mmmikael

from datetime import datetime
import math
import time

import tensorflow.python.platform
import tensorflow as tf

FLAGS = tf.app.flags.FLAGS

# TODO: why is batch size 64 going OOM?

mmmikael

from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337)  # for reproducibility

import random
from keras.datasets import mnist
from keras.models import Sequential, Graph
from keras.layers.core import *
from keras.optimizers import SGD, RMSprop

mmmikael

from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337)  # for reproducibility

import random
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import *
from keras.optimizers import SGD, RMSprop

mmmikael

from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337)  # for reproducibility


import theano.tensor as T
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation

mmmikael

from keras.models import Sequential
from keras.layers.core import Permute, Flatten, Layer
from keras.layers.convolutional import Convolution2D
from keras.layers.core import Activation
import theano
import theano.tensor as T
import datetime
import numpy as np

assert theano.config.optimizer_excluding == 'cudnn', \

mmmikael

Function profiling
==================
  Message: build/bdist.linux-x86_64/egg/keras/models.py:399
  Time in 1 calls to Function.__call__: 1.027354e+01s
  Time in Function.fn.__call__: 1.026697e+01s (99.936%)
  Time in thunks: 1.017123e+01s (99.004%)
  Total compile time: 1.421726e+00s
    Number of Apply nodes: 140
    Theano Optimizer time: 1.223497e+00s
       Theano validate time: 6.331444e-02s

mmmikael

from keras.models import Sequential
from keras.layers.core import Permute
from keras.layers.convolutional import Convolution2D
from keras.layers.core import Activation
import theano
import theano.tensor as T
import datetime
import numpy as np

now = datetime.datetime.now

mmmikael

from __future__ import absolute_import
from __future__ import print_function
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.utils import np_utils
from scipy.special import expit
import numpy as np
np.set_printoptions(suppress=True)

mmmikael

require 'cudnn'
require 'fbcunn'

local timer = torch.Timer()

local tensorsAreProbablySimilar = function(l, r, epsilon)
    epsilon = epsilon or 0.00001
    return math.abs((l:norm() - r:norm()) / (l:norm() + r:norm())) < epsilon
end

mmmikael

local function rgbToYuv(rgbTensor)
  local r,g,b = rgbTensor[1],rgbTensor[2],rgbTensor[3]
  local yuvTensor = rgbTensor:clone()
  yuvTensor[1] = torch.mul(r, 0.299) + torch.mul(g, 0.587) + torch.mul(b, 0.114)
  yuvTensor[2] = torch.mul(b - yuvTensor[1], 0.492)
  yuvTensor[3] = torch.mul(r - yuvTensor[1], 0.877)
  return yuvTensor
end

local function yuvToRgb(yuvTensor)