In [1]:

    

import gzip
#import pickle
import cPickle
import numpy
import timeit
import theano


    

In [2]:

    

def unpickle(file):
    import cPickle
    with open(file, 'rb') as fo:
        dict = cPickle.load(fo)
    return dict


    

In [ ]:

    

#python 3
#def unpickle(file):
###    import pickle
#    with open(file, 'rb') as fo:
#        dict = pickle.load(fo, encoding='bytes')
#    return dict


    

In [8]:

    

DATA_PATH = "/Users/myt007/git/data/cifar-10-batches-py/"
DATA_PATH = "../../data/cifar-10-batches-py/"
#DATA_PATH = ""

data = unpickle(DATA_PATH + "data_batch_1")


    

In [9]:

    

data


    

    
Out[9]:





{'batch_label': 'training batch 1 of 5',
 'data': array([[ 59,  43,  50, ..., 140,  84,  72],
        [154, 126, 105, ..., 139, 142, 144],
        [255, 253, 253, ...,  83,  83,  84],
        ..., 
        [ 71,  60,  74, ...,  68,  69,  68],
        [250, 254, 211, ..., 215, 255, 254],
        [ 62,  61,  60, ..., 130, 130, 131]], dtype=uint8),
 'filenames': ['leptodactylus_pentadactylus_s_000004.png',
  'camion_s_000148.png',
  'tipper_truck_s_001250.png',
  'american_elk_s_001521.png',
  'station_wagon_s_000293.png',
  'coupe_s_001735.png',
  'cassowary_s_001300.png',
  'cow_pony_s_001168.png',
  'sea_boat_s_001584.png',
  'tabby_s_001355.png',
  'muntjac_s_001000.png',
  'arabian_s_001354.png',
  'quarter_horse_s_000672.png',
  'passerine_s_000343.png',
  'camion_s_001895.png',
  'trailer_truck_s_000335.png',
  'dumper_s_000821.png',
  'alley_cat_s_000200.png',
  'accentor_s_000677.png',
  'frog_s_001671.png',
  'capreolus_capreolus_s_000051.png',
  'tomcat_s_000772.png',
  'pickerel_frog_s_000446.png',
  'bufo_s_001242.png',
  'cassowary_s_001246.png',
  'toad_s_001748.png',
  'cat_s_000081.png',
  'chihuahua_s_000825.png',
  'alces_alces_s_000959.png',
  'stealth_bomber_s_000554.png',
  'twinjet_s_000663.png',
  'trucking_rig_s_001402.png',
  'auto_s_000609.png',
  'tabby_cat_s_000983.png',
  'wapiti_s_000416.png',
  'monoplane_s_000895.png',
  'true_cat_s_000247.png',
  'tennessee_walker_s_000486.png',
  'house_cat_s_000243.png',
  'house_cat_s_001196.png',
  'pekinese_s_001337.png',
  'ostrich_s_001368.png',
  'ostrich_s_001150.png',
  'stallion_s_000046.png',
  'station_waggon_s_000041.png',
  'coupe_s_001944.png',
  'estate_car_s_000580.png',
  'accentor_s_000759.png',
  'emu_novaehollandiae_s_000795.png',
  'dive_bomber_s_001390.png',
  'articulated_lorry_s_000131.png',
  'pekinese_s_001093.png',
  'broodmare_s_001463.png',
  'delivery_truck_s_000834.png',
  'songbird_s_001052.png',
  'emu_s_000692.png',
  'puppy_s_000115.png',
  'wagtail_s_001821.png',
  'dama_dama_s_000658.png',
  'domestic_cat_s_001970.png',
  'ambulance_s_003039.png',
  'convertible_s_001763.png',
  'tank_ship_s_001229.png',
  'cassowary_s_001055.png',
  'wagon_s_001142.png',
  'police_cruiser_s_000620.png',
  'moose_s_002308.png',
  'aerial_ladder_truck_s_000584.png',
  'saddle_horse_s_000717.png',
  'tanker_s_001350.png',
  'mongrel_s_001571.png',
  'truck_s_000835.png',
  'pickerel_frog_s_001195.png',
  'lipizzan_s_000399.png',
  'tabby_s_000074.png',
  'automobile_s_001887.png',
  'moving_van_s_001665.png',
  'attack_aircraft_s_000153.png',
  'domestic_cat_s_001596.png',
  'compact_car_s_000048.png',
  'domestic_cat_s_000009.png',
  'pekingese_s_002089.png',
  'capreolus_capreolus_s_001095.png',
  'blenheim_spaniel_s_001103.png',
  'stallion_s_000040.png',
  'stud_mare_s_001672.png',
  'elk_s_000920.png',
  'lipizzan_s_001123.png',
  'fire_truck_s_002721.png',
  'elk_s_001888.png',
  'finch_s_000750.png',
  'tabby_s_000880.png',
  'banana_boat_s_001324.png',
  'twinjet_s_000591.png',
  'shooting_brake_s_000029.png',
  'rana_pipiens_s_000101.png',
  'station_wagon_s_001387.png',
  'station_wagon_s_002712.png',
