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reduce cob model to 400m

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This commit is contained in:
Dobromir Popov
2025-06-25 13:11:00 +03:00
parent 2cbc202d45
commit fdb9e83cf9
6 changed files with 195 additions and 29 deletions
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18
tests/test_realtime_rl_cob_trader.py
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@ -112,11 +112,11 @@ class RealtimeRLTester:
raise
async def test_model_parameter_count(self):
"""Test that model has approximately 1B parameters"""
"""Test that model has approximately 400M parameters"""
logger.info("🔢 Testing Model Parameter Count...")
try:
model = MassiveRLNetwork(input_size=2000, hidden_size=4096, num_layers=12)
model = MassiveRLNetwork(input_size=2000, hidden_size=2048, num_layers=8)
total_params = sum(p.numel() for p in model.parameters())
trainable_params = sum(p.numel() for p in model.parameters() if p.requires_grad)
@ -124,15 +124,23 @@ class RealtimeRLTester:
logger.info(f"Total parameters: {total_params:,}")
logger.info(f"Trainable parameters: {trainable_params:,}")
# Check if parameters are approximately 400M (350M - 450M range)
target_400m = total_params >= 350_000_000 and total_params <= 450_000_000
self.test_results['test_model_parameter_count'] = {
'status': 'PASSED',
'status': 'PASSED' if target_400m else 'WARNING',
'total_parameters': total_params,
'trainable_parameters': trainable_params,
'parameter_size_gb': (total_params * 4) / (1024**3), # 4 bytes per float32
'is_massive': total_params > 100_000_000 # At least 100M parameters
'is_optimized': target_400m, # Around 400M parameters for faster startup
'target_range': '350M - 450M parameters'
}
logger.info(f"✅ Model has {total_params:,} parameters ({total_params/1e9:.2f}B)")
logger.info(f"✅ Model has {total_params:,} parameters ({total_params/1e6:.0f}M)")
if target_400m:
logger.info("✅ Parameter count within 400M target range for fast startup")
else:
logger.warning(f"⚠️ Parameter count outside 400M target range: {total_params/1e6:.0f}M")
except Exception as e:
self.test_results['test_model_parameter_count'] = {'status': 'FAILED', 'error': str(e)}