TypeError: _init_() got an unexpected keyword argument 'comment_text' and AttributeError: module 'config' has no attribute 'DEVICE'

[SauravYadavOfficial]

while doing the code for multilingual toxic comment classification i am getting errors, import config import dataset import engine import torch import pandas as pd import torch.nn as nn import numpy as np

from model import BERTBaseUncased from sklearn import model_selection from sklearn import metrics from transformers import AdamW from transformers import get_linear_schedule_with_warmup

def run(): df1 = pd.read_csv(r"C:\Users\saura\Desktop\tcc\input\jigsaw-toxic-comment-train.csv", usecols = ["comment_text","toxic"]) df2 = pd.read_csv(r"C:\Users\saura\Desktop\tcc\input\jigsaw-unintended-bias-train.csv", usecols = ["comment_text","toxic"])

  df_train = pd.concat([df1,df2], axis=0).reset_index(drop=True)

  df_valid = pd.read_csv(r"C:\Users\saura\Desktop\tcc\input\validation.csv")

  train_dataset = dataset.BERTDataset(
      comment_text=df_train.comment_text.values,
      target=df_train.toxic.values
  )

  train_data_loader = torch.utils.data.DataLoader(
      train_dataset,
      batch_size=config.TRAIN_BATCH_SIZE, 
      num_workers=4
  )

  valid_dataset = dataset.BERTDataset(
      comment_text=df_valid.comment_text.values, 
      target=df_valid.toxic.values
  )

  valid_data_loader = torch.utils.data.DataLoader(
      valid_dataset, 
      batch_size=config.VALID_BATCH_SIZE, 
      num_workers=1
  )

  device = torch.device(config.DEVICE)
  model = BERTBaseUncased()
  model.to(device)

  param_optimizer = list(model.named_parameters())
  no_decay = ["bias", "LayerNorm.bias", "LayerNorm.weight"]
  optimizer_parameters = [
      {
          "params": [
              p for n, p in param_optimizer if not any(nd in n for nd in no_decay)
          ],
          "weight_decay": 0.001,
      },
      {
          "params": [
              p for n, p in param_optimizer if any(nd in n for nd in no_decay)
          ],
          "weight_decay": 0.0,
      },
  ]

  num_train_steps = int(len(df_train) / config.TRAIN_BATCH_SIZE * config.EPOCHS)
  optimizer = AdamW(optimizer_parameters, lr=3e-5)
  scheduler = get_linear_schedule_with_warmup(
      optimizer, num_warmup_steps=0, num_training_steps=num_train_steps
  )

  best_accuracy = 0
  for epoch in range(config.EPOCHS):
      engine.train_fn(train_data_loader, model, optimizer, device, scheduler)
      outputs, targets = engine.eval_fn(valid_data_loader, model, device)
      targets = np.array(targets) >= 0.5
      accuracy = metrics.roc_auc_score(targets, outputs)
      print(f"AUC Score = {accuracy}")
      if accuracy > best_accuracy:
          torch.save(model.state_dict(), config.MODEL_PATH)
          best_accuracy = accuracy

if name == "main": run()

error message:

PS C:\Users\saura\Desktop\tcc\src> python train.py
Traceback (most recent call last):
  File "train.py", line 86, in <module>
    run()
  File "train.py", line 46, in run
    device = torch.device(config.DEVICE)
AttributeError: module 'config' has no attribute 'DEVICE'