  'odocoileus_hemionus_s_000221.png',
  'convertible_s_001715.png',
  'abandoned_ship_s_000574.png',
  'true_cat_s_000114.png',
  'dustcart_s_000063.png',
  'frog_s_000797.png',
  'green_frog_s_001320.png',
  'compact_car_s_001038.png',
  'freighter_s_001351.png',
  'mutt_s_000251.png',
  'accentor_s_000303.png',
  'lorry_s_001154.png',
  'fire_truck_s_000894.png',
  'cargo_vessel_s_000731.png',
  'cruiser_s_000774.png',
  'lippizan_s_000359.png',
  'broodmare_s_001741.png',
  'fighter_aircraft_s_000876.png',
  'amphibious_aircraft_s_000216.png',
  'leopard_frog_s_000339.png',
  'trucking_rig_s_001315.png',
  'shooting_brake_s_000886.png',
  'pipit_s_000549.png',
  'ostrich_s_002148.png',
  'trucking_rig_s_001600.png',
  'alauda_arvensis_s_000755.png',
  'rana_temporaria_s_001087.png',
  'bufo_s_000136.png',
  'estate_car_s_000529.png',
  'aerial_ladder_truck_s_000997.png',
  'toy_spaniel_s_000384.png',
  'amphibious_aircraft_s_001195.png',
  'fallow_deer_s_001598.png',
  'quarter_horse_s_000414.png',
  'anuran_s_000712.png',
  'arabian_s_001366.png',
  'auto_s_000040.png',
  'cargo_ship_s_001063.png',
  'motorcar_s_000121.png',
  'motorcar_s_000305.png',
  'anthus_pratensis_s_001071.png',
  'cruiser_s_000294.png',
  'wagon_s_000763.png',
  'alley_cat_s_002579.png',
  'tabby_cat_s_000825.png',
  'spadefoot_s_000051.png',
  'wagtail_s_002075.png',
  'fallow_deer_s_001697.png',
  'garbage_truck_s_000777.png',
  'moving_van_s_000067.png',
  'mongrel_s_000696.png',
  'red_deer_s_000741.png',
  'true_cat_s_001768.png',
  'spadefoot_s_000377.png',
  'lipizzan_s_001233.png',
  'japanese_deer_s_000163.png',
  'toad_s_002436.png',
  'police_boat_s_001421.png',
  'puppy_s_002062.png',
  'lapdog_s_001869.png',
  'elk_s_001196.png',
  'domestic_cat_s_001235.png',
  'car_s_000057.png',
  'lightship_s_000064.png',
  'fallow_deer_s_001997.png',
  'quarter_horse_s_000022.png',
  'bufo_calamita_s_000566.png',
  'biplane_s_000624.png',
  'fire_truck_s_001616.png',
  'japanese_spaniel_s_000037.png',
  'ambulance_s_001394.png',
  'domestic_cat_s_001056.png',
  'tugboat_s_001384.png',
  'emu_s_000072.png',
  'gelding_s_000206.png',
  'puppy_s_000637.png',
  'tabby_cat_s_002607.png',
  'elk_s_001198.png',
  'estate_car_s_001496.png',
  'peke_s_001338.png',
  'arabian_s_001018.png',
  'fighter_aircraft_s_000538.png',
  'fallow_deer_s_001164.png',
  'lippizan_s_000390.png',
  'toy_dog_s_000932.png',
  'maltese_s_002151.png',
  'car_s_000002.png',
  'jumbo_jet_s_000697.png',
  'dump_truck_s_000008.png',
  'spadefoot_s_000084.png',
  'motortruck_s_000014.png',
  'jetliner_s_001502.png',
  'tanker_s_000157.png',
  'riding_horse_s_001870.png',
  'cabin_cruiser_s_000096.png',
  'dredger_s_001623.png',
  'pipit_s_001102.png',
  'mongrel_s_002430.png',
  'skylark_s_000150.png',
  'cat_s_001604.png',
  'puppy_s_000211.png',
  'airbus_s_001124.png',
  'leopard_frog_s_001021.png',
  'wagon_s_001824.png',
  'garbage_truck_s_000147.png',
  'tabby_s_001354.png',
  'rana_temporaria_s_000295.png',
  'lorry_s_000364.png',
  'estate_car_s_000075.png',
  'tabby_s_000970.png',
  'fire_engine_s_000985.png',
  'toad_s_000022.png',
  'texas_toad_s_000215.png',
  'broodmare_s_000707.png',
  'car_s_000286.png',
  'twinjet_s_000565.png',
  'truck_s_001385.png',
  'toy_dog_s_000752.png',
  'police_boat_s_000092.png',
  'toy_dog_s_001197.png',
  'cassowary_s_002446.png',
  'articulated_lorry_s_000050.png',
  'monoplane_s_000781.png',
  'lightship_s_000343.png',
  'powerboat_s_001486.png',
  'jumbo_jet_s_000071.png',
  'bufo_debilis_s_000024.png',
  'transporter_s_000272.png',
  'estate_car_s_000743.png',
  'motorcar_s_000697.png',
  'rana_catesbeiana_s_001655.png',
  'tabby_s_000675.png',
  'remount_s_000285.png',
  'rana_catesbeiana_s_001521.png',
  'true_frog_s_000223.png',
  'airliner_s_002304.png',
  'natterjack_s_000987.png',
