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import os
__author__ = 'Rio'
from yacs.config import CfgNode as CN
config = CN()
config.root = os.path.dirname(os.path.abspath(__file__))
config.models = os.path.join(config.root, '../Model/liver_model_best.pth')
config.dataset_name = 'Thyroid'
config.distiller_num = 18 # liver:18; Mamary:18; Thyroid:5
config.jieba_dir = os.path.join(config.root, 'key_technical_words.txt')
config.image_dir = os.path.join(config.root, '../Data_demo/Images')
# config.ann_path = 'E:/Datasets/Ultrasound/Data/new_Liver2.json'
config.ann_path = os.path.join(config.root, '../Data_demo/Liver.json')
config.dict_pth = os.path.join(config.root, 'liver_dict.txt')
config.max_seq_length_train = 150
config.max_seq_length = 150
config.threshold = 3
config.num_workers = 0
config.batch_size = 32
config.evaluate_batch = 1
config.visual_extractor = 'resnet101'
config.visual_extractor_pretrained = True
config.d_model = 512
config.d_ff = 512
config.d_vf = 2048
config.num_heads = 8
config.num_layers = 3
config.dropout = 0.1
config.logit_layers = 1
config.bos_idx = 0
config.eos_idx = 0
config.pad_idx = 0
config.use_bn = 0
config.drop_prob_lm = 0.5
config.sample_n = 1
config.output_logsoftmax = 1
config.decoding_constraintt = 0
config.n_gpu = 1
config.epochs = 50
config.save_dir = '/Result/Models'
config.record_dir = '/Result/Records'
config.save_period = 1
config.monitor_mode = 'max'
config.monitor_metric = 'BLEU_4'
config.early_stop = 100
config.image_type = '2d'
config.optim = 'Adam'
config.lr_ve = 5e-5
config.lr_ed = 1e-3
config.weight_decay = 5e-5
config.amsgrad = True
config.lr_scheduler = 'StepLR'
config.step_size = 28
config.gamma = 0.1
config.seed = 9233
config.resume = None
config.embedding_vector = 300
config.nhidden = 512
config.nlayers = 1
config.bidirectional = True
config.rnn_type = 'LSTM'
# text_image_losses.py
config.cuda = True
config.train_smooth_gamma3 = 10.0
config.train_smooth_gamma2 = 5.0
config.train_smooth_gamma1 = 4.0
config.attn_pth = 'E:/Captionv0/Code/SGF/Result/Attn_pth'
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