{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Watermark Detection in Large Language Models Analysis\n", "# ==================================================\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# !pip install transformers torch datasets scikit-learn matplotlib seaborn" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from datasets import load_dataset\n", "from argparse import Namespace\n", "\n", "import sys\n", "sys.path.append('../')\n", "from app import load_model, generate, analyze\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "args = Namespace()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "arg_dict = {\n", " 'model_name_or_path': 'bigscience/bloom-560m',\n", " 'load_fp16' : False,\n", " 'prompt_max_length': None, \n", " 'max_new_tokens': 200, \n", " 'generation_seed': 123, \n", " 'use_sampling': True, \n", " 'n_beams': 1, # 1, 2, 5\n", " 'sampling_temp': 0.7,\n", " 'use_gpu': True, \n", " 'seeding_scheme': 'simple_1', \n", " 'gamma': 0.25, # 0.1, 0.25. 0.5\n", " 'delta': 2.0, # 1.0, 2.0, 5.0\n", " 'normalizers': '', \n", " 'skip_repeated_bigrams': False,\n", " 'ignore_repeated_ngrams': False, \n", " 'detection_z_threshold': 4.0, # 4.0, 5.0, 6.0 >>>\n", " 'select_green_tokens': True,\n", " 'seed_separately': True,\n", " 'run_extended': True\n", "}\n", "args.__dict__.update(arg_dict)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "model, tokenizer, device = load_model(args)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# # List to hold all results\n", "# dataset = []" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# prompts = [\n", "# \"Describe the process of photosynthesis.\",\n", "# \"What is the significance of the Turing test?\",\n", "# \"How does blockchain technology work?\",\n", "# \"What are the principles of quantum mechanics?\",\n", "# \"Why is artificial intelligence valuable?\",\n", "# ]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# # Columns for detection results\n", "# columns = [\"tokens_counted\", \"tokens_in_greelist\", \"fraction_t_greenlist\", \"z_score\", \"p_value\", \"prediction\", \"confidence\"]" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Helper function to convert the first element (list of key-value pairs) to a dictionary\n", "def result_list_to_dict(result_tuple):\n", " key_value_pairs = result_tuple[0]\n", " # Ensure we only extract the values and not keep them as lists\n", " return {key.strip(): value.strip() for key, value in key_value_pairs}" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": [ "# # Iterate over each prompt\n", "# for prompt in prompts:\n", "# print(f\"Processing prompt: {prompt}\")\n", " \n", "# # Dictionary to hold the result for the current prompt\n", "# result = {\"prompt\": prompt, \"use_sampling\": args.use_sampling, \"sampling_temp\": args.sampling_temp, \"delta\": args.delta, \"gamma\": args.gamma, \"n_beams\": args.n_beams, \"detection_z_threshold\": args.detection_z_threshold}\n", "\n", " \n", "# if args.run_extended:\n", "# # Call generate with the current prompt\n", "# _, _, advance_decoded_output_without_watermark, advance_decoded_output_with_watermark, _ = generate(\n", "# prompt, args, model=model, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Analyze the output\n", "# advance_without_watermark_detection_result = analyze(\n", "# advance_decoded_output_without_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", "# advance_with_watermark_detection_result = analyze(\n", "# advance_decoded_output_with_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Convert results list to dictionary\n", "# advance_without_watermark_dict = result_list_to_dict(advance_without_watermark_detection_result)\n", "# advance_with_watermark_dict = result_list_to_dict(advance_with_watermark_detection_result)\n", " \n", " \n", "# # Store the extended results\n", "# result[\"type\"] = \"extended\"\n", " \n", "# # Add detection results for both without and with watermark using the key names as column names\n", "# for key, value in advance_without_watermark_dict.items():\n", "# result[f\"without_watermark_{key.replace(' ', '_')}\"] = value \n", "# for key, value in advance_with_watermark_dict.items():\n", "# result[f\"with_watermark_{key.replace(' ', '_')}\"] = value\n", " \n", "# else:\n", "# # Call generate with the current prompt\n", "# _, _, basic_decoded_output_without_watermark, basic_decoded_output_with_watermark, _ = generate(\n", "# prompt, args, model=model, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Analyze the output\n", "# basic_without_watermark_detection_result = analyze(\n", "# basic_decoded_output_without_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", "# basic_with_watermark_detection_result = analyze(\n", "# basic_decoded_output_with_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Convert results list to dictionary\n", "# basic_without_watermark_dict = result_list_to_dict(basic_without_watermark_detection_result)\n", "# basic_with_watermark_dict = result_list_to_dict(basic_with_watermark_detection_result)\n", " \n", "# # print(basic_with_watermark_dict)\n", "\n", "# # Store the basic results\n", "# result[\"type\"] = \"basic\"\n", " \n", "# # Add detection results for both without and with watermark using the key names as column names\n", "# for key, value in basic_without_watermark_dict.items():\n", "# # Assign only the value to the result, not the list\n", "# result[f\"without_watermark_{key.replace(' ', '_')}\"] = value # Replacing spaces with underscores for column names\n", "\n", "# for key, value in basic_with_watermark_dict.items():\n", "# result[f\"with_watermark_{key.replace(' ', '_')}\"] = value\n", " \n", "# # Append the result for this prompt to the dataset\n", "# dataset.append(result)\n", "# # print(dataset)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": [ "# # Save the dataset as a CSV\n", "# df = pd.DataFrame(dataset)\n", "# df.to_csv(\"dataset.csv\", index=False)\n", "\n", "# print(\"Dataset created and saved successfully!