@staticmethod

def get_permutation(input_size):

# Generate binary dataset of all possible permutations for size input_size

import itertools

print "Generating dataset of all possible permutations for size ({0}) input_size ...".format(input_size),

dataset = []

for i in itertools.product("01", repeat=input_size):

dataset.append(i)

fake_dataset = {'input_size': input_size}

fake_dataset['valid'] = {'data': theano.shared(value=np.asarray(dataset, dtype=theano.config.floatX), borrow=True)}

fake_dataset['train'] = {'data': theano.shared(value=np.asarray(dataset[:int(len(dataset) * 0.10)], dtype=theano.config.floatX), borrow=True)}

fake_dataset['test'] = {'data': theano.shared(value=np.asarray(dataset, dtype=theano.config.floatX), borrow=True)}

print "Done. {0} items generated.".format(len(dataset))

return fake_dataset

@staticmethod

def get_fake(in_size=4, dataset_size=1):

fake_dataset = {'input_size': in_size}

fake_dataset['valid'] = {'data': theano.shared(value=np.zeros((dataset_size, in_size), dtype=theano.config.floatX), borrow=True), 'length': dataset_size}

fake_dataset['train'] = {'data': theano.shared(value=np.zeros((dataset_size, in_size), dtype=theano.config.floatX), borrow=True), 'length': dataset_size}

fake_dataset['test'] = {'data': theano.shared(value=np.zeros((dataset_size, in_size), dtype=theano.config.floatX), borrow=True), 'length': dataset_size}

return fake_dataset

@staticmethod

def _clean(dataset):

data = []

for i in dataset:

data.append(i)

return np.asarray(data, dtype=theano.config.floatX)

@staticmethod

def get(dataset_name):

datasets = ['adult',

'binarized_mnist',

'connect4',

'dna',

'mushrooms',

'nips',

'ocr_letters',

'rcv1',

'web',

'simple_tree'

]

if dataset_name not in datasets:

raise ValueError('Dataset unknown: ' + dataset_name)

print '### Loading dataset [{0}] ...'.format(dataset_name),

start_time = t.time()

raw_dataset = np.load(os.path.join("datasets", dataset_name) + ".npz")

full_dataset = {'input_size': raw_dataset['inputsize']}

trainset_theano = theano.shared(value=raw_dataset['train_data'], borrow=True)

validset_theano = theano.shared(value=raw_dataset['valid_data'], borrow=True)

testset_theano = theano.shared(value=raw_dataset['test_data'], borrow=True)

full_dataset['train'] = {'data': trainset_theano, 'length': raw_dataset['train_length']}

full_dataset['valid'] = {'data': validset_theano, 'length': raw_dataset['valid_length']}

full_dataset['test'] = {'data': testset_theano, 'length': raw_dataset['test_length']}

print "(Dim:{0} Train:{1} Valid:{2} Test:{3})".format(full_dataset['input_size'], full_dataset['train']['length'], full_dataset['valid']['length'], full_dataset['test']['length']),

print get_done_text(start_time), "###"