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import os
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import torch
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class Config(object):
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def __init__(self, data_dir):
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assert os.path.exists(data_dir)
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self.train_file = os.path.join(data_dir, "train.txt")
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self.dev_file = os.path.join(data_dir, "dev.txt")
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self.label_file = os.path.join(data_dir, "label.txt")
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assert os.path.isfile(self.train_file)
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assert os.path.isfile(self.dev_file)
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assert os.path.isfile(self.label_file)
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self.saved_model_dir = os.path.join(data_dir, "model")
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self.saved_model = os.path.join(self.saved_model_dir, "bert_model.pth")
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if not os.path.exists(self.saved_model_dir):
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os.mkdir(self.saved_model_dir)
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self.label_list = [label.strip() for label in open(self.label_file, "r", encoding="UTF-8").readlines()]
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self.num_labels = len(self.label_list)
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self.num_epochs = 3
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self.log_batch = 100
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self.batch_size = 128
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self.max_seq_len = 32
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self.require_improvement = 1000
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self.warmup_steps = 0
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self.weight_decay = 0.01
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self.max_grad_norm = 1.0
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self.learning_rate = 5e-5
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self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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