From ab1076e00d6a92120e46d4a0085911b4425a0d60 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Tue, 5 May 2015 11:36:59 -0400 Subject: Add date/time transformer and new model that uses it --- config/simple_mlp_2_cs.py | 4 -- config/simple_mlp_2_noembed.py | 4 -- config/simple_mlp_tgtcls_0_cs.py | 4 -- config/simple_mlp_tgtcls_1_cs.py | 4 -- config/simple_mlp_tgtcls_1_cswdt.py | 28 ++++++++ train.py | 18 +++-- transformers.py | 127 ++++++++++++++++-------------------- 7 files changed, 95 insertions(+), 94 deletions(-) create mode 100644 config/simple_mlp_tgtcls_1_cswdt.py diff --git a/config/simple_mlp_2_cs.py b/config/simple_mlp_2_cs.py index 692d325..fa2f4c1 100644 --- a/config/simple_mlp_2_cs.py +++ b/config/simple_mlp_2_cs.py @@ -2,10 +2,6 @@ import model.simple_mlp as model import data -n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday -n_dom = 31 -n_hour = 24 - n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory n_end_pts = 5 diff --git a/config/simple_mlp_2_noembed.py b/config/simple_mlp_2_noembed.py index bc300e7..2f45f63 100644 --- a/config/simple_mlp_2_noembed.py +++ b/config/simple_mlp_2_noembed.py @@ -2,10 +2,6 @@ import model.simple_mlp as model import data -n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday -n_dom = 31 -n_hour = 24 - n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory n_end_pts = 5 diff --git a/config/simple_mlp_tgtcls_0_cs.py b/config/simple_mlp_tgtcls_0_cs.py index b174517..96faca0 100644 --- a/config/simple_mlp_tgtcls_0_cs.py +++ b/config/simple_mlp_tgtcls_0_cs.py @@ -4,10 +4,6 @@ import data import model.simple_mlp_tgtcls as model -n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday -n_dom = 31 -n_hour = 24 - n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory n_end_pts = 5 diff --git a/config/simple_mlp_tgtcls_1_cs.py b/config/simple_mlp_tgtcls_1_cs.py index 6bf82e1..293a0ab 100644 --- a/config/simple_mlp_tgtcls_1_cs.py +++ b/config/simple_mlp_tgtcls_1_cs.py @@ -4,10 +4,6 @@ import data import model.simple_mlp_tgtcls as model -n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday -n_dom = 31 -n_hour = 24 - n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory n_end_pts = 5 diff --git a/config/simple_mlp_tgtcls_1_cswdt.py b/config/simple_mlp_tgtcls_1_cswdt.py new file mode 100644 index 0000000..9261635 --- /dev/null +++ b/config/simple_mlp_tgtcls_1_cswdt.py @@ -0,0 +1,28 @@ +import cPickle + +import data + +import model.simple_mlp_tgtcls as model + +n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory +n_end_pts = 5 + +n_valid = 1000 + +with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f) + +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10), + ('week_of_year', 53, 10), + ('day_of_week', 7, 10), + ('qhour_of_day', 24 * 4, 10) +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) +dim_hidden = [500] +dim_output = tgtcls.shape[0] + +learning_rate = 0.0001 +momentum = 0.99 +batch_size = 32 diff --git a/train.py b/train.py index 238803a..2c9522e 100644 --- a/train.py +++ b/train.py @@ -49,11 +49,13 @@ def setup_train_stream(req_vars): subset=slice(0, data.dataset_size), load_in_memory=True) train = DataStream(train, iteration_scheme=SequentialExampleScheme(data.dataset_size - config.n_valid)) - train = transformers.filter_out_trips(data.valid_trips, train) + + train = transformers.TaxiExcludeTrips(data.valid_trips, train) train = transformers.TaxiGenerateSplits(train, max_splits=100) - train = transformers.add_first_k(config.n_begin_end_pts, train) - train = transformers.add_last_k(config.n_begin_end_pts, train) + train = transformers.TaxiAddDateTime(train) + train = transformers.TaxiAddFirstK(config.n_begin_end_pts, train) + train = transformers.TaxiAddLastK(config.n_begin_end_pts, train) train = transformers.Select(train, tuple(req_vars)) train_stream = Batch(train, iteration_scheme=ConstantScheme(config.batch_size)) @@ -63,8 +65,9 @@ def setup_train_stream(req_vars): def setup_valid_stream(req_vars): valid = DataStream(data.valid_data) - valid = transformers.add_first_k(config.n_begin_end_pts, valid) - valid = transformers.add_last_k(config.n_begin_end_pts, valid) + valid = transformers.TaxiAddDateTime(valid) + valid = transformers.TaxiAddFirstK(config.n_begin_end_pts, valid) + valid = transformers.TaxiAddLastK(config.n_begin_end_pts, valid) valid = transformers.Select(valid, tuple(req_vars)) valid_stream = Batch(valid, iteration_scheme=ConstantScheme(1000)) @@ -74,8 +77,9 @@ def setup_valid_stream(req_vars): def setup_test_stream(req_vars): test = DataStream(data.test_data) - test = transformers.add_first_k(config.n_begin_end_pts, test) - test = transformers.add_last_k(config.n_begin_end_pts, test) + test = transformers.TaxiAddDateTime(test) + test = transformers.TaxiAddFirstK(config.n_begin_end_pts, test) + test = transformers.TaxiAddLastK(config.n_begin_end_pts, test) test = transformers.Select(test, tuple(req_vars)) test_stream = Batch(test, iteration_scheme=ConstantScheme(1000)) diff --git a/transformers.py b/transformers.py index 876cee2..d6ed611 100644 --- a/transformers.py +++ b/transformers.py @@ -4,6 +4,8 @@ import theano import random import data +import datetime + def at_least_k(k, v, pad_at_begin, is_longitude): if len(v) == 0: v = numpy.array([data.porto_center[1 if is_longitude else 0]], dtype=theano.config.floatX) @@ -63,78 +65,61 @@ class TaxiGenerateSplits(Transformer): return tuple(r + [dlat, dlon]) - -class first_k(object): - def __init__(self, k, id_latitude, id_longitude): - self.k = k - self.id_latitude = id_latitude - self.id_longitude = id_longitude - def __call__(self, data): - return (numpy.array(at_least_k(self.k, data[self.id_latitude], False, False)[:self.k], - dtype=theano.config.floatX), - numpy.array(at_least_k(self.k, data[self.id_longitude], False, True)[:self.k], - dtype=theano.config.floatX)) -def add_first_k(k, stream): - id_latitude = stream.sources.index('latitude') - id_longitude = stream.sources.index('longitude') - return Mapping(stream, first_k(k, id_latitude, id_longitude), ('first_k_latitude', 'first_k_longitude')) - -class random_k(object): - def __init__(self, k, id_latitude, id_longitude): +class TaxiAddFirstK(Transformer): + def __init__(self, k, stream): + super(TaxiAddFirstK, self).__init__(stream) + self.sources = stream.sources + ('first_k_latitude', 'first_k_longitude') + self.id_latitude = stream.sources.index('latitude') + self.id_longitude = stream.sources.index('longitude') self.k = k - self.id_latitude = id_latitude - self.id_longitude = id_longitude - def __call__(self, x): - lat = at_least_k(self.k, x[self.id_latitude], True, False) - lon = at_least_k(self.k, x[self.id_longitude], True, True) - loc = random.randrange(len(lat)-self.k+1) - return (numpy.array(lat[loc:loc+self.k], dtype=theano.config.floatX), - numpy.array(lon[loc:loc+self.k], dtype=theano.config.floatX)) -def add_random_k(k, stream): - id_latitude = stream.sources.index('latitude') - id_longitude = stream.sources.index('longitude') - return Mapping(stream, random_k(k, id_latitude, id_longitude), ('last_k_latitude', 'last_k_longitude')) - -class last_k(object): - def __init__(self, k, id_latitude, id_longitude): + def get_data(self, request=None): + if request is not None: raise ValueError + data = next(self.child_epoch_iterator) + first_k = (numpy.array(at_least_k(self.k, data[self.id_latitude], False, False)[:self.k], + dtype=theano.config.floatX), + numpy.array(at_least_k(self.k, data[self.id_longitude], False, True)[:self.k], + dtype=theano.config.floatX)) + return data + first_k + +class TaxiAddLastK(Transformer): + def __init__(self, k, stream): + super(TaxiAddLastK, self).