==0.9.0.1
dataclasses==0.6
dill==0.2.9
fastai==1.0.48
fastprogress==0.1.20
idna==2.8
kiwisolver==1.0.1
matplotlib==3.0.3
msgpack==0.5.6
msgpack-numpy==0.4.3.2
murmurhash==1.0.2
numexpr==2.6.9
numpy==1.16.2
nvidia-ml-py3==7.352.0
packaging==19.0
pandas==0.24.1
Pillow==5.4.1
plac==0.9.6
preshed==2.0.1
pyparsing==2.3.1
python-dateutil==2.8.0
pytz==2018.9
PyYAML==5.1
regex==2018.1.10
requests==2.21.0
scipy==1.2.1
six==1.12.0
soupsieve==1.8
spacy==2.0.18
thinc==6.12.1
toolz==0.9.0
torch==1.0.1
torchvision==0.2.2.post3
tqdm==4.31.1
typing==3.6.6
ujson==1.35
urllib3==1.24.1
wincertstore==0.2
wrapt==1.10.11