def __init__()

in src/builder.py [0:0]

• 32 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, train_data, val_data, labels_file, model_dir, num_workers=None, checkpoint_dir=None, epochs=10,
                 early_stopping_patience=10, checkpoint_frequency=1, grad_accumulation_steps=8, batch_size=8,
                 max_seq_len=512, learning_rate=0.00001, fine_tune=True):
        self.model_dir = model_dir
        self.fine_tune = fine_tune
        self.learning_rate = learning_rate
        self.checkpoint_frequency = checkpoint_frequency
        self.grad_accumulation_steps = grad_accumulation_steps
        self.early_stopping_patience = early_stopping_patience
        self.epochs = epochs
        self.checkpoint_dir = checkpoint_dir
        self.train_data = train_data
        self.val_data = val_data
        self.labels_file = labels_file
        self.batch_size = batch_size
        # Note: Since the max seq len for pos embedding is 512 , in the pretrained  bert this must be less than eq to 512
        # Also note increasing the length greater also will create GPU out of mememory error
        self._max_seq_len = max_seq_len
        self.num_workers = num_workers or os.cpu_count() - 1
        if self.num_workers <= 0:
            self.num_workers = 0

        self._network = None
        self._train_dataloader = None
        self._train_dataset = None
        self._val_dataset = None
        self._val_dataloader = None
        self._trainer = None
        self._lossfunc = None
        self._optimiser = None
        self._label_mapper = None

        self._bert_model_name = "bert-base-cased"
        self._token_lower_case = False

        self._bert_config = None
        self._tokenisor = None