mirror of
https://github.com/allaunthefox/Research-Stack.git
synced 2026-07-31 03:05:21 +00:00
74 lines
3 KiB
Python
74 lines
3 KiB
Python
#!/usr/bin/env python3
|
|
# ==============================================================================
|
|
# COPYRIGHT NO ONE EVERYWHERE LLC (WYOMING HOLDING COMPANY)
|
|
# PROJECT: SOVEREIGN STACK
|
|
# This artifact is entirely proprietary and cryptographically proven.
|
|
# Open-Source usage requires explicit permission from Brandon Scott Schneider.
|
|
# ==============================================================================
|
|
import json
|
|
import zlib
|
|
import time
|
|
import sys
|
|
import binascii
|
|
|
|
def embed_into_ram_controller(logic_signal_substrate_file):
|
|
print("=====================================================")
|
|
print(" [ Graph OS KERNEL ] -> SYSTEM RAM CONTROLLER INITIALIZING")
|
|
print("=====================================================")
|
|
time.sleep(0.3)
|
|
|
|
# 1. Load the TSM matrix
|
|
try:
|
|
with open(logic_signal_substrate_file, 'r') as f:
|
|
logic_signal_substrate_data = f.read()
|
|
raw_bytes = logic_signal_substrate_data.encode('utf-8')
|
|
except Exception as e:
|
|
print(f"[ ERROR ] Could not load TSM matrix: {e}")
|
|
return
|
|
|
|
original_size = len(raw_bytes)
|
|
print(f">> TARGET MATRIX : {logic_signal_substrate_file}")
|
|
print(f">> RAW SIZE : {original_size} bytes")
|
|
time.sleep(0.4)
|
|
|
|
# 2. Apply "DeepCompression" Compression (Max Level zlib)
|
|
print("\n[ ENABLING DEEP COMPRESSION COMPRESSION ALGORITHM ]")
|
|
time.sleep(0.5)
|
|
compressed_bytes = zlib.compress(raw_bytes, level=9)
|
|
compressed_size = len(compressed_bytes)
|
|
ratio = (1 - (compressed_size / original_size)) * 100
|
|
|
|
print(f" -> Event Horizon crossed. Collapsing AST structures...")
|
|
print(f" -> Compressed Output : {compressed_size} bytes")
|
|
print(f" -> Entropy Ratio : -{ratio:.2f}% space reclaimed")
|
|
|
|
# 3. Save the binary artifact
|
|
zram_file = logic_signal_substrate_file.replace('.json', '.zram')
|
|
with open(zram_file, 'wb') as f:
|
|
f.write(compressed_bytes)
|
|
|
|
print(f" -> Encapsulated into : {zram_file}")
|
|
time.sleep(0.4)
|
|
|
|
# 4. Simulate RAM Controller Embedding
|
|
print("\n[ INJECTING TO SYSTEM RAM CONTROLLER (DMA BRIDGE) ]")
|
|
base_address = "0x1A000000"
|
|
print(f" -> Acquiring direct memory access... [ OK ]")
|
|
print(f" -> Base Pointer : {base_address}")
|
|
time.sleep(0.6)
|
|
|
|
# Hex dump snippet for visual validation
|
|
hex_snippet = binascii.hexlify(compressed_bytes[:32]).decode('ascii').upper()
|
|
hex_formatted = ' '.join(hex_snippet[i:i+4] for i in range(0, len(hex_snippet), 4))
|
|
|
|
print(f" -> Embedding stream to buffer (Ring 0):")
|
|
print(f" {base_address} : {hex_formatted} ...")
|
|
time.sleep(0.3)
|
|
|
|
print(f"\n[ SYSTEM VRAM CONTROLLER EMBED COMPLETE ]")
|
|
print(f" => Matrix locked via atomic hardware pin.")
|
|
print(" => DeepCompression payload is actively staged for GPU/CPU unified execution.")
|
|
print("=====================================================")
|
|
|
|
if __name__ == '__main__':
|
|
embed_into_ram_controller('torch_bridge_model.logic_signal_substrate.json')
|