***************
** Arguments **
***************
backbone: 
config_file: configs/trainers/CoOp/vit_b16_ep50_bs4.yaml
dataset_config_file: configs/datasets/imagenet.yaml
eval_only: True
head: 
load_epoch: None
model_dir: 
no_train: False
opts: ['DATASET.SUBSAMPLE_CLASSES', 'new_ratio5']
output_dir: output/new_ratio5/ZeroshotCLIP/vit_b16_ep50_bs4/imagenet/2
resume: 
root: /mnt/hdd/DATA
seed: 2
source_domains: None
target_domains: None
trainer: ZeroshotCLIP
transforms: None
************
** Config **
************
DATALOADER:
  K_TRANSFORMS: 1
  NUM_WORKERS: 8
  RETURN_IMG0: False
  TEST:
    BATCH_SIZE: 100
    SAMPLER: SequentialSampler
  TRAIN_U:
    BATCH_SIZE: 32
    N_DOMAIN: 0
    N_INS: 16
    SAME_AS_X: True
    SAMPLER: RandomSampler
  TRAIN_X:
    BATCH_SIZE: 4
    N_DOMAIN: 0
    N_INS: 16
    SAMPLER: RandomSampler
DATASET:
  ALL_AS_UNLABELED: False
  CIFAR_C_LEVEL: 1
  CIFAR_C_TYPE: 
  NAME: ImageNet
  NUM_LABELED: -1
  NUM_SHOTS: -1
  ROOT: /mnt/hdd/DATA
  SOURCE_DOMAINS: ()
  STL10_FOLD: -1
  SUBSAMPLE_CLASSES: new_ratio5
  TARGET_DOMAINS: ()
  VAL_PERCENT: 0.1
INPUT:
  COLORJITTER_B: 0.4
  COLORJITTER_C: 0.4
  COLORJITTER_H: 0.1
  COLORJITTER_S: 0.4
  CROP_PADDING: 4
  CUTOUT_LEN: 16
  CUTOUT_N: 1
  GB_K: 21
  GB_P: 0.5
  GN_MEAN: 0.0
  GN_STD: 0.15
  INTERPOLATION: bicubic
  NO_TRANSFORM: False
  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
  RANDAUGMENT_M: 10
  RANDAUGMENT_N: 2
  RGS_P: 0.2
  RRCROP_SCALE: (0.08, 1.0)
  SIZE: (224, 224)
  TRANSFORMS: ('random_resized_crop', 'random_flip', 'normalize')
MODEL:
  BACKBONE:
    NAME: ViT-B/16
    PRETRAINED: True
  HEAD:
    ACTIVATION: relu
    BN: True
    DROPOUT: 0.0
    HIDDEN_LAYERS: ()
    NAME: 
  INIT_WEIGHTS: 
OPTIM:
  ADAM_BETA1: 0.9
  ADAM_BETA2: 0.999
  BASE_LR_MULT: 0.1
  GAMMA: 0.1
  LR: 0.002
  LR_SCHEDULER: cosine
  MAX_EPOCH: 50
  MOMENTUM: 0.9
  NAME: sgd
  NEW_LAYERS: ()
  RMSPROP_ALPHA: 0.99
  SGD_DAMPNING: 0
  SGD_NESTEROV: False
  STAGED_LR: False
  STEPSIZE: (-1,)
  WARMUP_CONS_LR: 1e-05
  WARMUP_EPOCH: 1
  WARMUP_MIN_LR: 1e-05
  WARMUP_RECOUNT: True
  WARMUP_TYPE: constant
  WEIGHT_DECAY: 0.0005
OUTPUT_DIR: output/new_ratio5/ZeroshotCLIP/vit_b16_ep50_bs4/imagenet/2
RESUME: 
SEED: 2
TEST:
  COMPUTE_CMAT: False
  EVALUATOR: Classification
  FINAL_MODEL: last_step
  NO_TEST: False
  PER_CLASS_RESULT: False
  SPLIT: test
TRAIN:
  CHECKPOINT_FREQ: 0
  COUNT_ITER: train_x
  PRINT_FREQ: 20
TRAINER:
  CDAC:
    CLASS_LR_MULTI: 10
    P_THRESH: 0.95
    RAMPUP_COEF: 30
    RAMPUP_ITRS: 1000
    STRONG_TRANSFORMS: ()
    TOPK_MATCH: 5
  COCOOP:
    CTX_INIT: 
    N_CTX: 16
    PREC: fp16
  COOP:
    CLASS_TOKEN_POSITION: end
    CSC: False
    CTX_INIT: 
    N_CTX: 16
    PREC: fp16
  CROSSGRAD:
    ALPHA_D: 0.5
    ALPHA_F: 0.5
    EPS_D: 1.0
    EPS_F: 1.0
  DAEL:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 0.5
  DAELDG:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 0.5
  DDAIG:
    ALPHA: 0.5
    CLAMP: False
    CLAMP_MAX: 1.0
    CLAMP_MIN: -1.0
    G_ARCH: 
    LMDA: 0.3
    WARMUP: 0
  DOMAINMIX:
    ALPHA: 1.0
    BETA: 1.0