  'leptodactylid_s_000082.png',
  'coupe_s_001892.png',
  'quarter_horse_s_000419.png',
  'car_s_001323.png',
  'maltese_dog_s_001043.png',
  'boat_s_000543.png',
  'tabby_cat_s_001537.png',
  'rana_catesbeiana_s_001096.png',
  'bufo_bufo_s_000326.png',
  'pilot_boat_s_000646.png',
  'toad_frog_s_001672.png',
  'boat_s_000988.png',
  'deer_s_001383.png',
  'bufo_bufo_s_000261.png',
  'leopard_frog_s_000763.png',
  'coupe_s_002178.png',
  'cat_s_000663.png',
  'ship_s_000175.png',
  'house_cat_s_001471.png',
  'stag_s_001458.png',
  'station_wagon_s_001337.png',
  'quarter_horse_s_002201.png',
  'coupe_s_000698.png',
  'tomcat_s_002553.png',
  'scow_s_001266.png',
  'chihuahua_s_000385.png',
  'convertible_s_001500.png',
  'convertible_s_000408.png',
  'odocoileus_hemionus_s_000512.png',
  'jumbo_jet_s_000971.png',
  'truck_s_000650.png',
  'domestic_cat_s_001288.png',
  'walking_horse_s_000194.png',
  'elk_s_001657.png',
  'tipper_truck_s_000287.png',
  'dumper_s_000648.png',
  'struthio_camelus_s_000225.png',
  'woodland_caribou_s_000803.png',
  'ladder_truck_s_000795.png',
  'pantechnicon_s_000230.png',
  'shooting_brake_s_000229.png',
  'jetliner_s_001349.png',
  'toy_dog_s_001280.png',
  'dump_truck_s_002104.png',
  'twinjet_s_001360.png',
  'tugboat_s_000715.png',
  'passerine_s_000360.png',
  'automobile_s_002337.png',
  'honey_eater_s_001422.png',
  'attack_aircraft_s_001304.png',
  'toy_dog_s_000114.png',
  'anuran_s_000550.png',
  'mouser_s_000382.png',
  'sparrow_s_000037.png',
  'stud_mare_s_001038.png',
  'speedboat_s_002588.png',
  'passenger_ship_s_002153.png',
  'bufo_bufo_s_001876.png',
  'biplane_s_000651.png',
  'gelding_s_001785.png',
  'trucking_rig_s_001598.png',
  'deer_s_000309.png',
  'pekingese_s_001946.png',
  'frog_s_002802.png',
  'cervus_unicolor_s_000290.png',
  'honey_eater_s_000478.png',
  'automobile_s_001152.png',
  'coupe_s_000846.png',
  'flying_bird_s_000252.png',
  'automobile_s_002343.png',
  'japanese_spaniel_s_001162.png',
  'fire_truck_s_000043.png',
  'semi_s_001207.png',
  'fighter_aircraft_s_001840.png',
  'ship_s_001976.png',
  'caribou_s_001222.png',
  'police_cruiser_s_001347.png',
  'coupe_s_000042.png',
  'bufo_bufo_s_000995.png',
  'tabby_s_001148.png',
  'true_cat_s_000476.png',
  'garbage_truck_s_001442.png',
  'fighter_aircraft_s_000385.png',
  'quarter_horse_s_001602.png',
  'camion_s_000116.png',
  'tennessee_walker_s_000539.png',
  'lipizzan_s_000452.png',
  'trucking_rig_s_001594.png',
  'shooting_brake_s_001611.png',
  'puppy_s_002096.png',
  'auto_s_000855.png',
  'bufo_marinus_s_001364.png',
  'natterjack_s_000036.png',
  'pontoon_s_000643.png',
  'stallion_s_001256.png',
  'coupe_s_001863.png',
  'house_cat_s_000079.png',
  'jetliner_s_000981.png',
  'felis_catus_s_000853.png',
  'tabby_cat_s_000827.png',
  'struthio_camelus_s_001250.png',
  'fawn_s_001915.png',
  'canis_familiaris_s_001298.png',
  'lipizzan_s_002122.png',
  'toy_spaniel_s_001133.png',
  'dump_truck_s_000029.png',
  'fighter_s_001042.png',
  'domestic_cat_s_000493.png',
  'cervus_elaphus_s_001764.png',
  'airbus_s_000627.png',
  'fawn_s_001452.png',
  'fallow_deer_s_000959.png',
  'spadefoot_s_000777.png',
  'seaplane_s_001639.png',
  'plane_s_001066.png',
  'bufo_viridis_s_000348.png',
  'crapaud_s_000051.png',
  'seaplane_s_001447.png',
  'boat_s_000404.png',
  'convertible_s_001242.png',
  'toad_s_000201.png',
  'finch_s_000494.png',
  'fire_engine_s_001437.png',
  'pipit_s_000226.png',
  'toy_dog_s_000960.png',
  'delivery_truck_s_001121.png',
  'bufo_marinus_s_001506.png',
  'studhorse_s_000010.png',
  'woodland_caribou_s_001003.png',
  'station_wagon_s_000260.png',
  'pilot_boat_s_000356.png',
  'stud_mare_s_001497.png',
  'tabby_cat_s_001966.png',
  'american_toad_s_000006.png',
  'tipper_s_000010.png',
  'tomcat_s_002230.png',
