weight_decay=eval(self.config['weight_decay'])

这行代码中，`self.config` 是一个字典，`'weight_decay'` 是这个字典中的一个键，`eval()` 函数用于将这个键对应的值（字符串类型）转换为 Python 表达式并求值，最终得到的结果赋值给 `weight_decay` 变量。通常情况下，这个值会被用作模型优化器的正则化项系数。

相关问题

Traceback (most recent call last): File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\run.py", line 37, in <module> train_ner() File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\run.py", line 33, in train_ner train(args=args) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\train\bert_lstm_ner.py", line 626, in train tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 473, in train_and_evaluate return executor.run() File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 613, in run return self.run_local() File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 714, in run_local saving_listeners=saving_listeners) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 370, in train loss = self._train_model(input_fn, hooks, saving_listeners) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1161, in _train_model return self._train_model_default(input_fn, hooks, saving_listeners) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1191, in _train_model_default features, labels, ModeKeys.TRAIN, self.config) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1149, in _call_model_fn model_fn_results = self._model_fn(features=features, **kwargs) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\train\bert_lstm_ner.py", line 405, in model_fn total_loss, learning_rate, num_train_steps, num_warmup_steps, False) File "E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\bert\optimization.py", line 65, in create_optimizer exclude_from_weight_decay=["LayerNorm", "layer_norm", "bias"]) TypeError: Can't instantiate abstract class AdamWeightDecayOptimizer with abstract methods get_config 进程已结束,退出代码1

从错误信息看，这个问题与创建优化器时涉及到抽象类 AdamWeightDecayOptimizer 的实例化有关。前面提到过，这个类是一个抽象基类，不能直接实例化。

在这个具体的问题中，可能是你的代码中对于 AdamWeightDecayOptimizer 的使用方式不正确，导致无法实例化该类。你需要检查代码中创建优化器的部分，确保使用的是具体的子类，如 Adam、AdamW 等。

此外，还需要确认你是否导入了正确的模块，并且使用了合适的子类来实例化优化器对象。

如果问题仍然存在，请提供更多的代码和上下文信息，以便我能够更好地帮助你解决问题。