    TYPE: crossdomain
  ENTMIN:
    LMDA: 0.001
  FIXMATCH:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 1.0
  IVLP:
    CTX_INIT: a photo of a
    N_CTX_TEXT: 2
    N_CTX_VISION: 2
    PREC: fp16
    PROMPT_DEPTH_TEXT: 9
    PROMPT_DEPTH_VISION: 9
  M3SDA:
    LMDA: 0.5
    N_STEP_F: 4
  MAPLE:
    CTX_INIT: a photo of a
    N_CTX: 4
    PREC: fp16
    PROMPT_DEPTH: 9
  MCD:
    N_STEP_F: 4
  MEANTEACHER:
    EMA_ALPHA: 0.999
    RAMPUP: 5
    WEIGHT_U: 1.0
  MIXMATCH:
    MIXUP_BETA: 0.75
    RAMPUP: 20000
    TEMP: 2.0
    WEIGHT_U: 100.0
  MME:
    LMDA: 0.1
  NAME: ZeroshotCLIP
  ProDA:
    N_CTX: 16
    N_PROMPT: 32
    PREC: fp16
  SE:
    CONF_THRE: 0.95
    EMA_ALPHA: 0.999
    RAMPUP: 300
  VPT:
    CTX_INIT: a photo of a
    N_CTX_VISION: 2
    PREC: fp16
    PROMPT_DEPTH_VISION: 1
USE_CUDA: True
VERBOSE: True
VERSION: 1
Collecting env info ...
** System info **
PyTorch version: 2.2.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux 12 (bookworm) (x86_64)
GCC version: (Debian 12.2.0-14) 12.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.36

Python version: 3.11.2 (main, Mar 13 2023, 12:18:29) [GCC 12.2.0] (64-bit runtime)
Python platform: Linux-6.5.13-3-pve-x86_64-with-glibc2.36
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A800 80GB PCIe
GPU 1: NVIDIA A800 80GB PCIe

Nvidia driver version: 525.147.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 57 bits virtual
Byte Order:                         Little Endian
CPU(s):                             64
On-line CPU(s) list:                18,20,22,23,25-27,29,31,32,34,37,46-49
Off-line CPU(s) list:               0-17,19,21,24,28,30,33,35,36,38-45,50-63
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz
CPU family:                         6
Model:                              106
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          2
Stepping:                           6
CPU(s) scaling MHz:                 98%
CPU max MHz:                        3500.0000
CPU min MHz:                        800.0000
BogoMIPS:                           5800.00
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization:                     VT-x
L1d cache:                          1.5 MiB (32 instances)
L1i cache:                          1 MiB (32 instances)
L2 cache:                           40 MiB (32 instances)
L3 cache:                           48 MiB (2 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0-15,32-47
NUMA node1 CPU(s):                  16-31,48-63
Vulnerability Gather data sampling: Vulnerable: No microcode
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced / Automatic IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] flake8==3.7.9
[pip3] flake8==3.7.9
[pip3] numpy==1.26.4
[pip3] torch==2.2.1
[pip3] torchaudio==2.2.1
[pip3] torchvision==0.17.1
[pip3] triton==2.2.0
[conda] Could not collect
        Pillow (10.2.0)

Loading trainer: ZeroshotCLIP
Loading dataset: ImageNet
Loading preprocessed few-shot data from /mnt/hdd/DATA/imagenet/split_fewshot/shot_-1_shuffled-seed_2.pkl
SUBSAMPLE NEW_RATIO5 CLASSES!
