arthurmensch

SVG + Latex to PDF/PNG converter

Usage: make will yield pdf for all SVG file in the directory. make png will rasterize them to png

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import os

import nibabel
import numpy as np
import sklearn.externals.joblib as joblib
from nibabel import Nifti1Image as NibabelNifti1Image
from nibabel import load as nibabel_load
from sklearn.externals.joblib.func_inspect import filter_args
from sklearn.externals.joblib.hashing import NumpyHasher, Hasher

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arthurmensch

import numpy as np
from lightning.classification import SAGAClassifier
from scipy import sparse

from sklearn.datasets import load_iris, make_classification
from sklearn.linear_model.logistic import (
    LogisticRegression,
)

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"""
Copyright (c) 2017 Arthur Mensch

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

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"""
Custom twice differentiable functions in Pytorch.

Author: Arthur Mensch
"""


import torch

import torch.nn as nn

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import threading as thr
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import as_completed as thr_as_completed
from queue import Queue as ThrQueue
from time import sleep

import numpy as np
import tornado
from distributed import Client, Queue, as_completed, Pub, Sub, get_client, \
    get_worker

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import torch
import torch.nn as nn
import torch.nn.functional as F


def duality_gap(f, fn):
    diff = f - fn
    return (torch.max(diff, dim=1)[0] - torch.min(diff, dim=1)[
        0]).mean().item()

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import json
import math
import time

import numpy as np
import torch

import matplotlib.pyplot as plt
import seaborn as sns
import os

arthurmensch

import json
import math
import time

import numpy as np
import torch

import matplotlib.pyplot as plt
import seaborn as sns
import os