__init__(stream) + self.sources = stream.sources + ('last_k_latitude', 'last_k_longitude') + self.id_latitude = stream.sources.index('latitude') + self.id_longitude = stream.sources.index('longitude') self.k = k - self.id_latitude = id_latitude - self.id_longitude = id_longitude - def __call__(self, data): - return (numpy.array(at_least_k(self.k, data[self.id_latitude], True, False)[-self.k:], - dtype=theano.config.floatX), - numpy.array(at_least_k(self.k, data[self.id_longitude], True, True)[-self.k:], - dtype=theano.config.floatX)) -def add_last_k(k, stream): - id_latitude = stream.sources.index('latitude') - id_longitude = stream.sources.index('longitude') - return Mapping(stream, last_k(k, id_latitude, id_longitude), ('last_k_latitude', 'last_k_longitude')) - -class destination(object): - def __init__(self, id_latitude, id_longitude): - self.id_latitude = id_latitude - self.id_longitude = id_longitude - def __call__(self, data): - return (numpy.array(at_least_k(1, data[self.id_latitude], True, False)[-1], + def get_data(self, request=None): + if request is not None: raise ValueError + data = next(self.child_epoch_iterator) + last_k = (numpy.array(at_least_k(self.k, data[self.id_latitude], True, False)[-self.k:], dtype=theano.config.floatX), - numpy.array(at_least_k(1, data[self.id_longitude], True, True)[-1], - dtype=theano.config.floatX)) -def add_destination(stream): - id_latitude = stream.sources.index('latitude') - id_longitude = stream.sources.index('longitude') - return Mapping(stream, destination(id_latitude, id_longitude), ('destination_latitude', 'destination_longitude')) - - -class trip_filter(object): - def __init__(self, id_trip_id, exclude): - self.id_trip_id = id_trip_id - self.exclude = exclude - def __call__(self, data): - if data[self.id_trip_id] in self.exclude: - return False - else: - return True -def filter_out_trips(exclude_trips, stream): - id_trip_id = stream.sources.index('trip_id') - return Filter(stream, trip_filter(id_trip_id, exclude_trips)) + numpy.array(at_least_k(self.k, data[self.id_longitude], True, True)[-self.k:], + dtype=theano.config.floatX)) + return data + last_k + +class TaxiAddDateTime(Transformer): + def __init__(self, stream): + super(TaxiAddDateTime, self).__init__(stream) + self.sources = stream.sources + ('week_of_year', 'day_of_week', 'qhour_of_day') + self.id_timestamp = stream.sources.index('timestamp') + def get_data(self, request=None): + if request is not None: raise ValueError + data = next(self.child_epoch_iterator) + ts = data[self.id_timestamp] + date = datetime.datetime.utcfromtimestamp(ts) + info = (date.isocalendar()[1] - 1, date.weekday(), date.hour * 4 + date.minute / 15) + return data + info + +class TaxiExcludeTrips(Transformer): + def __init__(self, exclude_list, stream): + super(TaxiExcludeTrips, self).__init__(stream) + self.id_trip_id = stream.sources.index('trip_id') + self.exclude = {v: True for v in exclude_list} + def get_data(self, request=None): + if request is not None: raise ValueError + while True: + data = next(self.child_epoch_iterator) + if not data[self.id_trip_id] in self.exclude: break + return data + -- cgit v1.2.3