mirror of
https://github.com/onestardao/WFGY.git
synced 2026-04-28 11:40:07 +00:00
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
# example_06_compare.py
|
||
# GPT-2 local vs optional remote compare
|
||
|
||
import pathlib, sys, numpy as np, torch
|
||
sys.path.insert(0, str(pathlib.Path(__file__).resolve().parents[1]))
|
||
|
||
from transformers import GPT2LMHeadModel, GPT2TokenizerFast
|
||
import wfgy_sdk as w
|
||
from wfgy_sdk.evaluator import compare_logits, pretty_print
|
||
|
||
use_remote = False
|
||
MODEL_ID = "gpt2" # remote model id
|
||
|
||
prompt = "Explain the Navier–Stokes millennium problem in 50 words."
|
||
|
||
if use_remote:
|
||
logits_before = w.call_remote_model(prompt, model_id=MODEL_ID)
|
||
else:
|
||
tok = GPT2TokenizerFast.from_pretrained("gpt2")
|
||
gpt2 = GPT2LMHeadModel.from_pretrained("gpt2").eval()
|
||
ids = tok(prompt, return_tensors="pt").input_ids
|
||
with torch.no_grad():
|
||
logits_before = gpt2(ids).logits[0, -1].cpu().numpy()
|
||
|
||
G = np.random.randn(256); G /= np.linalg.norm(G)
|
||
I = G + np.random.normal(scale=0.05, size=256)
|
||
|
||
eng = w.get_engine(reload=True)
|
||
logits_after = eng.run(input_vec=I, ground_vec=G, logits=logits_before)
|
||
|
||
print("\n=== Example 06 · Logit compare ===")
|
||
pretty_print(compare_logits(logits_before, logits_after))
|
||
print("⚠ Larger LLM → stronger variance drop & higher KL.\n")
|