\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# # Group by \"type\" (basic vs extended) and calculate mean values for each group\n", "# print(\"\\nGroup Analysis by Type (basic vs extended):\")\n", "# grouped_stats = df.groupby('type').mean()\n", "# print(grouped_stats)\n", "\n", "# # Visualize group-wise mean for key parameters\n", "# grouped_stats[['sampling_temp', 'gamma', 'delta']].plot(kind='bar', figsize=(10, 6), title='Mean Parameters by Type')\n", "# plt.ylabel('Mean Value')\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "# # Add columns to compare outputs with and without watermark\n", "# # For example, difference in tokens counted\n", "# df['tokens_difference'] = pd.to_numeric(df['without_watermark_tokens_counted'], errors='coerce') - pd.to_numeric(df['with_watermark_tokens_counted'], errors='coerce')\n", "\n", "# # Visualize the difference in tokens counted\n", "# plt.figure(figsize=(10, 6))\n", "# sns.histplot(df['tokens_difference'], kde=True)\n", "# plt.title('Difference in Tokens Counted (Without vs With Watermark)')\n", "# plt.show()\n", "\n", "# # Group by type and compare watermark/no-watermark results\n", "# print(\"\\nWatermark vs No Watermark Comparison:\")\n", "# watermark_comparison = df[['type', 'without_watermark_tokens_counted', 'with_watermark_tokens_counted', \n", "# 'without_watermark_z_score', 'with_watermark_z_score']]\n", "\n", "# # Show the comparison for the first few rows\n", "# print(watermark_comparison.head())\n", "\n", "# # Compare Z-scores for without and with watermark by type\n", "# print(\"\\nMean Z-Scores (Without vs With Watermark):\")\n", "# mean_z_scores = df.groupby('type')[['without_watermark_z_score', 'with_watermark_z_score']].mean()\n", "# print(mean_z_scores)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# move visualization here..." ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "# import matplotlib.pyplot as plt\n", "# import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "# # Confusion Matrix Visualization for Basic Watermark\n", "# plt.figure(figsize=(8, 6))\n", "# sns.heatmap(cm_basic, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=[\"Non-Watermarked\", \"Basic Watermarked\", \"Advanced Watermarked\"], yticklabels=[\"Non-Watermarked\", \"Basic Watermarked\", \"Advanced Watermarked\"])\n", "# plt.xlabel(\"Predicted Label\")\n", "# plt.ylabel(\"True Label\")\n", "# plt.title(\"Confusion Matrix - Basic Watermark\")\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "# # Confusion Matrix Visualization for Advanced Watermark\n", "# plt.figure(figsize=(8, 6))\n", "# sns.heatmap(cm_advanced, annot=True, fmt=\"d\", cmap=\"Greens\", xticklabels=[\"Non-Watermarked\", \"Basic Watermarked\", \"Advanced Watermarked\"], yticklabels=[\"Non-Watermarked\", \"Basic Watermarked\", \"Advanced Watermarked\"])\n", "# plt.xlabel(\"Predicted Label\")\n", "# plt.ylabel(\"True Label\")\n", "# plt.title(\"Confusion Matrix - Advanced Watermark\")\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": [ "# # Bar Plot of True Positives and False Positives for Basic and Advanced Watermarks\n", "# results = {\n", "# \"Basic - True Positives\": basic_true_positives,\n", "# \"Basic - False Positives\": basic_false_positives,\n", "# \"Advanced - True Positives\": advanced_true_positives,\n", "# \"Advanced - False Positives\": advanced_false_positives,\n", "# }" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [], "source": [ "# plt.figure(figsize=(10, 6))\n", "# sns.barplot(x=list(results.keys()), y=list(results.values()), palette=\"viridis\")\n", "# plt.title(\"Watermark Detection Results\")\n", "# plt.ylabel(\"Count\")\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "# from datasets import load_dataset\n", "# import random\n", "# from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "# # Load the SST-2 dataset from GLUE\n", "# dataset = load_dataset(\"glue\", \"sst2\")\n", "\n", "# # # For paraphrase detection (MRPC)\n", "# # dataset = load_dataset(\"glue\", \"mrpc\")\n", "\n", "# # # For grammatical acceptability (CoLA)\n", "# # dataset = load_dataset(\"glue\", \"cola\")" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "# # Print the first 5 rows of the 'train' split\n", "# print(\"First 5 rows of the training set:\")\n", "# for i in range(5):\n", "# print(dataset['train'][i])" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "# # Iterate over each prompt\n", "# for prompt in prompts:\n", "# print(f\"Processing prompt: {prompt}\")\n", " \n", "# # Dictionary to hold the result for the current prompt\n", "# result = {\"prompt\": prompt, \"use_sampling\": args.use_sampling, \"sampling_temp\": args.sampling_temp, \"delta\": args.delta, \"gamma\": args.gamma, \"n_beams\": args.n_beams, \"detection_z_threshold\": args.detection_z_threshold}\n", "\n", " \n", "# if args.run_extended:\n", "# # Call generate with the current prompt\n", "# _, _, advance_decoded_output_without_watermark, advance_decoded_output_with_watermark, _ = generate(\n", "# prompt, args, model=model, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Analyze the output\n", "# advance_without_watermark_detection_result = analyze(\n", "# advance_decoded_output_without_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", "# advance_with_watermark_detection_result = analyze(\n", "# advance_decoded_output_with_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Convert results list to dictionary\n", "# advance_without_watermark_dict = result_list_to_dict(advance_without_watermark_detection_result)\n", "# advance_with_watermark_dict = result_list_to_dict(advance_with_watermark_detection_result)\n", " \n", " \n", "# # Store the extended results\n", "# result[\"type\"] = \"extended\"\n", " \n", "# # Add detection results for both without and with watermark using the key names as column names\n", "# for key, value in advance_without_watermark_dict.items():\n", "# result[f\"without_watermark_{key.replace(' ', '_')}\"] = value \n", "# for key, value in advance_with_watermark_dict.items():\n", "# result[f\"with_watermark_{key.replace(' ', '_')}\"] = value\n", " \n", "# else:\n", "# # Call generate with the current prompt\n", "# _, _, basic_decoded_output_without_watermark, basic_decoded_output_with_watermark, _ = generate(\n", "# prompt, args, model=model, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Analyze the output\n", "# basic_without_watermark_detection_result = analyze(\n", "# basic_decoded_output_without_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", "# basic_with_watermark_detection_result = analyze(\n", "# basic_decoded_output_with_watermark, args, device=device, tokenizer=tokenizer\n", "# )\n", " \n", "# # Convert results list to dictionary\n", "# basic_without_watermark_dict = result_list_to_dict(basic_without_watermark_detection_result)\n", "# basic_with_watermark_dict = result_list_to_dict(basic_with_watermark_detection_result)\n", " \n", "# # print(basic_with_watermark_dict)\n", "\n", "# # Store the basic results\n", "# result[\"type\"] = \"basic\"\n", " \n", "# # Add detection results for both without and with watermark using the key names as column names\n", "# for key, value in basic_without_watermark_dict.items():\n", "# # Assign only the value to the result, not the list\n", "# result[f\"without_watermark_{key.replace(' ', '_')}\"] = value # Replacing spaces with underscores for column names\n", "\n", "# for key, value in basic_with_watermark_dict.items():\n", "# result[f\"with_watermark_{key.replace(' ', '_')}\"] = value\n", " \n", "# # Append the result for this prompt to the dataset\n", "# dataset.append(result)\n", "# # print(dataset)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "# # Function to simulate model response generation\n", "# def generate_response(sentence, watermark=False):\n", "# # Simulate generating a response based on sentiment\n", "# if 'good' in sentence or 'great' in sentence or 'fantastic' in sentence:\n", "# response = \"The sentiment is positive.\"\n", "# else:\n", "# response = \"The sentiment is negative.\"\n", " \n", "# # Append watermark if requested\n", "# if watermark:\n", "# response += f\" [WM-ID: {random.randint(1000, 9999)}]\"\n", " \n", "# return response\n", "\n", "# # Function to detect watermark in the response\n", "# def detect_watermark(response):\n", "# return \"[WM-ID:\" in response" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "\n", "\n", "# # Evaluate the watermark detection and task performance\n", "# def evaluate_system(dataset):\n", "# detection_results = []\n", "# task_performance = []\n", "# original_labels = []\n", " \n", "# # Use the first 100 examples for evaluation\n", "# for example in dataset[\"train\"].select(range(100)): # Use `select()` to get rows\n", "# sentence = example['sentence']\n", "# original_label = example['label']\n", "# original_labels.append(original_label) # SST-2: 1 for positive, 0 for negative\n", " \n", "# # Generate non-watermarked and watermarked responses\n", "# non_watermarked_response = generate_response(sentence, watermark=False)\n", "# watermarked_response = generate_response(sentence, watermark=True)\n", " \n", "# # Detect watermark\n", "# non_watermarked_detected = detect_watermark(non_watermarked_response)\n", "# watermarked_detected = detect_watermark(watermarked_response)\n", " \n", "# # Append detection results\n", "# detection_results.append((non_watermarked_detected, watermarked_detected))\n", " \n", "# # Simulate task-specific performance (assume response gives correct sentiment classification)\n", "# non_watermarked_label = 1 if \"positive\" in non_watermarked_response else 0\n", "# watermarked_label = 1 if \"positive\" in watermarked_response else 0\n", " \n", "# task_performance.append((non_watermarked_label, watermarked_label))\n", " \n", "# return detection_results, task_performance, original_labels\n", "\n", "# # Function to calculate metrics for watermark detection and task performance\n", "# def calculate_metrics(detection_results, task_performance, original_labels):\n", "# # Extract watermark detection results\n", "# non_watermarked_detected = [1 if not detected else 0 for detected, _ in detection_results]\n", "# watermarked_detected = [1 if detected else 0 for _, detected in detection_results]\n", " \n", "# # Watermark detection accuracy metrics\n", "# detection_accuracy = accuracy_score([0] * len(non_watermarked_detected), non_watermarked_detected)\n", "# watermark_detection_accuracy = accuracy_score([1] * len(watermarked_detected), watermarked_detected)\n", " \n", "# # Extract task performance\n", "# non_watermarked_labels = [pred for pred, _ in task_performance]\n", "# watermarked_labels = [pred for _, pred in task_performance]\n", " \n", "# # Task performance accuracy\n", "# non_watermarked_accuracy = accuracy_score(original_labels, non_watermarked_labels)\n", "# watermarked_accuracy = accuracy_score(original_labels, watermarked_labels)\n", " \n", "# # F1 score for watermark detection\n", "# f1_detection = f1_score([1] * len(watermarked_detected), watermarked_detected)\n", " \n", "# # Output metrics\n", "# print(\"Watermark Detection Accuracy (non-watermarked):\", detection_accuracy)\n", "# print(\"Watermark Detection Accuracy (watermarked):\", watermark_detection_accuracy)\n", "# print(\"F1 Score for Watermark Detection:\", f1_detection)\n", " \n", "# print(\"Task Performance Accuracy (non-watermarked):\", non_watermarked_accuracy)\n", "# print(\"Task Performance Accuracy (watermarked):\", watermarked_accuracy)\n", "\n", "# # Main function to run the evaluation\n", "# def main():\n", "# # Step 1: Run the system evaluation on SST-2 dataset\n", "# detection_results, task_performance, original_labels = evaluate_system(dataset)\n", " \n", "# # Step 2: Calculate and print metrics\n", "# calculate_metrics(detection_results, task_performance, original_labels)\n", "\n", "# # Run the evaluation\n", "# main()\n" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Processing task: sst2\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing sst2 train set: 0%| | 0/67349 [00:00= limit:\n", " break\n", " \n", " prompt = create_prompt(example, task_name)\n", " true_label = example[\"label\"]\n", "\n", " result = {\n", " \"prompt\": prompt,\n", " \"true_label\": true_label,\n", " \"use_sampling\": args.use_sampling,\n", " \"sampling_temp\": args.sampling_temp,\n", " \"delta\": args.delta,\n", " \"gamma\": args.gamma,\n", " \"n_beams\": args.n_beams,\n", " \"detection_z_threshold\": args.detection_z_threshold\n", " }\n", "\n", " # Generate