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from PIL import Image
import requests
import tempfile

def load_gif_url(url):
    with tempfile.NamedTemporaryFile(suffix=".gif") as f:
        f.write(requests.get(url).content)
        f.flush()
        img = Image.open(f.name)

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def get_bw(src):
    return cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)

def show_color(src):
    plt.imshow(cv2.cvtColor(src, cv2.COLOR_BGR2RGB))
    _ = plt.xticks([]), plt.yticks([])

def show_bw(bw):
    plt.imshow(bw, cmap='gray')
    _ = plt.xticks([]), plt.yticks([])

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def get_state_v0(state):
    url = make_url(state)

    IN = load_gif_url(url)

    #Drop the text at the top
    IN = IN[150:]

    #Convert 3 color channels to 1
    IN_bw = get_bw(IN)

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def get_state_v1(state):
    url = make_url(state)

    IN = load_gif_url(url)

    #Drop the text at the top
    IN = IN[150:]

    #Convert 3 color channels to 1
    IN_bw = get_bw(IN)

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[default]
library_dirs = /usr/local/lib
[atlas]
atlas_libs = openblas
library_dirs = /usr/local/lib
[lapack]
lapack_libs = openblas
library_dirs = /usr/local/lib
[openblas]
libraries = openblas

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import os
os.environ['THEANO_FLAGS']="optimizer_including=conv_fft_valid:conv_fft_full"

from pylearn2.config import yaml_parse
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
import numpy as np


train_str = """!obj:pylearn2.train.Train {
    dataset: &train !import '__main__ .train_set',