ferrine

import math
from functools import wraps

from theano import tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams

from lasagne import init
from lasagne.random import get_rng

__all__ = ['Accumulator', 'NormalApproximation', 'NormalApproximationScMix', 'bbpwrap']

ferrine

Coal, peat and oil shale-Production (ktoe)
Coal, peat and oil shale-Imports (ktoe)
Coal, peat and oil shale-Exports (ktoe)
Coal, peat and oil shale-Total primary energy supply (ktoe)
Coal, peat and oil shale-Electricity plants (ktoe)
Coal, peat and oil shale-CHP plants (ktoe)
Coal, peat and oil shale-Heat plants (ktoe)
Coal, peat and oil shale-Oil refineries, transformation (ktoe)
Coal, peat and oil shale-Total final consumption (ktoe)
Coal, peat and oil shale-Industry (ktoe)

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xkb_keymap {
xkb_keycodes "(unnamed)" {
    minimum = 8;
    maximum = 255;
     <ESC> = 9;
    <AE01> = 10;
    <AE02> = 11;
    <AE03> = 12;
    <AE04> = 13;
    <AE05> = 14;

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\newif\ifIncludeAuthorNotes
% Comment the below line to remove notes from text
\IncludeAuthorNotestrue

\DeclareRobustCommand{\note}[1]{
\ifIncludeAuthorNotes
	% the below line skips are intentional and force comment to be on a separate line

	\textcolor{gray}{/* #1 */}

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curl -fsSL get.docker.com | sh \
  && sudo curl -L https://github.com/docker/compose/releases/download/1.20.1/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose \
  && sudo chmod +x /usr/local/bin/docker-compose

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git secret hide && git add $(git secret list | awk -v ext=${SECRETS_EXTENSION:-secret} '{print $1"."ext}') 

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def random_subimages_idx(n, d1, d2, h, w):
    hs = np.random.randint(d1-h, size=n)
    ws = np.random.randint(d2-w, size=n)
    grid = np.meshgrid(np.arange(h), np.arange(w), indexing='ij')
    i = np.tile(np.arange(n)[:, None, None], (h, w))
    xs = grid[0]+hs[:, None, None]
    ys = grid[1]+ws[:, None, None]
    return i, xs, ys

def random_subimages(images, h, w):

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def sample_swap(shape):
    b, c, h, w = shape
    left = np.arange(0, w//2)
    right = np.arange(w//2, w)
    flip = np.random.uniform(size=(b, 1)) > .5
    b = np.arange(b)[:, None, None, None]
    c = np.arange(c)[None, :, None, None]
    h = np.arange(h)[None, None, :, None]
    w = np.concatenate([left+flip*(w//2), right-flip*(w//2)], -1)
    w = w[:, None, None, :]

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