radekosmulski

# from the root of fastcore:

python -c "from nbdev.cli import notebook2html; notebook2html()"

gem install jekyll bundler # need to have Ruby installed

cd docs

bundle install

radekosmulski

from fastai.vision import *
from fastai.script import *
from torch import nn
from fastai.metrics import top_k_accuracy

path = untar_data(URLs.CIFAR)
data = ImageDataBunch.from_folder(path, valid='test')

class block(nn.Module):
    def __init__(self, n_in, n_out, two_d=True):

radekosmulski

from fastai.vision import *
from fastai.script import *
from torch import nn
from fastai.metrics import top_k_accuracy

path = untar_data(URLs.CIFAR)
data = ImageDataBunch.from_folder(path, valid='test')

class block(nn.Module):
    def __init__(self, n_in, n_out, two_d=True):

radekosmulski

import fire
import fastai
from fastai.vision import *
from torch import nn
from fastai.metrics import top_k_accuracy

path = untar_data(URLs.CIFAR)
data = ImageDataBunch.from_folder(path, valid='test')

class block(nn.Module):

radekosmulski

class ConcatDataset(Dataset):
    """Concatenates a dataset and an iterable of appropriate size."""
    def __init__(self, ds, y2):
        assert(len(ds)==len(y2))
        self.ds,self.y2 = ds,y2
    def __len__(self): return len(self.ds)
    def __getitem__(self, i):
        x,y = self.ds[i]
        return (x, (self.y2[i],y))
    def denorm(self, im): return self.ds.denorm(im)