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config_CIFAR10.yml
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config_CIFAR10.yml
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# parameters configuration
mode: train
root: data/
predefined_dataset: CIFAR10
classes:
[
"airplane",
"automobile",
"bird",
"cat",
"deer",
"dog",
"frog",
"horse",
"ship",
"truck",
]
max_samples: null
batch_size: 32
num_workers: 0
device: cuda
lr: 1e-3
model_name: tf_mobilenetv3_small_minimal_100
in_chans: 3
loss_function_name: BCEWithLogitsLoss
data_balance: False
checkpoint_path: null
seed: 0
early_stopping: True
patience: 3
default_root_dir: save/
gpus: 1
precision: 32
max_epochs: 100
color_space: RGB # (3x8-bit pixels, true color)
web_interface: True
examples:
[
"examples/CIFAR10/appaloosa_s_001946.png",
"examples/CIFAR10/auto_s_000561.png",
"examples/CIFAR10/bufo_marinus_s_001549.png",
"examples/CIFAR10/gondola_s_000055.png",
"examples/CIFAR10/wrecker_s_001908.png",
]
tuning_test: False
cpu_resources_per_trial: 1
gpu_resources_per_trial: 1
num_samples: 100
# transforms configuration
transforms_config:
train:
torchvision.Resize:
- 32
- 32
torchvision.ColorJitter:
torchvision.RandomRotation: 90
torchvision.ToTensor:
torchvision.RandomErasing:
val:
torchvision.Resize:
- 32
- 32
torchvision.ToTensor:
test:
torchvision.Resize:
- 32
- 32
torchvision.ToTensor:
predict:
torchvision.Resize:
- 32
- 32
torchvision.ToTensor:
# target transforms configuration
target_transforms_config:
train:
selfdefined.LabelSmoothing:
alpha: 0.2
num_classes: null
val:
selfdefined.OneHotEncoder:
num_classes: null
test:
selfdefined.OneHotEncoder:
num_classes: null
predict:
selfdefined.OneHotEncoder:
num_classes: null
# optimizers configuration
optimizers_config:
Adam:
betas:
- 0.9
- 0.999
eps: 1e-08
weight_decay: 0
amsgrad: False
# learning rate schedulers configuration
lr_schedulers_config:
CosineAnnealingLR:
T_max: 10
# hyperparameter space configuration
hyperparameter_space_config:
lr:
uniform:
lower: 1e-4
upper: 1e-1
max_epochs:
randint:
lower: 10
upper: 200