def get_epoch_iterator(self, as_dict=False):
return DataIterator(self, self.iteration_scheme.get_request_iterator()
if self.iteration_scheme else None,
as_dict=as_dict)
def load(self):
self.iterator = DataIterator(None)
import csv
import os
from fuel.iterator import DataIterator
from fuel.schemes import SequentialExampleScheme
from fuel.streams import DataStream
from data.hdf5 import TaxiDataset
import data
dest_outfile = open(os.path.join(data.path, 'test_answer.csv'), 'w')
dest_outcsv = csv.writer(dest_outfile)
dest_outcsv.writerow(["TRIP_ID", "LATITUDE", "LONGITUDE"])
dataset = TaxiDataset('test',
'tvt.hdf5',
sources=('trip_id', 'longitude', 'latitude',
'destination_longitude',
'destination_latitude'))
it = DataIterator(DataStream(dataset),
iter(xrange(dataset.num_examples)),
as_dict=True)
for v in it:
# print v
dest_outcsv.writerow(
[v['trip_id'], v['destination_latitude'], v['destination_longitude']])
dest_outfile.close()
def taxi_it(which_set, filename='data.hdf5', sub=None, as_dict=True):
dataset = TaxiDataset(which_set, filename)
if sub is None:
sub = xrange(dataset.num_examples)
return DataIterator(DataStream(dataset), iter(sub), as_dict)
def test_it():
return DataIterator(DataStream(valid_data))
def train_it():
return DataIterator(DataStream(train_data))