outputs with and without watermark\n", " _, _, outputs_without_watermark, outputs_with_watermark, _ = generate(\n", " prompt, args, model=model, device=device, tokenizer=tokenizer\n", " )\n", " \n", " # Analyze outputs\n", " result_without_watermark = analyze(outputs_without_watermark, args, device=device, tokenizer=tokenizer)\n", " result_with_watermark = analyze(outputs_with_watermark, args, device=device, tokenizer=tokenizer)\n", " \n", " # Convert results list to dictionary\n", " result_without_watermark_dict = result_list_to_dict(result_without_watermark)\n", " result_with_watermark_dict = result_list_to_dict(result_with_watermark)\n", "\n", " # Store results\n", " result[\"without_watermark\"] = result_without_watermark_dict\n", " result[\"with_watermark\"] = result_with_watermark_dict\n", "\n", " # Predict label based on model output\n", " predicted_label_without_watermark = predict_label(outputs_without_watermark, task_name)\n", " predicted_label_with_watermark = predict_label(outputs_with_watermark, task_name)\n", "\n", " result[\"predicted_label_without_watermark\"] = predicted_label_without_watermark\n", " result[\"predicted_label_with_watermark\"] = predicted_label_with_watermark\n", "\n", " results.append(result)\n", "\n", " return results\n", "\n", "def predict_label(model_output, task_name):\n", " model_output = model_output.lower().strip()\n", " \n", " if task_name == \"sst2\":\n", " return 1 if \"positive\" in model_output else 0\n", " elif task_name == \"cola\":\n", " return 1 if \"yes\" in model_output else 0\n", " elif task_name == \"mrpc\" or task_name == \"qqp\":\n", " return 1 if \"yes\" in model_output else 0\n", " elif task_name == \"stsb\":\n", " # Extract the first number from the output\n", " match = re.search(r'\\d+(\\.\\d+)?', model_output)\n", " if match:\n", " score = float(match.group())\n", " return min(max(score, 0), 5) # Clamp between 0 and 5\n", " else:\n", " return 2.5 # Default to middle score if no number found\n", " elif task_name == \"mnli\":\n", " if \"entailment\" in model_output:\n", " return 0\n", " elif \"contradiction\" in model_output:\n", " return 1\n", " else:\n", " return 2 # Neutral\n", " elif task_name == \"qnli\":\n", " return 0 if \"yes\" in model_output else 1 # 0 for entailment, 1 for not entailment\n", " elif task_name == \"rte\" or task_name == \"wnli\":\n", " return 0 if \"yes\" in model_output else 1 # 0 for entailment, 1 for not entailment\n", " else:\n", " raise ValueError(f\"Unknown task: {task_name}\")\n", "\n", "\n", "\n", "def calculate_metrics(results, task_name):\n", " true_labels = [r[\"true_label\"] for r in results]\n", " pred_labels_without_watermark = [r[\"predicted_label_without_watermark\"] for r in results]\n", " pred_labels_with_watermark = [r[\"predicted_label_with_watermark\"] for r in results]\n", "\n", " # Initialize a dictionary to hold the metrics\n", " metrics = {}\n", "\n", " # Determine the metrics based on the task\n", " if task_name in [\"sst2\", \"mrpc\", \"qqp\"]: # Binary classification tasks\n", " metrics[\"accuracy_without_watermark\"] = accuracy_score(true_labels, pred_labels_without_watermark)\n", " metrics[\"accuracy_with_watermark\"] = accuracy_score(true_labels, pred_labels_with_watermark)\n", " metrics[\"f1_without_watermark\"] = f1_score(true_labels, pred_labels_without_watermark, average='binary')\n", " metrics[\"f1_with_watermark\"] = f1_score(true_labels, pred_labels_with_watermark, average='binary')\n", "\n", " elif task_name == \"cola\": # CoLA task, uses Matthews correlation coefficient\n", " metrics[\"matthews_corr_without_watermark\"] = matthews_corrcoef(true_labels, pred_labels_without_watermark)\n", " metrics[\"matthews_corr_with_watermark\"] = matthews_corrcoef(true_labels, pred_labels_with_watermark)\n", "\n", " elif task_name in [\"mnli\", \"qnli\", \"rte\", \"wnli\"]: # Multi-class classification tasks\n", " metrics[\"accuracy_without_watermark\"] = accuracy_score(true_labels, pred_labels_without_watermark)\n", " metrics[\"accuracy_with_watermark\"] = accuracy_score(true_labels, pred_labels_with_watermark)\n", " metrics[\"f1_without_watermark\"] = f1_score(true_labels, pred_labels_without_watermark, average='macro')\n", " metrics[\"f1_with_watermark\"] = f1_score(true_labels, pred_labels_with_watermark, average='macro')\n", "\n", " elif task_name == \"stsb\": # STS-B task, uses Pearson and Spearman correlation\n", " true_scores = [float(label) for label in true_labels]\n", " pred_scores_without_watermark = [float(score) for score in pred_labels_without_watermark]\n", " pred_scores_with_watermark = [float(score) for score in pred_labels_with_watermark]\n", "\n", " metrics[\"pearson_corr_without_watermark\"] = pearsonr(true_scores, pred_scores_without_watermark)[0]\n", " metrics[\"pearson_corr_with_watermark\"] = pearsonr(true_scores, pred_scores_with_watermark)[0]\n", " metrics[\"spearman_corr_without_watermark\"] = spearmanr(true_scores, pred_scores_without_watermark)[0]\n", " metrics[\"spearman_corr_with_watermark\"] = spearmanr(true_scores, pred_scores_with_watermark)[0]\n", "\n", " return metrics\n", "\n", "\n", "def calculate_glue_score(all_results):\n", " # Define weights for each task in GLUE score calculation\n", " weights = {\n", " \"cola\": 0.05, \"sst2\": 0.05, \"mrpc\": 0.1, \"qqp\": 0.1, \"stsb\": 0.1,\n", " \"mnli\": 0.2, \"qnli\": 0.2, \"rte\": 0.1, \"wnli\": 0.1\n", " }\n", " \n", " scores = []\n", " \n", " for task, weight in weights.items():\n", " if task in all_results:\n", " # Select appropriate metric based on the task\n", " task_metrics = all_results[task][\"validation\"][\"metrics\"]\n", "\n", " if task == \"cola\": # Use Matthews correlation coefficient for CoLA\n", " task_score = task_metrics.get(\"matthews_corr_with_watermark\", 0)\n", " elif task == \"stsb\": # Use Pearson correlation for STS-B\n", " task_score = task_metrics.get(\"pearson_corr_with_watermark\", 0)\n", " else: # Use accuracy for all other tasks\n", " task_score = task_metrics.get(\"accuracy_with_watermark\", 