EPOCH_FINETUNING = 10
DICT_LR_FINETUNING = collections.OrderedDict()
DICT_LR_FINETUNING['0'] = 1e-3
DICT_LR_FINETUNING['2'] = 3e-4
DICT_LR_FINETUNING['3'] = 1e-4
DICT_LR_FINETUNING['4'] = 3e-5
DICT_LR_FINETUNING['5'] = 1e-5
DICT_LR_FINETUNING['7'] = 3e-6
DICT_LR_FINETUNING['8'] = 1e-6
train_task_one_step(model1=model1, filename_csv_train=FILENAME_CSV_TRAIN,
FILENAME_CSV_VALID=FILENAME_CSV_VALID, filename_csv_test=FILENAME_CSV_TEST,
input_shape=IMAGE_SHAPE, imgaug_train_seq=IMGAUG_TRAIN_SEQ,
add_top=False, change_top=True,
optimizer=OPTIMIZER, lookahead=LOOKAHEAD,
batch_size_train=BATCH_SIZE_TRAIN, batch_size_valid=BATCH_SIZE_TRAIN,
epoch_finetuning=EPOCH_FINETUNING, dict_lr_finetuning=DICT_LR_FINETUNING,
class_weight=CLASS_WEIGHT, label_smoothing=LABEL_SMOOTHING,
weight_class_start=WEIGHT_CLASS_START, weight_class_end=WEIGHT_CLASS_END,
balance_ratio=BALANCE_RATIO,
model_save_dir=model_save_dir1, model_name=MODEL_NAME,
verbose=2, gpu_num=GPU_NUM,
config_file_realtime='config_file_realtime.json')
#endregion
print('OK!')
train_task_one_step(
model_file=MODEL_FILE,
pre_define_model=PRE_DEFINE_MODEL,
filename_csv_train=FILENAME_CSV_TRAIN,
filename_csv_valid=FILENAME_CSV_VALID,
filename_csv_test=FILENAME_CSV_TEST,
add_top=ADD_TOP,
change_top=CHANGE_TOP,
input_shape=IMAGE_SHAPE,
imgaug_train_seq=IMGAUG_TRAIN_SEQ,
optimizer='adam',
lookahead=False,
batch_size_train=BATCH_SIZE_TRAIN,
batch_size_valid=BATCH_SIZE_TRAIN,
epoch=EPOCH_FINETUNING,
dict_lr=DICT_LR_FINETUNING,
class_weight=CLASS_WEIGHT,
label_smoothing=LABEL_SMOOTHING,
weight_class_start=WEIGHT_CLASS_START,
weight_class_end=WEIGHT_CLASS_END,
balance_ratio=BALANCE_RATIO,
# specificity=0.9, sensitivity=0.9,
verbose=VERBOSE,
model_save_dir=MODEL_SAVE_DIR,
model_name=MODEL_NAME,
config_file_realtime='config_file_realtime.json',
use_multiprocessing=USE_MULTIPROCESSING,
workers=WORKER,
plt_history_image_file=PLT_HISTORY_IMAGE_FILE)