  'dive_bomber_s_001120.png',
  'wapiti_s_000802.png',
  'biplane_s_000862.png',
  'blenheim_spaniel_s_000589.png',
  'shooting_brake_s_001161.png',
  'jetliner_s_000400.png',
  'tabby_s_000923.png',
  'alces_alces_s_000361.png',
  'police_boat_s_000002.png',
  'mutt_s_001696.png',
  'cervus_elaphus_s_001695.png',
  'quarter_horse_s_000752.png',
  'accentor_s_000449.png',
  'tabby_cat_s_000144.png',
  'fire_engine_s_001513.png',
  'tennessee_walking_horse_s_001187.png',
  'bufo_s_001247.png',
  'arabian_s_002147.png',
  'compact_s_001258.png',
  'elk_s_002339.png',
  'stud_mare_s_001384.png',
  'fighter_aircraft_s_000745.png',
  'police_cruiser_s_001047.png',
  'lipizzan_s_001764.png',
  'cat_s_000331.png',
  'taxi_s_000701.png',
  'boat_s_000432.png',
  'japanese_deer_s_000942.png',
  'sambar_s_000076.png',
  'ostrich_s_001559.png',
  'dive_bomber_s_000185.png',
  'lark_s_001532.png',
  'flightless_bird_s_000480.png',
  'stealth_fighter_s_001312.png',
  'jumbojet_s_000789.png',
  'delivery_truck_s_000510.png',
  'biplane_s_001901.png',
  'lorry_s_001185.png',
  'crapaud_s_000511.png',
  'boat_s_001280.png',
  'bird_s_001357.png',
  'stud_mare_s_001477.png',
  'arabian_s_000751.png',
  'rangifer_caribou_s_000586.png',
  'monoplane_s_000036.png',
  'house_cat_s_001321.png',
  'stealth_fighter_s_000240.png',
  'oil_tanker_s_000129.png',
  'tipper_truck_s_000416.png',
  'roe_deer_s_000358.png',
  'rhea_americana_s_000475.png',
  'lippizaner_s_000517.png',
  'cassowary_s_000297.png',
  'pekingese_s_001675.png',
  'accentor_s_001058.png',
  'lapdog_s_000227.png',
  'auto_s_001153.png',
  'fire_engine_s_000443.png',
  'muntjac_s_000815.png',
  'lightship_s_000090.png',
  'dog_s_002441.png',
  'auto_s_001951.png',
  'arabian_s_000328.png',
  'odocoileus_hemionus_s_000188.png',
  'barking_deer_s_000019.png',
  'dive_bomber_s_001486.png',
  'bufo_viridis_s_000503.png',
  'wrecker_s_002294.png',
  'monoplane_s_000206.png',
  'arabian_s_002282.png',
  'speedboat_s_002160.png',
  'cargo_vessel_s_002136.png',
  'garbage_truck_s_000726.png',
  'delivery_truck_s_001468.png',
  'house_cat_s_002240.png',
  'house_cat_s_000045.png',
  'caribou_s_002007.png',
  'propeller_plane_s_000451.png',
  'fallow_deer_s_001082.png',
  'dog_s_001897.png',
  'bufo_bufo_s_001631.png',
  'spadefoot_s_000191.png',
  'multiengine_airplane_s_000186.png',
  'auto_s_002359.png',
  'stealth_bomber_s_001607.png',
  'passenger_ship_s_000582.png',
  'airliner_s_001297.png',
  'fallow_deer_s_000973.png',
  'speedboat_s_000178.png',
  'boat_s_001444.png',
  'estate_car_s_000712.png',
  'english_toy_spaniel_s_000888.png',
  'passerine_s_000699.png',
  'rana_pipiens_s_000286.png',
  'tanker_s_000025.png',
  'car_s_001956.png',
  'stealth_bomber_s_000424.png',
  'airliner_s_001070.png',
  'stud_mare_s_001348.png',
  'quarter_horse_s_000282.png',
  'maltese_s_001818.png',
  'lorry_s_001786.png',
  'true_frog_s_000064.png',
  'cassowary_s_001372.png',
  'houseboat_s_000626.png',
  'domestic_cat_s_000035.png',
  'deer_s_001596.png',
  'cow_pony_s_000803.png',
  'tabby_cat_s_001466.png',
  'tipper_truck_s_001525.png',
  'stealth_fighter_s_000533.png',
  'station_wagon_s_000750.png',
  'wagtail_s_001549.png',
  'rangifer_caribou_s_000985.png',
  'cargo_ship_s_000408.png',
  'cab_s_000788.png',
  'flatboat_s_000044.png',
  'bufo_viridis_s_000457.png',
  'fallow_deer_s_000040.png',
  'barren_ground_caribou_s_000077.png',
  'pekinese_s_000453.png',
  'female_horse_s_000358.png',
  'compact_car_s_000869.png',
  'tabby_cat_s_002454.png',
  'delivery_truck_s_000864.png',
  'cargo_ship_s_000802.png',
  'attack_aircraft_s_000037.png',
  'convertible_s_000037.png',
  'broodmare_s_001448.png',
  'toy_spaniel_s_001286.png',
  'packet_boat_s_001206.png',
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In [ ]:

