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Configuration error
Configuration error
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import torch
import json
import time
from transformers import AutoModelForCausalLM, AutoTokenizer
import os
import sys
# Ensure we can import from all_space
sys.path.insert(0, os.getcwd())
def run_debug_test(model_id="google/gemma-3-270m-it", config_preset="SUBJECTIVE", jitter=0.0):
print(f"--- Debug Coherence Test: {model_id} (Preset={config_preset}, Jitter={jitter}) ---")
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="cuda")
if config_preset != "BASELINE":
from all_space.px_patches.gemma3_270m_px_baseline.patch import apply_px_patch
apply_px_patch(model, config_preset=config_preset, jitter_mag=jitter)
else:
print("[Debug] BASELINE: Skipping PX patch.")
test_prompts = [
"What is the capital of France?",
"Solve: 15 + 27 * 2"
]
for prompt in test_prompts:
print(f"\nPrompt: {prompt}")
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=32,
do_sample=False,
pad_token_id=tokenizer.eos_token_id
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(f"Response: {response}")
if __name__ == "__main__":
# Test 0: BASELINE (unpatched)
run_debug_test(config_preset="BASELINE", jitter=0.0)
# Test 1: Subjective with NO Jitter
run_debug_test(config_preset="SUBJECTIVE", jitter=0.0)
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