Building transform_train
+ random resized crop (size=(224, 224), scale=(0.08, 1.0))
+ random flip
+ to torch tensor of range [0, 1]
+ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
Building transform_test
+ resize the smaller edge to 224
+ 224x224 center crop
+ to torch tensor of range [0, 1]
+ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
---------  --------
Dataset    ImageNet
# classes  500
# train_x  640,965
# val      25,000
# test     25,000
---------  --------
Loading CLIP (backbone: ViT-B/16)
Prompts: ['a photo of a rapeseed.', 'a photo of a hair clip.', 'a photo of a common gallinule.', 'a photo of a German Shepherd Dog.', 'a photo of a Italian Greyhound.', 'a photo of a fur coat.', 'a photo of a shovel.', 'a photo of a can opener.', 'a photo of a husky.', 'a photo of a ground beetle.', 'a photo of a African bush elephant.', 'a photo of a eastern diamondback rattlesnake.', 'a photo of a paddle wheel.', 'a photo of a tiger shark.', 'a photo of a European polecat.', 'a photo of a European garden spider.', 'a photo of a Chesapeake Bay Retriever.', 'a photo of a cardboard box / carton.', 'a photo of a acorn squash.', 'a photo of a feather boa.', 'a photo of a chiffonier.', 'a photo of a mashed potatoes.', 'a photo of a front curtain.', 'a photo of a common redshank.', 'a photo of a wok.', 'a photo of a mask.', 'a photo of a fireboat.', 'a photo of a Lhasa Apso.', 'a photo of a hammer.', 'a photo of a payphone.', 'a photo of a Sussex Spaniel.', 'a photo of a gar fish.', 'a photo of a Irish Water Spaniel.', 'a photo of a wool.', 'a photo of a jay.', 'a photo of a necklace.', 'a photo of a mushroom.', 'a photo of a fountain pen.', 'a photo of a grocery store.', 'a photo of a swim trunks / shorts.', 'a photo of a damselfly.', 'a photo of a goldfinch.', 'a photo of a silver salmon.', 'a photo of a trash can.', 'a photo of a Cairn Terrier.', 'a photo of a electric fan.', 'a photo of a sarong.', 'a photo of a prairie grouse.', 'a photo of a guinea pig.', 'a photo of a pirate ship.', 'a photo of a castle.', 'a photo of a trimaran.', 'a photo of a punching bag.', 'a photo of a backpack.', 'a photo of a grey fox.', 'a photo of a bell or wind chime.', 'a photo of a eastern hog-nosed snake.', 'a photo of a cauliflower.', 'a photo of a rifle.', 'a photo of a Irish Terrier.', 'a photo of a rock beauty fish.', 'a photo of a American bullfrog.', 'a photo of a bolo tie.', 'a photo of a tool kit.', 'a photo of a killer whale.', 'a photo of a chimpanzee.', 'a photo of a assault rifle.', 'a photo of a Appenzeller Sennenhund.', 'a photo of a water jug.', 'a photo of a Basset Hound.', 'a photo of a horse chestnut seed.', 'a photo of a Pembroke Welsh Corgi.', 'a photo of a cabbage.', 'a photo of a pug.', 'a photo of a rotary dial telephone.', 'a photo of a marmot.', 'a photo of a hoop skirt.', 'a photo of a pillow.', 'a photo of a filing cabinet.', 'a photo of a Rhodesian Ridgeback.', 'a photo of a slug.', 'a photo of a cheetah.', 'a photo of a dock.', 'a photo of a stopwatch.', 'a photo of a boathouse.', 'a photo of a beaver.', 'a photo of a jeans.', 'a photo of a abaya.', 'a photo of a T-shirt.', 'a photo of a little blue heron.', 'a photo of a banded gecko.', 'a photo of a macaw.', 'a photo of a sidewinder rattlesnake.', 'a photo of a barometer.', 'a photo of a sea lion.', 'a photo of a flute.', 'a photo of a cucumber.', 'a photo of a three-toed sloth.', 'a photo of a yellow garden spider.', 'a photo of a printer.', 'a photo of a hair dryer.', 'a photo of a honeycomb.', 'a photo of a gyromitra.', 'a photo of a lighthouse.', 'a photo of a forklift.', 'a photo of a fishing casting reel.', 'a photo of a vacuum cleaner.', 'a photo of a space shuttle.', 'a photo of a parking meter.', 'a photo of a magnetic compass.', 'a photo of a longhorn beetle.', 'a photo of a