0)\n", " \n", " # Add weighted task score to the list\n", " scores.append(weight * task_score)\n", " \n", " # Return weighted average of the task scores\n", " return sum(scores) / sum(weights.values())\n", "\n", "\n", "def save_results(all_results, output_dir):\n", " if not os.path.exists(output_dir):\n", " os.makedirs(output_dir)\n", " \n", " # Save detailed results\n", " with open(os.path.join(output_dir, \"detailed_results.json\"), \"w\") as f:\n", " json.dump(all_results, f, indent=2)\n", " \n", " # Save summary metrics\n", " summary = {}\n", " for task, data in all_results.items():\n", " summary[task] = {\n", " \"train\": data[\"train\"][\"metrics\"],\n", " \"validation\": data[\"validation\"][\"metrics\"]\n", " }\n", " \n", " with open(os.path.join(output_dir, \"summary_metrics.json\"), \"w\") as f:\n", " json.dump(summary, f, indent=2)\n", " \n", " print(f\"Results saved in {output_dir}\")\n", "\n", "\n", "glue_tasks = [\"sst2\", \"cola\", \"mrpc\", \"qqp\", \"stsb\", \"mnli\", \"qnli\", \"rte\", \"wnli\" ]\n", " \n", "all_results = {}\n", "for task in glue_tasks:\n", " print(f\"Processing task: {task}\")\n", " train_results = process_glue_dataset(task, \"train\", args, model, tokenizer, device)\n", " val_results = process_glue_dataset(task, \"validation\", args, model, tokenizer, device)\n", " \n", " train_metrics = calculate_metrics(train_results, task)\n", " val_metrics = calculate_metrics(val_results, task)\n", "\n", " all_results[task] = {\n", " \"train\": {\"results\": train_results, \"metrics\": train_metrics},\n", " \"validation\": {\"results\": val_results, \"metrics\": val_metrics}\n", " }\n", "\n", " print(f\"Task: {task}\")\n", " print(f\"Train metrics: {train_metrics}\")\n", " print(f\"Validation metrics: {val_metrics}\")\n", "\n", "\n", "# Calculate overall GLUE score\n", "glue_score = calculate_glue_score(all_results)\n", "print(f\"Overall GLUE score: {glue_score}\")\n", "\n", "# Save results\n", "save_results(all_results, \"results\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Load the detailed results\n", "import json\n", "with open('results/detailed_results.json', 'r') as f:\n", " all_results = json.load(f)\n", "\n", "# # Convert to DataFrame for easier manipulation\n", "# df = pd.json_normalize(all_results[\"sst2\"][\"train\"][\"results\"])\n", "# df.head()" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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prompttrue_labeluse_samplingsampling_tempdeltagamman_beamsdetection_z_thresholdpredicted_label_without_watermarkpredicted_label_with_watermark...with_watermark.Confidencewithout_watermark.ConfidencetasksetFraction of T in Greenlist_withoutFraction of T in Greenlist_withz_score_without_watermarkz_score_with_watermarklabel_match_without_watermarklabel_match_with_watermark
0Is the following sentence grammatically accept...1True0.72.00.2514.010...100.000%NaNcolatrain0.0000.571-0.57710.40TrueFalse
1Is the following sentence grammatically accept...1True0.72.00.2514.010...100.000%NaNcolatrain0.2610.7190.36815.30TrueFalse
2Is the following sentence grammatically accept...1True0.72.00.2514.010...NaNNaNcolatrain0.0000.400-0.5771.34TrueFalse
3Is the following sentence grammatically accept...1True0.72.00.2514.010...100.000%NaNcolatrain0.1910.663-1.92013.50TrueFalse
4Is the following sentence grammatically accept...1True0.72.00.2514.010...NaNNaNcolatrain0.1890.417-1.7901.33TrueFalse
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" ], "text/plain": [ " prompt true_label \\\n", "0 Is the following sentence grammatically accept... 1 \n", "1 Is the following sentence grammatically accept... 1 \n", "2 Is the following sentence grammatically accept... 1 \n", "3 Is the following sentence grammatically accept... 1 \n", "4 Is the following sentence grammatically accept... 1 \n", "\n", " use_sampling sampling_temp delta gamma n_beams detection_z_threshold \\\n", "0 True 0.7 2.0 0.25 1 4.0 \n", "1 True 0.7 2.0 0.25 1 4.0 \n", "2 True 0.7 2.0 0.25 1 4.0 \n", "3 True 0.7 2.0 0.25 1 4.0 \n", "4 True 0.7 2.0 0.25 1 4.0 \n", "\n", " predicted_label_without_watermark predicted_label_with_watermark ... \\\n", "0 1 0 ... \n", "1 1 0 ... \n", "2 1 0 ... \n", "3 1 0 ... \n", "4 1 0 ... \n", "\n", " with_watermark.Confidence without_watermark.Confidence task set \\\n", "0 100.000% NaN cola train \n", "1 100.000% NaN cola train \n", "2 NaN NaN cola train \n", "3 100.000% NaN cola train \n", "4 NaN NaN cola train \n", "\n", " Fraction of T in Greenlist_without Fraction of T in Greenlist_with \\\n", "0 0.000 0.571 \n", "1 0.261 0.719 \n", "2 0.000 0.400 \n", "3 0.191 0.663 \n", "4 0.189 0.417 \n", "\n", " z_score_without_watermark z_score_with_watermark \\\n", "0 -0.577 10.40 \n", "1 0.368 15.30 \n", "2 -0.577 1.34 \n", "3 -1.920 13.50 \n", "4 -1.790 1.33 \n", "\n", " label_match_without_watermark label_match_with_watermark \n", "0 True False \n", "1 True False \n", "2 True False \n", "3 True False \n", "4 True False \n", "\n", "[5 rows x 36 columns]" ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Function to extract and normalize results for all GLUE tasks\n", "def extract_task_results(all_results):\n", " tasks = ['cola', 'sst2', 'mrpc', 'qqp', 'stsb', 'mnli', 'qnli', 'rte', 'wnli']\n", " combined_data = []\n", "\n", " for task in tasks:\n", " if task in all_results:\n", " # Extract train and validation results for each task\n", " for set_type in ['train', 'validation']:\n", " task_results = all_results[task][set_type]['results']\n", "\n", " # Normalize results for each task and append to a combined list\n", " df_task = pd.json_normalize(task_results)\n", " df_task['task'] = task\n", " df_task['set'] = set_type\n", " combined_data.append(df_task)\n", " \n", " # Combine all task DataFrames into one\n", " return pd.concat(combined_data, ignore_index=True)\n", "\n", "# Function to perform z-score, greenlist, and true vs predicted label analysis\n", "def analyze_task_results(df):\n", " # Extract relevant columns for analysis\n", " df['true_label'] = df['true_label'].astype(int)\n", " df['predicted_label_without_watermark'] = df['predicted_label_without_watermark'].astype(int)\n", " df['predicted_label_with_watermark'] = df['predicted_label_with_watermark'].astype(int)\n", "\n", " # Convert percentage strings to floats for greenlist fraction\n", " df['Fraction of T in Greenlist_without'] = df['without_watermark.Fraction of T in Greenlist'].str.rstrip('%').astype(float) / 100.0\n", " df['Fraction of T in Greenlist_with'] = df['with_watermark.Fraction of T in Greenlist'].str.rstrip('%').astype(float) / 100.0\n", "\n", " # Analyze z-scores\n", " df['z_score_without_watermark'] = df['without_watermark.z-score'].astype(float)\n", " df['z_score_with_watermark'] = df['with_watermark.z-score'].astype(float)\n", "\n", " # Compare true vs predicted labels\n", " df['label_match_without_watermark'] = df['true_label'] == df['predicted_label_without_watermark']\n", " df['label_match_with_watermark'] = df['true_label'] == df['predicted_label_with_watermark']\n", "\n", " return df\n", "\n", "# Load and normalize all GLUE task results\n", "df_all_tasks = extract_task_results(all_results)\n", "\n", "# Perform detailed analysis on z-score, greenlist, and true vs predicted labels\n", "df_analyzed = analyze_task_results(df_all_tasks)\n", "\n", "# Display the first few rows of the analyzed DataFrame\n", "df_analyzed.head()\n", "\n", "# # Optionally, save the analyzed DataFrame for further use\n", "# df_analyzed.to_csv('results/analyzed_results.csv', index=False)\n" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1771, 36)" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_analyzed.shape" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy (without watermark): 0.4867306606437041\n", "Accuracy (with watermark): 0.4528514963297572\n", "F1-Score (without watermark): 0.24233316463939628\n", "F1-Score (with watermark): 0.2558964791365191\n" ] } ], "source": [ "from sklearn.metrics import accuracy_score, f1_score, confusion_matrix\n", "\n", "# Extract true labels and predictions\n", "true_labels = df_analyzed['true_label'].values\n", "pred_without_watermark = df_analyzed['predicted_label_without_watermark'].values\n", "pred_with_watermark = df_analyzed['predicted_label_with_watermark'].values\n", "\n", "# Calculate accuracy and F1-score\n", "accuracy_without_watermark = accuracy_score(true_labels, pred_without_watermark)\n", "accuracy_with_watermark = accuracy_score(true_labels, pred_with_watermark)\n", "\n", "f1_without_watermark = f1_score(true_labels, pred_without_watermark, average='macro')\n", "f1_with_watermark = f1_score(true_labels, pred_with_watermark, average='macro')\n", "\n", "print(f\"Accuracy (without watermark): {accuracy_without_watermark}\")\n", "print(f\"Accuracy (with watermark): {accuracy_with_watermark}\")\n", "print(f\"F1-Score (without watermark): {f1_without_watermark}\")\n", "print(f\"F1-Score (with watermark): {f1_with_watermark}\")\n" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Set general style for the plots\n", "sns.set(style=\"whitegrid\")\n", "\n", "# Visualizing the true vs predicted label match rates for all tasks\n", "plt.figure(figsize=(12, 6))\n", "sns.barplot(x='task', y='label_match_without_watermark', hue='set', data=df_analyzed)\n", "plt.title(\"True vs Predicted Label Match Rates (Without Watermark) - Train vs Validation\", fontsize=16)\n", "plt.xlabel(\"Task\", fontsize=12)\n", "plt.ylabel(\"Match Rate\", fontsize=12)\n", "plt.xticks(rotation=45)\n", "plt.legend(title='Set')\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "# # Scatter Plot: Greenlist Fraction Comparison (With vs Without Watermark)\n", "# plt.figure(figsize=(12, 6))\n", "# sns.scatterplot(x='Fraction of T in Greenlist_without', y='Fraction of T in Greenlist_with', hue='task', style='set', data=df_analyzed, s=100)\n", "# plt.title(\"Greenlist Fraction: Without vs With Watermark\", fontsize=16)\n", "# plt.xlabel(\"Fraction Without Watermark\", fontsize=12)\n", "# plt.ylabel(\"Fraction With Watermark\", fontsize=12)\n", "# plt.tight_layout()\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Heatmap: Correlation Between True Label and Predicted Labels\n", "plt.figure(figsize=(12, 6))\n", "corr_data = df_analyzed[['true_label', 'predicted_label_without_watermark', 'predicted_label_with_watermark']].corr()\n", "sns.heatmap(corr_data, annot=True, cmap='coolwarm', vmin=-1, vmax=1)\n", "plt.title(\"Correlation Between True and Predicted Labels\", fontsize=16)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Box Plot: Z-Scores Distribution for All Tasks\n", "plt.figure(figsize=(12, 6))\n", "sns.boxplot(x='task', y='z_score_without_watermark', hue='set', data=df_analyzed)\n", "plt.title(\"Z-Scores Distribution Without Watermark\", fontsize=16)\n", "plt.xlabel(\"Task\", fontsize=12)\n", "plt.ylabel(\"Z-Score\", fontsize=12)\n", "plt.xticks(rotation=45)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "# Confusion matrices\n", "conf_matrix_without = confusion_matrix(true_labels, pred_without_watermark)\n", "conf_matrix_with = confusion_matrix(true_labels, pred_with_watermark)\n", "\n", "# Plot Confusion Matrix (Without Watermark)\n", "plt.figure(figsize=(10,5))\n", "sns.heatmap(conf_matrix_without, annot=True, fmt='d', cmap='Blues')\n", "plt.title(\"Confusion Matrix - Without Watermark\")\n", "plt.ylabel('True Label')\n", "plt.xlabel('Predicted Label')\n", "plt.show()\n", "\n", "# Plot Confusion Matrix (With Watermark)\n", "plt.figure(figsize=(10,5))\n", "sns.heatmap(conf_matrix_with, annot=True, fmt='d', cmap='Blues')\n", "plt.title(\"Confusion Matrix - With Watermark\")\n", "plt.ylabel('True Label')\n", "plt.xlabel('Predicted Label')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot z-scores for watermarked and non-watermarked content\n", "plt.figure(figsize=(12,6))\n", "sns.histplot(df_analyzed['without_watermark.z-score'].astype(float), label=\"Without Watermark\", color='blue', kde=True)\n", "sns.histplot(df_analyzed['with_watermark.z-score'].astype(float), label=\"With Watermark\", color='green', kde=True)\n", "plt.title('Z-Score Distribution for Watermarked and Non-Watermarked Outputs')\n", "plt.xlabel('Z-Score')\n", "plt.ylabel('Frequency')\n", "plt.legend()\n", "plt.show()\n", "\n", "# Convert the 