fastai / book.fast.ai

Information for readers of the fastai book

The fastai book

How to get started with the fastai book.

This information is for readers of the Early Access version of Deep Learning for Coders with fastai and PyTorch and of the fastai draft notebooks.

Note that these require you to use fastai v2, which is currently in pre-release. During pre-release, this module is called fastai. The draft notebooks contain the correct imports for fastai, but the PDF book does not - it uses fastai. Therefore, you should change fastai to fastai in all import statements.

Install

Clone the draft notebooks repo, and then from that directory:

pip install -r requirements.txt

It is best to first install fastai v1 to ensure you have all the correct dependencies. See the docs for details.

How to use

To get started, run Jupyter Notebook (or use one of the online Jupyter platforms listed at https://course.fast.ai) and click on the app_jupyter.ipynb notebook.

We'll be adding more information to this site as the official book release in July 2020 gets closer.

book.fast.ai's Issues

Keep-Alive-Actions

Keep-Alive-Actions

getting error in 01 _intro.ipynb on running the first cell.

Below is the error:

---

RuntimeError Traceback (most recent call last)
in
1 #hide
----> 2 from utils import *

/home/jovyan/fastbook/utils.py in
1 # Numpy and pandas by default assume a narrow screen - this fixes that
----> 2 from fastai2.vision.all import *
3 from nbdev.showdoc import *
4 from ipywidgets import widgets
5 from pandas.api.types import CategoricalDtype

/usr/local/lib/python3.6/site-packages/fastai2/vision/all.py in
1 from ..basics import *
2 from ..callback.all import *
----> 3 from .augment import *
4 from .core import *
5 from .data import *

/usr/local/lib/python3.6/site-packages/fastai2/vision/augment.py in
89
90 # Cell
---> 91 from torchvision.transforms.functional import pad as tvpad
92
93 # Cell

/usr/local/lib/python3.6/site-packages/torchvision/init.py in
1 import warnings
2
----> 3 from torchvision import models
4 from torchvision import datasets
5 from torchvision import ops

/usr/local/lib/python3.6/site-packages/torchvision/models/init.py in
10 from .shufflenetv2 import *
11 from . import segmentation
---> 12 from . import detection
13 from . import video
14 from . import quantization

/usr/local/lib/python3.6/site-packages/torchvision/models/detection/init.py in
----> 1 from .faster_rcnn import *
2 from .mask_rcnn import *
3 from .keypoint_rcnn import *

/usr/local/lib/python3.6/site-packages/torchvision/models/detection/faster_rcnn.py in
11
12 from .generalized_rcnn import GeneralizedRCNN
---> 13 from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork
14 from .roi_heads import RoIHeads
15 from .transform import GeneralizedRCNNTransform

/usr/local/lib/python3.6/site-packages/torchvision/models/detection/rpn.py in
9 from torchvision.ops import boxes as box_ops
10
---> 11 from . import _utils as det_utils
12 from .image_list import ImageList
13

/usr/local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py in
17
18 @torch.jit.script
---> 19 class BalancedPositiveNegativeSampler(object):
20 """
21 This class samples batches, ensuring that they contain a fixed proportion of positives

/usr/local/lib/python3.6/site-packages/torch/jit/init.py in script(obj, optimize, _frames_up, _rcb)
1217 if _rcb is None:
1218 _rcb = _jit_internal.createResolutionCallback(_frames_up + 1)
-> 1219 _compile_and_register_class(obj, _rcb, qualified_name)
1220 return obj
1221 else:

/usr/local/lib/python3.6/site-packages/torch/jit/init.py in _compile_and_register_class(obj, rcb, qualified_name)
1074 def _compile_and_register_class(obj, rcb, qualified_name):
1075 ast = get_jit_class_def(obj, obj.name)
-> 1076 _jit_script_class_compile(qualified_name, ast, rcb)
1077 _add_script_class(obj, qualified_name)
1078

RuntimeError: class 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler' already defined. (register_type at /pytorch/torch/csrc/jit/script/compilation_unit.h:166)
frame #0: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x33 (0x7f707f65b813 in /usr/local/lib/python3.6/site-packages/torch/lib/libc10.so)
frame #1: + 0x5a2539 (0x7f70c78d1539 in /usr/local/lib/python3.6/site-packages/torch/lib/libtorch_python.so)
frame #2: + 0x589e4e (0x7f70c78b8e4e in /usr/local/lib/python3.6/site-packages/torch/lib/libtorch_python.so)
frame #3: + 0x58b123 (0x7f70c78ba123 in /usr/local/lib/python3.6/site-packages/torch/lib/libtorch_python.so)
frame #4: + 0x2110f4 (0x7f70c75400f4 in /usr/local/lib/python3.6/site-packages/torch/lib/libtorch_python.so)

packages with version:

Package Version

---

absl-py 0.8.1
adal 1.2.2
astor 0.8.1
attrs 19.3.0
awscli 1.16.303
azure-cognitiveservices-search-imagesearch 2.0.0
azure-common 1.1.25
backcall 0.1.0
beautifulsoup4 4.8.1
bleach 3.1.0
blis 0.4.1
boto 2.49.0
boto3 1.10.39
botocore 1.13.39
bs4 0.0.1
cachetools 3.1.1
catalogue 0.0.8
certifi 2019.11.28
cffi 1.14.0
chardet 3.0.4
colorama 0.4.1
cryptography 2.8
cycler 0.10.0
cymem 2.0.3
dataclasses 0.7
decorator 4.4.1
defusedxml 0.6.0
docutils 0.15.2
entrypoints 0.3
fastai2 0.0.15
fastcore 0.1.16
fastprogress 0.2.2
fastscript 0.1.4
fasttext 0.9.1
findspark 1.3.0
gast 0.2.2
gensim 3.8.1
google-auth 1.8.2
google-auth-oauthlib 0.4.1
google-pasta 0.1.8
graphviz 0.13.2
grpcio 1.25.0
h5py 2.10.0
idna 2.8
importlib-metadata 1.3.0
ipykernel 5.1.3
ipython 7.10.2
ipython-genutils 0.2.0
ipywidgets 7.5.1
isodate 0.6.0
jedi 0.15.1
Jinja2 2.10.3
jmespath 0.9.4
joblib 0.14.1
json5 0.8.5
jsonschema 3.2.0
jupyter-client 5.3.4
jupyter-core 4.6.1
jupyterlab 1.2.4
jupyterlab-server 1.0.6
Keras 2.3.1
Keras-Applications 1.0.8
Keras-Preprocessing 1.1.0
kiwisolver 1.1.0
Markdown 3.1.1
MarkupSafe 1.1.1
matplotlib 3.1.2
mistune 0.8.4
more-itertools 8.0.2
msrest 0.6.11
msrestazure 0.6.3
murmurhash 1.0.2
nbconvert 5.6.1
nbdev 0.2.16
nbformat 4.4.0
nltk 3.4.5
notebook 6.0.2
numpy 1.17.4
oauthlib 3.1.0
opt-einsum 3.1.0
packaging 20.3
pandas 0.25.3
pandocfilters 1.4.2
parso 0.5.2
pexpect 4.7.0
pickleshare 0.7.5
Pillow 7.0.0
pip 20.0.2
plac 1.1.3
preshed 3.0.2
prometheus-client 0.7.1
prompt-toolkit 3.0.2
protobuf 3.11.1
ptyprocess 0.6.0
pyasn1 0.4.8
pyasn1-modules 0.2.7
pybind11 2.4.3
pycparser 2.20
Pygments 2.5.2
PyJWT 1.7.1
pyparsing 2.4.5
pyrsistent 0.15.6
python-dateutil 2.8.0
pytz 2019.3
PyYAML 5.1.2
pyzmq 18.1.1
regex 2019.12.9
requests 2.22.0
requests-oauthlib 1.3.0
rsa 3.4.2
s3transfer 0.2.1
scikit-learn 0.22
scipy 1.3.3
seaborn 0.9.0
Send2Trash 1.5.0
sentencepiece 0.1.85
setuptools 41.0.1
six 1.13.0
sklearn 0.0
smart-open 1.9.0
soupsieve 1.9.5
spacy 2.2.3
srsly 0.2.0
tensorboard 2.0.2
tensorflow 2.0.0
tensorflow-estimator 2.0.1
termcolor 1.1.0
terminado 0.8.3
testpath 0.4.4
thinc 7.3.1
torch 1.3.1
torchvision 0.5.0
tornado 6.0.3
tqdm 4.40.2
traitlets 4.3.3
urllib3 1.25.7
wasabi 0.4.2
wcwidth 0.1.7
webencodings 0.5.1
Werkzeug 0.16.0
wheel 0.33.4
widgetsnbextension 3.5.1
wrapt 1.11.2
zipp 0.6.0