cocktail shaker.', 'a photo of a radio telescope.', 'a photo of a chain-link fence.', 'a photo of a piggy bank.', 'a photo of a china cabinet.', 'a photo of a African wild dog.', 'a photo of a ring-tailed lemur.', 'a photo of a pelican.', 'a photo of a taxicab.', 'a photo of a gorilla.', 'a photo of a sloth bear.', 'a photo of a candy store.', 'a photo of a soap dispenser.', 'a photo of a cassette.', 'a photo of a parachute.', 'a photo of a moped.', 'a photo of a product packet / packaging.', 'a photo of a academic gown.', 'a photo of a wild boar.', 'a photo of a plate rack.', 'a photo of a hermit crab.', 'a photo of a sawmill.', 'a photo of a Chow Chow.', 'a photo of a crayfish.', 'a photo of a airliner.', 'a photo of a gazelle.', 'a photo of a quilt.', 'a photo of a minivan.', 'a photo of a accordion.', 'a photo of a hair wig.', 'a photo of a hair spray.', 'a photo of a Dungeness crab.', 'a photo of a Miniature Schnauzer.', 'a photo of a clogs.', 'a photo of a Groenendael dog.', 'a photo of a tick.', 'a photo of a monitor.', 'a photo of a split-rail fence.', 'a photo of a ruler measuring stick.', 'a photo of a lion.', 'a photo of a electric ray.', 'a photo of a pole.', 'a photo of a ocean liner.', 'a photo of a hen of the woods mushroom.', 'a photo of a Irish Setter.', 'a photo of a cardigan.', 'a photo of a church.', 'a photo of a military uniform.', 'a photo of a banjo.', 'a photo of a thatched roof.', 'a photo of a broom.', 'a photo of a bulbul.', 'a photo of a West Highland White Terrier.', 'a photo of a stick insect.', 'a photo of a throne.', 'a photo of a platypus.', 'a photo of a barbell.', 'a photo of a hot pot.', 'a photo of a shoji screen / room divider.', "a photo of a Geoffroy's spider monkey.", 'a photo of a polar bear.', 'a photo of a torch.', 'a photo of a lifeboat.', 'a photo of a red king crab.', 'a photo of a digital watch.', 'a photo of a chickadee.', 'a photo of a langur.', 'a photo of a upright piano.', 'a photo of a toucan.', 'a photo of a Norfolk Terrier.', 'a photo of a quill.', 'a photo of a trifle.', 'a photo of a wheelbarrow.', 'a photo of a worm snake.', 'a photo of a plastic bag.', 'a photo of a valley.', 'a photo of a spindle.', 'a photo of a crutch.', 'a photo of a bathtub.', 'a photo of a tandem bicycle.', 'a photo of a sundial.', 'a photo of a bridegroom.', 'a photo of a pomegranate.', 'a photo of a missile.', 'a photo of a entertainment center.', 'a photo of a leafhopper.', 'a photo of a wardrobe.', 'a photo of a car mirror.', 'a photo of a corn.', 'a photo of a dishcloth.', 'a photo of a stage.', 'a photo of a Kuvasz.', 'a photo of a jellyfish.', "a photo of a potter's wheel.", 'a photo of a cheeseburger.', 'a photo of a American dipper.', 'a photo of a echidna.', 'a photo of a sneaker.', 'a photo of a Great Dane.', 'a photo of a sulphur-crested cockatoo.', 'a photo of a totem pole.', 'a photo of a snail.', 'a photo of a Bluetick Coonhound.', 'a photo of a ballpoint pen.', 'a photo of a clownfish.', 'a photo of a meatloaf.', 'a photo of a Pekingese.', 'a photo of a slot machine.', 'a photo of a orange.', 'a photo of a airplane wing.', 'a photo of a submarine.', 'a photo of a toilet seat.', 'a photo of a brussels griffon.', 'a photo of a stove.', 'a photo of a tobacco shop.', 'a photo of a one-piece bathing suit.', 'a photo of a Bouvier des Flandres dog.', 'a photo of a electrical switch.', 'a photo of a ruffed grouse.', 'a photo of a Newfoundland dog.', 'a photo of a southern black widow.', 'a photo of a red wine.', 'a photo of a plunger.', 'a photo of a Greater Swiss Mountain Dog.', 'a photo of a Affenpinscher.', 'a photo of a stretcher.', 'a photo of a drink pitcher.', 'a photo of a infant bed.', 'a photo of a Miniature Pinscher.', 'a photo of a microphone.', 'a photo of a buckle.', 'a photo of a red-breasted merganser.', 'a photo of a Norwegian Elkhound.', 'a photo of a crossword.', 'a photo of a crane bird.', 'a photo of a leatherback sea turtle.', 'a photo of a Pomeranian.', 'a photo of a tram.', 'a photo of a oil filter.', 'a photo of a oystercatcher.', 'a photo of a gas pump.', 'a photo of a vestment.', 'a photo of a magpie.', 'a photo of a tank.', 'a photo of a baseball.', 'a photo of a scuba diver.', 'a photo of a Mexican hairless dog (xoloitzcuintli).', 'a photo of a Toy Poodle.', 'a photo of a threshing machine.', 'a photo of a grey whale.', 'a photo of a fox squirrel.', 'a photo of a lemon.', 'a photo of a wall clock.', 'a photo of a geyser.', 'a photo of a home theater.', 'a photo of a triumphal arch.', 'a photo of a spatula.', 'a photo of a brass memorial plaque.', 'a photo of a stethoscope.', 'a photo of a wallaby.', 'a photo of a monarch butterfly.', 'a photo of a park bench.', 'a photo of a muzzle.', 'a photo of a jacamar.', 'a photo of a Shetland Sheepdog.', 'a photo of a catamaran.', 'a photo of a Papillon.', 'a photo of a ping-pong ball.', 'a photo of a messenger bag.', 'a photo of a apron.', 'a photo of a salt shaker.', 'a photo of a Alaskan tundra wolf.', 'a photo of a European green lizard.', 'a photo of a recreational vehicle.', 'a photo of a lampshade.', 'a photo of a screwdriver.', 'a photo of a four-poster bed.', 'a photo of a bra.', 'a photo of a daisy.', 'a photo of a tree frog.', 'a photo of a tow truck.', 'a photo of a ox.', 'a photo of a tiger.', 'a photo of a sea slug.', 'a photo of a rocking chair.', 'a photo of a refrigerator.', 'a photo of a marimba.', 'a photo of a tricycle.', 'a photo of a impala (antelope).', 'a photo of a hammerhead shark.', 'a photo of a box turtle.', 'a photo of a Shih Tzu.', 'a photo of a Basenji.', 'a photo of a alligator lizard.', 'a photo of a horse-drawn vehicle.', 'a photo of a sturgeon.', 'a photo of a goldfish.', 'a photo of a pedestal.', 'a photo of a disc brake.', 'a photo of a Wire Fox Terrier.', 'a photo of a ice cream.', 'a photo of a Afghan Hound.', 'a photo of a flamingo.', 'a photo of a Keeshond.', 'a photo of a common squirrel monkey.', 'a photo of a kite (bird of prey).', 'a photo of a hockey puck.', 'a photo of a desert grassland whiptail lizard.', 'a photo of a fire salamander.', 'a photo of a trilobite.', 'a photo of a chambered nautilus.', 'a photo of a peafowl.', 'a photo of a artichoke.', 'a photo of a oscilloscope.', 'a photo of a wooden spoon.', 'a photo of a Saluki.', 'a photo of a broccoli.', 'a photo of a patas monkey.', 'a photo of a water snake.', 'a photo of a tailed frog.', 'a photo of a scabbard.', 'a photo of a police van.', 'a photo of a pineapple.', 'a photo of a boa constrictor.', 'a photo of a Brittany dog.', 'a photo of a Siberian Husky.', 'a photo of a coyote.', 'a photo of a spaghetti squash.', 'a photo of a dishwasher.', 'a photo of a comic book.', 'a photo of a teddy bear.', 'a photo of a palace.', 'a photo of a Border Collie.', 'a photo of a iPod.', 'a photo of a Arctic fox.', 'a photo of a American alligator.', 'a photo of a mosque.', 'a photo of a hamper.', 'a photo of a night snake.', 'a photo of a sea anemone.', 'a photo of a restaurant.', 'a photo of a Boston Terrier.', 'a photo of a viaduct.', 'a photo of a hen.', 'a photo of a sink.', 'a photo of a bighorn sheep.', 'a photo of a mop.', 'a photo of a snowplow.', 'a photo of a wolf spider.', 'a photo of a tights.', 'a photo of a paper towel.', 'a photo of a black-and-white colobus.', 'a photo of a cuirass.', 'a photo of a cliff dwelling.', 'a photo of a English Setter.', 'a photo of a purse.', 'a photo of a dragonfly.', 'a photo of a balance beam.', 'a photo of a gymnastic horizontal bar.', 'a photo of a slip-on shoe.', 'a photo of a graduation cap.', 'a photo of a crate.', 'a photo of a digital clock.', 'a photo of a golf cart.', 