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config.py
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config.py
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import math
import os
from torch.nn.modules.loss import CrossEntropyLoss
CKPT_DIR = os.path.join(os.getcwd(), "best_dir")
RESULTS_DIR = os.path.join(os.getcwd(), "result_dir_1")
sweep_config = {
'method': 'bayes',
'name':'grid-augmentation-test',
'metric' : {
'name': 'best_acc',
'goal': 'maximize'
},
####Basic Hyper-parameters#####
'parameters' : {
'epochs': {
'value' : 50},
'batch_size': {
'value' : 4},
'model': {
'value': 'resnet'},
#'values' : ['resnet', 'scratch','efficient']},
'optimizer': {
'value': 'adabelief'},
#'values': ['adam', 'sgd', 'adabelief']},
'warm_up':{
#'value': 'no'},
'values': ['yes', 'no']},
'seed':{
#'value': 0},
'values': [0, 3407]},
'learning_rate': {
'value': 0.005},
'loss':{
'value': 'focal'},
#'values': ['focal', 'CrossEntropy']},
#'values': ['focal', 'CrossEntropy', 'LovaszHinge']},
},
'early_terminate':{
'type': 'hyperband',
's': 2,
'eta': 3,
'max_iter': 27,
},
}