    

data = cPickle.load(data_raw)


    

In [ ]:

    

print(train_x.shape)
print(train_y.shape)
print(test_x.shape)
print(test_y.shape)


    

In [ ]:

    

train_x.dtype


    

In [ ]:

    

train_set = (train_x, train_y)
valid_set = (train_x, train_y)
test_set = (test_x, test_y)

train_set_x, train_set_y = shared_dataset(train_set)
valid_set_x, valid_set_y = shared_dataset(valid_set)
test_set_x, test_set_y = shared_dataset(test_set)


    

In [ ]:

    




    

In [19]:

    

import cPickle as pickle
import numpy as np
import os
DATA_PATH = "../../data/cifar-10-batches-py/"

def load_CIFAR_batch(filename):
  """ load single batch of cifar """
  with open(filename, 'rb') as f:
    datadict = pickle.load(f)
    X = datadict['data']
    Y = datadict['labels']
    print X.shape
    #X = X.reshape(10000, 3, 32, 32).transpose(0,2,3,1).astype("float")
    X = X.reshape(10000, 3, 32, 32).transpose(0,1,2,3).astype("float")
    Y = np.array(Y)
    return X, Y

x,y = load_CIFAR_batch(DATA_PATH + "data_batch_1")


    

    




(10000, 3072)

In [20]:

    

x.shape


    

    
Out[20]:





(10000, 3, 32, 32)

In [ ]:

    




    

In [14]:

    

list_val = []
list_val.append([1, 2, 3])
list_val.append([1, 2, 3])
list_val.append([1, 2, 3])


    

In [16]:

    

[i[0] for i in list_val]
[i[1] for i in list_val]


    

    
Out[16]:





[2, 2, 2]

In [ ]: