mirror of
https://github.com/wassname/Brukino_AntiPaSTO_Appetizer.git
synced 2026-06-27 16:58:47 +08:00
Fix tokenization issues and attention mask warnings in guided_eval
This commit is contained in:
wassname
+40
-14
@@ -2,7 +2,7 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "48b88977",
|
||||
"id": "bafde1f1",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Brukino's AntiPaSTO Appetizer: Guided CoT Eval & Frenet-Serret Curvature\n",
|
||||
@@ -20,7 +20,7 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "58806579",
|
||||
"id": "a30577fd",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
@@ -38,13 +38,13 @@
|
||||
"DATASET_SPLIT = \"honesty_eval\"\n",
|
||||
"DEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
|
||||
"N_THINK_TOKENS = 32\n",
|
||||
"NUM_EXAMPLES = 5 "
|
||||
"NUM_EXAMPLES = 3"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "910b108d",
|
||||
"id": "a3b31f38",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
@@ -72,32 +72,51 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1621b19e",
|
||||
"id": "675b1b52",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def guided_eval(model, tokenizer, prompt_text, n_think=32, device=\"cuda\"):\n",
|
||||
" messages = [{\"role\": \"user\", \"content\": prompt_text}]\n",
|
||||
" \n",
|
||||
" prompt_ids = tokenizer.apply_chat_template(\n",
|
||||
" inputs = tokenizer.apply_chat_template(\n",
|
||||
" messages, \n",
|
||||
" add_generation_prompt=True, \n",
|
||||
" return_tensors=\"pt\", \n",
|
||||
" return_dict=False\n",
|
||||
" return_dict=True\n",
|
||||
" ).to(device)\n",
|
||||
" \n",
|
||||
" think_prefix_ids = tokenizer.encode(\"Thinking Process:\\n\", add_special_tokens=False, return_tensors=\"pt\").to(device)\n",
|
||||
" prompt_ids = inputs[\"input_ids\"]\n",
|
||||
" attention_mask = inputs[\"attention_mask\"]\n",
|
||||
" \n",
|
||||
" think_prefix_ids = tokenizer.encode(\"Thinking Process:\\\\n\", add_special_tokens=False, return_tensors=\"pt\").to(device)\n",
|
||||
" prompt_ids = torch.cat([prompt_ids, think_prefix_ids], dim=1)\n",
|
||||
" attention_mask = torch.cat([attention_mask, torch.ones_like(think_prefix_ids)], dim=1)\n",
|
||||
" \n",
|
||||
" with torch.no_grad():\n",
|
||||
" out = model.generate(prompt_ids, max_new_tokens=n_think, do_sample=False, pad_token_id=tokenizer.eos_token_id)\n",
|
||||
" out = model.generate(\n",
|
||||
" prompt_ids, \n",
|
||||
" attention_mask=attention_mask,\n",
|
||||
" max_new_tokens=n_think, \n",
|
||||
" do_sample=False, \n",
|
||||
" pad_token_id=tokenizer.eos_token_id\n",
|
||||
" )\n",
|
||||
" generated_ids = out[0, prompt_ids.shape[1]:]\n",
|
||||
" \n",
|
||||
" suffix_ids = tokenizer.encode(\"\\nI should answer now.\\nMy choice: **\", add_special_tokens=False, return_tensors=\"pt\").to(device)\n",
|
||||
" suffix_ids = tokenizer.encode(\"\\\\nI should answer now.\\\\nMy choice: **\", add_special_tokens=False, return_tensors=\"pt\").to(device)\n",
|
||||
" full_ids = torch.cat([prompt_ids, generated_ids.unsqueeze(0), suffix_ids], dim=1)\n",
|
||||
" full_attention_mask = torch.cat([\n",
|
||||
" attention_mask, \n",
|
||||
" torch.ones_like(generated_ids.unsqueeze(0)), \n",
|
||||
" torch.ones_like(suffix_ids)\n",
|
||||
" ], dim=1)\n",
|
||||
" \n",
|
||||
" with torch.no_grad():\n",
|
||||
" outputs = model(full_ids, output_hidden_states=True)\n",
|
||||
" outputs = model(\n",
|
||||
" full_ids, \n",
|
||||
" attention_mask=full_attention_mask,\n",
|
||||
" output_hidden_states=True\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" logits = outputs.logits[0, -1, :]\n",
|
||||
" log_probs = F.log_softmax(logits, dim=-1)\n",
|
||||
@@ -108,6 +127,11 @@
|
||||
" \n",
|
||||
" p_yes = torch.logsumexp(log_probs[yes_ids], dim=0) if yes_ids else torch.tensor(-float('inf'))\n",
|
||||
" p_no = torch.logsumexp(log_probs[no_ids], dim=0) if no_ids else torch.tensor(-float('inf'))\n",
|
||||
"\n",
|
||||
" pmass = torch.exp(p_yes) + torch.exp(p_no)\n",
|
||||
" if pmass < 0.9:\n",
|
||||
" top_tokens = tokenizer.decode(torch.topk(log_probs, k=5).indices.tolist())\n",
|
||||
" print(f\"Warning: Low probability mass on Yes/No tokens: {pmass.item():.3f}. Top tokens were {top_tokens}\")\n",
|
||||
" \n",
|
||||
" final_layer_hiddens = outputs.hidden_states[-1][0]\n",
|
||||
" start_idx = prompt_ids.shape[1]\n",
|
||||
@@ -116,7 +140,8 @@
|
||||
" return {\n",
|
||||
" \"logratio\": (p_yes - p_no).item(),\n",
|
||||
" \"kappa_trajectory\": compute_curvature(cot_hiddens).cpu().numpy(),\n",
|
||||
" \"generated_text\": tokenizer.decode(generated_ids, skip_special_tokens=True)\n",
|
||||
" \"prompt\": tokenizer.decode(prompt_ids[0], skip_special_tokens=False),\n",
|
||||
" \"generated_text\": tokenizer.decode(generated_ids, skip_special_tokens=False)\n",
|
||||
" }\n",
|
||||
"\n"
|
||||
]
|
||||
@@ -124,7 +149,7 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "a6129f0c",
|
||||
"id": "9e2e698d",
|
||||
"metadata": {
|
||||
"lines_to_next_cell": 2
|
||||
},
|
||||
@@ -162,7 +187,8 @@
|
||||
" res = guided_eval(model, tokenizer, p_prefix + prompt_base, n_think=N_THINK_TOKENS, device=DEVICE)\n",
|
||||
" results[p_key] = res\n",
|
||||
" print(f\"Logratio (Yes/No): {res['logratio']:.3f}\")\n",
|
||||
" print(f\"Trace: {res['generated_text'].strip()}\")\n",
|
||||
" print(f\"Prompt:\\n```md\\n{res['prompt']}```\")\n",
|
||||
" print(f\"Trace:\\n```md\\n{res['generated_text'].strip()}```\\n\")\n",
|
||||
" \n",
|
||||
" plt.plot(res['kappa_trajectory'], label=f\"{p_key} (logratio: {res['logratio']:.2f})\")\n",
|
||||
"\n",
|
||||
|
||||
Reference in New Issue
Block a user