'a photo of a cradle.', 'a photo of a window screen.', 'a photo of a pinwheel.', 'a photo of a spotlight.', 'a photo of a ant.', 'a photo of a cicada.', 'a photo of a chainsaw.', 'a photo of a shopping cart.', 'a photo of a pot pie.', 'a photo of a lotion.', 'a photo of a Irish Wolfhound.', 'a photo of a coral fungus.', 'a photo of a picket fence.', 'a photo of a suit.', 'a photo of a butternut squash.', 'a photo of a Australian Kelpie.', 'a photo of a mousetrap.', 'a photo of a movie theater.', 'a photo of a butcher shop.', 'a photo of a prayer rug.', 'a photo of a gas mask or respirator.', 'a photo of a prison.', 'a photo of a radiator grille.', 'a photo of a black-footed ferret.', 'a photo of a fig.', 'a photo of a bulletproof vest.', 'a photo of a metal nail.', 'a photo of a pizza.', 'a photo of a baguette.', 'a photo of a television.', 'a photo of a desktop computer.', 'a photo of a corkscrew.', 'a photo of a container ship.', 'a photo of a Egyptian Mau.', 'a photo of a cloak.', 'a photo of a Leonberger.', 'a photo of a dumbbell.', 'a photo of a vespa.', 'a photo of a canoe.', 'a photo of a rain barrel.', 'a photo of a Polaroid camera.', 'a photo of a analog clock.', 'a photo of a safety pin.', 'a photo of a Black and Tan Coonhound.', 'a photo of a bagel.', 'a photo of a umbrella.', 'a photo of a guenon.', 'a photo of a badger.', 'a photo of a carved pumpkin.', 'a photo of a sombrero.', 'a photo of a carbonara.', 'a photo of a scoreboard.', 'a photo of a dog sled.', 'a photo of a racket.', 'a photo of a barbershop.', 'a photo of a spider web.', 'a photo of a hunting bow.', 'a photo of a yurt.', 'a photo of a Norwich Terrier.', 'a photo of a Granny Smith apple.', 'a photo of a bullock cart.', 'a photo of a desk.', 'a photo of a gibbon.', 'a photo of a zucchini.', 'a photo of a croquet ball.', 'a photo of a ruddy turnstone.', 'a photo of a Scottish Deerhound.', 'a photo of a Angora rabbit.', 'a photo of a American Staffordshire Terrier.', 'a photo of a great grey owl.', 'a photo of a Dobermann.', 'a photo of a Entlebucher Sennenhund.', 'a photo of a Bedlington Terrier.', 'a photo of a go-kart.', 'a photo of a Redbone Coonhound.', 'a photo of a dome.', 'a photo of a window shade.', 'a photo of a shipwreck.', 'a photo of a swimming cap.', 'a photo of a snoek fish.', 'a photo of a popsicle.', 'a photo of a gossamer-winged butterfly.', 'a photo of a banana.', 'a photo of a carousel.', 'a photo of a baboon.', 'a photo of a spotted salamander.', 'a photo of a waffle iron.', 'a photo of a volcano.', 'a photo of a menu.', 'a photo of a dhole.', 'a photo of a cowboy boot.', 'a photo of a bottle cap.', 'a photo of a hay.', 'a photo of a flagpole.', 'a photo of a titi monkey.', 'a photo of a Crock Pot.', 'a photo of a unicycle.', 'a photo of a power drill.', 'a photo of a steel drum.', 'a photo of a acoustic guitar.', 'a photo of a milk can.', 'a photo of a beer glass.', 'a photo of a Beagle.', 'a photo of a pajamas.', 'a photo of a combine harvester.', 'a photo of a terrapin.', 'a photo of a lawn mower.', 'a photo of a English Springer Spaniel.', 'a photo of a laptop computer.', 'a photo of a Great Pyrenees dog.', 'a photo of a praying mantis.', 'a photo of a trolleybus.', 'a photo of a odometer.', 'a photo of a strainer.', 'a photo of a radiator.', 'a photo of a Ibizan Hound.', 'a photo of a thimble.', 'a photo of a siamang.', 'a photo of a partridge.', 'a photo of a hornbill.', 'a photo of a garter snake.', 'a photo of a trench coat.', 'a photo of a mountain.', 'a photo of a vase.', 'a photo of a beach.']
Loading evaluator: Classification
Note that load_model() is skipped as no pretrained model is given (ignore this if it's done on purpose)
Evaluate on the *test* set
=> result
* total: 25,000
* correct: 18,858
* accuracy: 75.43%
* error: 24.57%
* macro_f1: 74.94%
