mmmikael’s gists

mmmikael / benchmark_vgg_keras.py

Last active August 10, 2016 18:07

Soumith's tensorflow benchmark with Keras API

	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 / mnist_siamese_graph.py

Created February 6, 2016 20:40

Keras example for siamese training on mnist with graph model

	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 / mnist_siamese.py

Last active January 24, 2021 07:27

Keras example for siamese training on mnist

	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 / mnist_pseudo_siamese.py

Last active February 4, 2016 13:45

mnist pseudo siamese

	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 / fcn_bench_flat.py

Created October 13, 2015 13:24

fcn benchmark with flat outputs

	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 / fcn_bench_profiling.txt

Created October 9, 2015 12:41

fcn keras profiliing

	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 / fcn_bench.py

Created October 8, 2015 09:39

fcn benchmark

	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 / mnist_cnn_all.py

Last active October 28, 2016 19:20

	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 / dp_test.lua

Last active September 29, 2015 20:12

nn.DataParallel test

	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 / rgbyuv.lua

Last active August 29, 2015 14:11

lua torch rgb <=> yuv

	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)

Mikael Rousson mmmikael