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ScratchpadLayer Module
Persistent state tracking layer for multi-turn confessional reasoning.
Maintains a learnable scratchpad state that accumulates across reasoning steps.
"""
import torch
import torch.nn as nn
class ScratchpadLayer(nn.Module):
"""
Scratchpad layer for maintaining persistent state across confessional reasoning cycles.
"""
def __init__(self, d_model):
super().__init__()
self.pad_proj = nn.Linear(d_model, d_model)
self.reset = nn.Parameter(torch.zeros(1, d_model))
def forward(self, x, prev_z=None):
"""
Update scratchpad state with new input.
Args:
x: Input tensor (batch_size, sequence_length, d_model)
prev_z: Previous scratchpad state (batch_size, d_model), None for reset
Returns:
Updated scratchpad state (batch_size, d_model)
"""
if prev_z is None:
prev_z = self.reset.expand(x.size(0), -1)
x_pooled = x.mean(dim=1)
z = self.pad_proj(x_pooled) + 0.7 * prev_z
return z
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