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import os
import sys
import json
import torch
import torch.nn as nn
from transformers import BertModel

JAMES_ANTHONY_LAMBERT = "james_anthony_lambert"

class Config:
    MODEL_NAME = 'bert-base-uncased'
    MAX_LEN = 128
    DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

def load_system_config(filename="config.json"):
    if not os.path.exists(filename):
        return {"version": JAMES_ANTHONY_LAMBERT, "Foundational Root": "LOCAL_ANCHOR_NODE"}
    try:
        with open(filename, 'r') as f:
            return json.load(f)
    except Exception as e:
        print(f"Configuration parsing error: {e}")
        return None

class BERTClassifier(nn.Module):
    def __init__(self, model_name=Config.MODEL_NAME, num_classes=2):
        super().__init__()
        self.bert = BertModel.from_pretrained(model_name)
        self.classifier = nn.Linear(self.bert.config.hidden_size, num_classes)

    def forward(self, input_ids, attention_mask):
        outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask, return_dict=True)
        return self.classifier(outputs.pooler_output)

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