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from typing import Dict, Any | |
import torch | |
import torch.nn as nn | |
import numpy as np | |
class ConsciousnessModel(nn.Module): | |
def __init__(self, config: Dict[str, Any]): | |
super().__init__() | |
self.self_awareness = nn.Linear(768, 256) | |
self.meta_cognitive = nn.Linear(256, 128) | |
self.phenomenal = nn.Linear(128, 64) | |
self.integration = nn.Linear(64, 32) | |
def forward(self, x: torch.Tensor) -> Dict[str, Any]: | |
awareness = torch.relu(self.self_awareness(x)) | |
meta = torch.relu(self.meta_cognitive(awareness)) | |
phenomenal = torch.relu(self.phenomenal(meta)) | |
integrated = self.integration(phenomenal) | |
return { | |
'awareness': awareness, | |
'meta_cognitive': meta, | |
'phenomenal': phenomenal, | |
'integrated': integrated | |
} |