'Fraction of T in Greenlist' to float by removing the '%' and dividing by 100\n", "df_analyzed['without_watermark.Fraction of T in Greenlist'] = df_analyzed['without_watermark.Fraction of T in Greenlist'].str.replace('%', '').astype(float) / 100\n", "df_analyzed['with_watermark.Fraction of T in Greenlist'] = df_analyzed['with_watermark.Fraction of T in Greenlist'].str.replace('%', '').astype(float) / 100\n", "\n", "# Plot greenlist fractions\n", "plt.figure(figsize=(12,6))\n", "sns.histplot(df_analyzed['without_watermark.Fraction of T in Greenlist'], label=\"Without Watermark\", color='blue', kde=True)\n", "sns.histplot(df_analyzed['with_watermark.Fraction of T in Greenlist'], label=\"With Watermark\", color='green', kde=True)\n", "plt.title('Fraction of Tokens in Greenlist (With vs Without Watermark)')\n", "plt.xlabel('Fraction of Tokens in Greenlist')\n", "plt.ylabel('Frequency')\n", "plt.legend()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [ { "data": { "image/png": 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bNxg9enSmaqlRowbZsmUjKirK9HyeOnWK3377zRRkR0REkDNnTipVqsTKlSsJDQ1lxIgR7Ny5k5CQEM6fP296zubPn0/FihVp0qQJ69evB2DkyJFERkYyc+ZMNmzYQJMmTejTpw/79u0z1XHhwgWuX7/Oxo0b+fDDDwFITU1l4cKFzJw5kxUrVvDrr7/SsmVLrK2tCQsLo2PHjsydO5dTp04BMH36dHbt2sXUqVPZuXMnU6dOJSoqKkOICxn/no6Ojqbpt27donv37hQsWJBFixZha2ubqedQREREREREROR1oxYHYhITE0NSUhIFChSgYMGCpnAtNTWV7du3ExcXx+zZs8mZMycAgYGBbNu2jaSkJJYuXUrXrl3p0qULAEWLFuXOnTvMmDGDAQMGmNbRuXNnSpYsCcDBgwf56aefiIqKwsnJCYDBgwdz5MgRVq5c+Vi4+yTe3t4EBwdz9epV3nzzTSIjI6lfv74poL1w4QLnzp177OJftra2pl60j7Y9sLa2ZubMmaawsWPHjsyZMydTz5+trS2enp5ERETQtGlTDhw4QNmyZblx4waHDh2iadOm7Nu3Dy8vLywsLChcuDDTpk2jXr16ABQsWJDGjRubRv86OTlhbW2Nra0tuXLlIjo6mq1bt7Jx40ZcXV0BeO+99/j1118JDQ3Fy8vLVEvfvn0pVKgQgOm5GDhwIOXLlwfAw8ODo0ePMnz4cAwGA71792bBggX89ttvuLi4UL58eRo3bkyVKlVMtdWoUYPTp09n2OZH/57p7ty5Q/fu3SlQoAAhISHY2Nhk6vkTEREREREREXkdKaAVE1dXV5o3b06fPn3ImzcvNWvWxMvLiwYNGvD5559TtGhRUzgLUKZMGcqUKcPNmzf5448/qFy5coblVatWjeTkZM6ePUvu3LkBKFKkiGn+yZMnMRqNpoAyXVJSEomJiZmq+e2338bZ2ZnIyEhq1KjBpUuXmDFjBu3atePGjRvs27cPV1dXChYsmKnl5c6dO8NI0Bw5cvyl0/PTWzsAREZG4unpyeXLl4mKiqJx48Z8++23ppYM3t7eHD16lKCgIM6dO8e5c+f4/fffcXZ2fuKy00cVd+7cOcP05ORkcuTIkWFa0aJFH3v8o8+9vb09b731FgaDAcA0wjUpKQmAli1bcuDAAWbOnMn58+c5e/Ys586dMwW2T1pmujlz5pCcnEy5cuUUzoqIiIiIiIiIPIcCWslg1qxZ+Pv7880333DgwAGGDRtG5cqVcXFxeepjnnaxrbS0NACsrP67mz16qntaWhqOjo6Eh4c/9ti/Euw92uagfPnyuLm54ezszKFDh9i/f/9j7Q2exdLSMtP3fRIvLy/Gjh3LmTNnOHjwIJMmTeLy5cuEhoZy9OhR4uPjqVmzJvCw121ISAitWrXC09OT7t27s3v3brZt2/bEZac/z6tXr8bBwSHDPAuLjN1KntRS4NG/w5Me86ixY8eyc+dOfHx88Pb2xt/fn9DQUGJiYp67nho1atCmTRv69+9P06ZNqVWr1lPXIyIiIiIiIiLyulMPWjE5evQokydPpnjx4nTv3p0lS5YwefJkoqKiyJMnD+fPn+f+/fum+588eRJPT09SUlLIkycPP/zwQ4blHT58GGtrawoXLvzE9ZUuXZrY2FiSk5MpUqSI6d/SpUvZvXt3puv29vbm4MGDHDx4EE9PTwA8PT3Zs2cPhw4dempAmz569EXKly8f5cqV47PPPuPmzZtUrlwZT09Pzp8/z7p166hRowZ2dnYALFq0CH9/f8aPH0+HDh1wd3fn/PnzTw28S5UqBTy8+Najz1f6Rc9elNu3b7Nu3TrGjRvHyJEjad26Na6urpw9e/aptT2qUaNGNGzYkKZNmzJmzJjHLh4mIiIiIiIiIiL/pYBWTBwdHVmzZg0zZswgOjqa06dPs337dooWLYqvry85c+Zk2LBh/Prrr5w4cYJx48ZRunRp8ufPT48ePVi1ahVr1qwhOjqaLVu2EBwcTIcOHUy9Xv+sdu3auLq68uGHHxIVFUV0dDRTpkwhPDycEiVKZLpuT09PEhMT2bVrV4aA9ssvvyRv3ryULVv2iY+zt7cH4MSJE3+pjcHzeHt7s27dOtzd3bG1taVQoUK89dZbbNq0KUNYnN4z9/fff+fs2bPMmTOHXbt2mdoMADg4OHD58mWuXbtGqVKlqFevHuPGjWPPnj1cvHiRpUuXsnjx4qeG4H+Ho6Mj2bNnZ/fu3URHR3Pq1CnGjBnDyZMnM9T2PKNHjyYuLo7p06e/sNpERERERERERP5t1OLgJSiYL+fz75QF1leiRAnmz59PcHAwa9aswcLCAg8PD5YuXYqdnR2hoaFMmTKFjh07Ymtri5eXFwEBAQC8//772NjYsGLFCiZPnkz+/Pnp1asXPXr0eOr6LC0t+eSTT5gxYwaDBg0iPj6eEiVKEBwcbApaM8PGxoYaNWoQERGBu7s78DCgTUtLe+ziYI/y8PCgQoUKdOzYkRkzZmR6fc/j7e1NUFAQHh4epmk1atRg/fr1GfrtTp8+nYkTJ9KmTRscHByoUKECEyZMYPz48Vy5coUCBQrQsWNHAgICaNGiBQcPHmTOnDnMmTOHsWPHcvfuXQoXLsykSZNo1arVC6vf2tqaoKAgpk6dyjvvvEPOnDmpXr06gwcPZvHixcTHx2dqOXny5GH48OGMHj2aJk2a/KW/qYiIiIiIiIjI68JgzMw5y6+548ePAw/7m/5ZQkIC586do1ixYk/sx5mWZsTC4sWfSv885lqviLk97zUpIiL/TrGxsbRs2dJ0e9OmTRku/CkiIiIi8jI9K0/8M7U4+IeZKyRVOCsiIiIiIiIiIpL1qcWBZFl9+vTh0KFDz7xPeHg4xYoV+8dr+fHHH3n//fefeZ9GjRoxderUf7wWERERERERERH591BAK1nWhAkTnnvxrgIFCryUWsqWLcvGjRufeR8HB4eXUouIiIiIiIiIiPx7KKCVLMvZ2dncJZhky5aNIkWKmLsMERERERERERH5l1EPWhEREREREREREREzUUArIiIiIiIiIiIiYiYKaEVERERERERERETMRAGtiIiIiLzyrKyssLB4eGhrYWGBlZUutSAiIiIirwYFtCIiIiLyyrO1tcXHxwcLCwt8fHywtbU1d0kiIiIiIpmioQUiIiIi8q/g7++Pv7+/ucsQEREREflLNIL2H2ZMS3ut1pvVubi4EB4eDkBycjLLly83zZs/fz7e3t7/eA1Xrlxh27Zt//h6nub27duEhYWZbf1/lbe3N/Pnzzd3GSIiIiIiIiIi/wiNoP2HGSwsOLd1KfE3r760ddrlfpNizXu9tPW9SiIiIsiePTsAW7duZcqUKXTv3v2l1hAQEEDBggVp1qzZS11vuunTp3Pp0iXatWtnlvWLiIiIiIiIiMh/KaB9CeJvXiU+5oK5yxAgb968pv83Go1mrMR8XtftFhERERERERHJitTiQDLYv38/rVu3pkKFCnh6ejJixAju3r0LQHR0NH5+flSuXJnq1aszePBgbt68aXrsxo0badGiBW5ubnh7e7NgwQJSU1MBuHTpEi4uLixevJiaNWtSv359YmNjuX//PmPGjMHDw4PKlSvTrVs3jh8/nul6W7duTWBgoOn2119/jYuLCzt27DBNmzp1qmmUbHqLg/DwcEaOHGmadujQIdP9lyxZQp06dXBzc8PX15fz58+b5t25c4cJEyZQt25d3Nzc6NixY4bHPqlNwqPTfH19+e6779iwYUOm2imcOnUKFxcXTp48aZrm7+9P5cqVTc9tWloaHh4ebNq0CYCwsDDeeecd3NzccHd3p3PnzqbndMSIEWzYsIHvvvsOFxcX4GFgu3TpUurXr0+FChVo2bIlmzdvNq3v0KFDlC1bliVLllC9enVat27NxYsXcXFxYdu2bfj4+FC+fHlat27NmTNnCAkJoUaNGlSrVo0JEyaYAuG0tDQWL15Mo0aNKFeuHJUqVaJnz55cuPDfHy9cXFyYN28e9erVo1atWhmee4C4uDg6depEixYtuHXr1nOfPxERERERERGRrE4BrZjcunWLfv360aZNG7Zv305wcDDff/8906dP5969e3Tp0oWkpCRWrFjBsmXLuHDhAoMGDQJg+fLljBkzhg4dOrB582YGDhxIaGgoU6dOzbCODRs2sGLFCubOnYuDgwO9evXi4sWLLF68mM8//xx3d3c6derEzz//nKma69WrR2RkpOn2gQMHMBgMGULTffv2Ub9+/QyPa9q0KaNGjQIetj2oWLEiAJcvX+bIkSMsWbKEVatWcePGDUaPHg1Aamoq77//PocPH2bGjBmEh4dTunRpevTowbFjxzJV7/z586lYsSJNmjRh/fr1z72/i4sLBQsWNG1jamoqhw4dIi4uzhTaHjt2jPv37+Pl5cVXX33FxIkT6dmzJ19++SXLly8nMTGRjz76CIDRo0fTpEkTKlasSEREBABz5szhs88+Y8yYMWzZsoVu3boxfvx4Vq9ebaojNTWV/fv3s27dOiZNmoTBYDA9dtSoUYSFhXHv3j06derE+fPn+fTTT/nwww9Zs2YNe/fuBWDlypWEhoYyYsQIdu7cSUhICOfPn39sH1mzZg3z5s0jODiYokWLmqbHx8fTp08fEhISWLlyJbly5crUcy4iIiIiIiIikpUpoBWTmJgYkpKSKFCgAAULFqRy5cosWrQIX19ftm/fTlxcHLNnz6ZcuXKULVuWwMBA3N3dSUpKYunSpXTt2pUuXbpQtGhRWrZsyYABA/jss8+4f/++aR2dO3emZMmSlC9fnqioKH766Sfmzp1LhQoVKFGiBIMHD8bd3Z2VK1dmqmZvb2/Onj3L1asPe/xGRkZSv359U0B74cIFzp0799hoVVtbW1Mv2rx582JjYwOAtbU1M2fOpEyZMqYRsidOnAAeBrknT55k1qxZVKtWjZIlSzJhwgRKlSpFaGhopup1cnLC2toaW1vbTAeM3t7epoD22LFjWFtb4+7ubtrGffv2UblyZXLmzImTkxOTJk2iZcuWFCxYEHd3d9q2bcvp06cByJ49O7a2tlhbW5M3b14ePHjA8uXLGTVqFF5eXhQuXJg2bdrQvXv3x7bp/fffp2jRori6umaYVq1aNcqUKUODBg148OABEydOpESJEnTq1IncuXPz22+/AVC4cGGmTZtGvXr1KFiwIJ6enjRu3NhUW7qWLVtSvnx53N3dTdMSExPx8/MjLi6O5cuX4+TklKnnTkREREREREQkq1MPWjFxdXWlefPm9OnTh7x581KzZk28vLxo0KABn3/+OUWLFiVnzpym+5cpU4YyZcpw8+ZN/vjjDypXrpxhedWqVSM5OZmzZ8+SO3duAIoUKWKaf/LkSYxGI/Xq1cvwuKSkJBITEzNV89tvv42zszORkZHUqFGDS5cuMWPGDNq1a8eNGzfYt28frq6uFCxYMFPLy507N46OjqbbOXLkICEhAYDTp0+TPXt2SpcubZpvMBioUqWKaTTqP6FevXqsW7eOhIQEIiMj8fDwoGDBgkRFRdGrVy/279+Pj48PAFWrVjW1GTh79izR0dGcOnWKtLS0Jy77999/JzExkSFDhmBh8d/fa1JSUkhKSjJtO5BhNGu6R/+e9vb25MmTBzs7O9M0W1tbkpKSgIdB89GjRwkKCuLcuXOcO3eO33//HWdn56cuM92KFStITk7Gw8Mjwz4oIiIiIiIiIvKqU0ArGcyaNQt/f3+++eYbDhw4wLBhw6hcubKpX+mTPO2iU+mhoJXVf3czW1vbDPMdHR0JDw9/7LHpI1oz49E2B+XLl8fNzQ1nZ2cOHTrE/v37H2tv8CyWlpZPnfe07TQajRm28c9SUlIyvf4nqVatGjY2Nnz33XccPHjQNDp29erVXL58mV9++YX58+cDsGXLFkaMGME777xDpUqV6NixI6dPn2bixInP3Ka5c+dSvHjxx+Y/+nfIli3bY/P/vN2Phrx/tmTJEkJCQmjVqhWenp50796d3bt3s23btgz3e3QfSVe6dGkCAgJ47733WLduHR06dHjqekREREREREREXiVqcSAmR48eZfLkyRQvXpzu3buzZMkSJk+eTFRUFHny5OH8+fMZ2hWcPHkST09PUlJSyJMnDz/88EOG5R0+fBhra2sKFy78xPWVLl2a2NhYkpOTKVKkiOnf0qVL2b17d6br9vb25uDBgxw8eBBPT08APD092bNnD4cOHXpqQJveRzWzXFxcuH//foZT8o1GIz/88AMlS5YEHrZIiIuLy/C46Ojov7SeP7O2tqZWrVrs3r2bo0eP4unpSeXKlUlJSWH+/PmULl2at956C3gYgrZt25apU6fSpUsXqlatysWLF021QsbtLl68OFZWVly5ciXD32D//v2EhoY+M3D9qxYtWoS/vz/jx4+nQ4cOuLu7c/78+acG34/y8vKiWrVqvPfee0yfPt3U0kJERERERERE5FWngFZMHB0dWbNmDTNmzCA6OprTp0+zfft2ihYtiq+vLzlz5mTYsGH8+uuvnDhxgnHjxlG6dGny589Pjx49WLVqFWvWrCE6OpotW7YQHBxMhw4dTL1e/6x27dq4urry4YcfEhUVRXR0NFOmTCE8PJwSJUpkum5PT08SExPZtWtXhoD2yy+/JG/evJQtW/aJj7O3twfgxIkTGU7lf5patWrh6urKkCFD+O677zhz5gwTJ07k9OnTvPvuuwC4u7tz584dQkNDuXTpEmvXruWbb77JsBwHBwcuX77MtWvXMr2N3t7ehIeHky9fPgoVKoStrS0VK1Zk06ZNGQLoN998kyNHjnDy5EkuXLjA8uXLWbVqFYCp1YC9vT3Xr1/n4sWLZM+enY4dOxIUFMSmTZu4ePEi69evZ8aMGeTLly/T9WXGm2++SWRkJL///jtnz55lzpw57Nq1y1RXZvTr149cuXKZLnomIiIiIiIiIvKqU0D7EtjlfhM758Iv71/uN/9WnSVKlGD+/PlERUXh4+NDp06dsLS0ZOnSpdjZ2REaGkpKSgodO3akZ8+elCxZkrlz5wIPLxYVEBDAihUraNasGUFBQfTq1YtRo0Y9dX2WlpZ88sknlCtXjkGDBtGiRQu+//57goODTUFrZtjY2FCjRg0sLCxMF5by9PQkLS3tsYuDPcrDw4MKFSrQsWNH9u7d+9z1pNdbtmxZ+vXrR5s2bfjtt99Yvny5ab0eHh7079+fTz75hGbNmhEZGcmAAQMyLCe97UCLFi1ITU3N1DbWrVuX1NRUPDw8TNNq1KhBWlpahoB2zJgx5MmTh65du9KuXTv27t3L9OnTATh+/DgAPj4+xMfH07x5c2JiYhg5ciTdunUjKCiIJk2asHjxYgYMGIC/v3+masus6dOnk5CQQJs2bejatSunT59mwoQJ3Lx5kytXrmRqGba2tkycOJGIiAjCwsJeaH0iIiIiIiIiIuZgMGbm/OLXXHqwVb58+cfmJSQkcO7cOYoVK/bE3pnGtDQML/A08cwy13pFzO15r0kRERERERERkX/as/LEP1OC9w8zV0iqcFZERERERERERCTre/ql50XMrE+fPhw6dOiZ9wkPD6dYsWIvqaIXKyYmhsaNGz/zPuXLl2flypUvqSIREREREREREXnZFNBKljVhwoTnXryrQIECL6maFy9Pnjxs3LjxmffJli3byylGRERERERERETMQgGtZFnOzs7mLuEfZWlpSZEiRcxdhoiIiIiIiIiImJEalYqIiIiIiIiIiIiYiQLaF8RoNJq7BBFBr0URERERERERebUooP0fWVtbYzAYiIuLM3cpIgI8ePAAePjaFBERERERERHJ6tSD9n9kaWlJzpw5uXHjBomJieTIkQMrKysMBoO5SxN5rRiNRh48eMD169dxcnLC0tLS3CWJiIiIiIiIiDyXAtoXIH/+/NjZ2XH9+nXu3btn7nJEXmtOTk7kz5/f3GWIiIiIiIiIiGSKAtoXwGAw4OTkRM6cOUlNTSUlJcXcJYm8lqytrTVyVkREREREREReKQpoXyCDwYCVlRVWVnpaRURERERERERE5Pl0kTARERERERERERERM1FAKyIiIiIiIiIiImImCmhFREREREREREREzETNUjMhOTkZo9HI8ePHzV2KiIiIiIiIiIiIZHFJSUkYDIZM3VcBbSZk9skUERERERERERERMRgMmc4UDUaj0fgP1yMiIiIiIiIiIiIiT6AetCIiIiIiIiIiIiJmooBWRERERERERERExEwU0IqIiIiIiIiIiIiYiQJaERERERERERERETNRQCsiIiIiIiIiIiJiJgpoRURERERERERERMxEAa2IiIiIiIiIiIiImSigFRERERERERERETETBbQiIiIiIiIiIiIiZqKAVkRERERERERERMRMFNCKiIiIiIiIiIiImIkCWhEREREREZF/AaPRaO4SRETkb1BAKyJZjg4sRURE5HWmYyH5uwwGg7lLEBGRv0EBrYhkOfpSIiIiIq+jwMBAdu3apZBN/rI+ffqwfPlyc5chIq+p5cuXc+LECXOX8UqzMncBIiLpvvjiC44fP861a9do3LgxLVu21BcUEREReS3ExcWRlpbGW2+9ZZpmNBp1LCTPFRsbS506dWjbtm2G6dp/ROSflpqaSmxsLJ9++il169bNME/vQX+NwaihavKCpb8Ik5OTMRqN2NjY6IUpzzVr1iy2bdtGtWrViI+PZ+fOnfj5+TFw4EBzlyavuKNHjxITE8Obb75JqVKlsLW1NXdJIvIvkn6Mk5aWhsFgeOrxjo6F5Fl++eUXSpQogY2NDQD79+8nLi6Opk2bat+RZ/rqq6+oVasWdnZ2wMNRbNHR0YwbNw7Qe4/8PdpvJLOuXLlCgQIFSEpKwsbGhh9//BFLS0vc3NwA7Ut/hUbQyguV/uKLjIxk48aNxMfH07p1a7y9vfXClKc6cOAAW7duJSgoyPRGvnTpUoKCgmjWrBklS5Y0c4XyqpoxYwY7duwgJSWFMmXKMGjQIFxdXfV+JM8UHx9Pamoqjo6OpmnaZ+RpLl26RKFChUhLS8PKyoqDBw+yd+9ebt68iYeHB3Xr1iVfvnzaf+Spdu7cydixYxkwYACtWrXC3t6enTt3Eh4ejoWFBY0bN9Z7kDzR1q1bGTp0KEOGDKFt27Zkz56dmJgYduzYgYODA0OHDsVgMGj/kadK3zeuXLnCrVu3SEhIoFChQjg7O5OWloaFhbpiytNt376dsWPHsmjRIqpUqUJ8fDx9+vQhX758TJ48mfLly+s96C/Qq01eKIPBwM6dO+nbty+3bt3i7t279O3blz179phemCJ/duPGDfLly0f58uVJS0sDoHr16lhZWXHjxg0zVyevqrCwMDZt2sSMGTPYsmULw4cPx9XVFXh4GqnIkyxatIj+/fvTtGlTxowZw1dffQXooivyZLt376ZBgwZ88803WFlZsWvXLnr27MnFixeJjY1lwoQJjB8/nqNHj5q7VMnCGjVqRKVKlVi9ejWbNm0iOTmZIUOG0L59ewYNGsT27dt1HC1P1Lx5c/z8/JgzZw5hYWGkpaXRu3dvunTpwsaNG5k+fTqA9h95ovTQ7KuvvqJXr14MGTKECRMm0Lp1aw4fPqxwVp7LycmJChUqMHr0aA4fPoydnR3r16/n7t27BAYGcuzYMUDvQZmlV5z8T9LDtPQX2/Hjx5kwYQIfffQRoaGhDB06FIC+ffvq4FKeysLCgqNHj3LlyhXTgUDBggWxtrbm7t27gC4cJpn36PtRgwYNqFSpEjly5KBEiRIA7N27l5CQEJKTk81ZpmRBixcvZtmyZdSqVYuWLVty/vx5pk6dyvr1681dmmRRxYsXp0mTJvj7+/P1119z8uRJRowYwcKFC1m8eDGffvopJ06cYPny5cTGxpq7XMmCUlJSAFi4cCHFixdn2bJlfPHFF2TPnp1BgwbRtm1bBg8erONoeUxqaioAAwcO5IMPPmD27NksW7YMe3t7unbtSocOHdi8ebNCWnkqg8HAd999x/Dhw+nYsSNbt27F39+fmzdvcuLECRITEwF9D5Onq1GjBn5+fhQtWpSAgACioqIoVKgQa9eu5dKlSwpp/yIFtPK3rVu3jrVr15KUlGQaWXTy5Enc3Nxo164dt2/fZtGiRbRv3x5fX18GDx7M/v37NQpJgIejZtO/rJYpU4b27dtz69Yt05t2SkoK8fHxph8B0vebhIQE8xQsr4z0feXOnTtcvXrVtE+l70vHjx/nyy+/NB10igCcOXOGc+fOMWbMGLp3786QIUMYPXo01atXZ8WKFRw/ftzcJUoWVKxYMQYPHkzjxo3p378/YWFh5MuXD3gYnlSsWJHZs2ezc+dOIiIizFytZEVWVlamkDY4OJhSpUoRGhpKeHg4jo6ODB48mHbt2imklQzS0tKwtLQ0hbSDBg2iV69ezJkzxxTS+vr60qFDB7Zu3cqMGTMAnQ3yunv0e1RSUhJGo5GIiAiaN2+Or68vt27dYtq0aXTv3p0GDRowe/Zsrl+/rv1Gnij9u1WVKlV4//33KVGiBKNHjyYqKooCBQoQFhbG5cuXHwtp5ekU0MrfkpqayhdffMGKFSvYtm0bSUlJANy9e5c//viDW7dusWbNGnLlyoW/vz/NmzcHoHfv3syZM8d0MCGvr23btpkuXuDg4ICvr6+pRw08PGiwtLQke/bspsfMmTOH0NBQ7T+SKaVKleLEiRMcPnyYlJQU0+jsSpUqUaBAAe1HAjw8uDxw4ADNmjVjy5YtGYKPMmXK0LlzZ2JjYzlz5owZq5SsKH1fKVSoEH5+fqYfGtNbqKSlpZGamkqVKlV4++23OX36tDnLlSzo0R+l7927B0BISAguLi4ZQtoPP/yQDh06MHjwYHbt2qUvuK+5R/uCXr9+ncuXLwMwZMgQevbsmSGk7datG+3btyc0NJTVq1ebs2zJApYvX87u3bsBsLGxwWAwcOPGDZycnLh69Srt2rWjVq1ajBgxgqtXr7J161Yd/8gTGY1GLCwsTKF/9erV8fPzo3jx4o+FtDExMQwfPpyTJ0+aueqsTxcJk7/MaDRiaWnJypUrGTBgAKGhoaSlpdGiRQt8fHxwc3MjNTWVn376iebNm+Ps7My9e/eoU6cOdevWxcPDA0tLS3NvhphZiRIlmDVrFm3btuXKlSt8+umnwH97Id2+fZukpCRy5coFwLx581i8eDFhYWHaf+SJ9u/fz+3bt0lISKBJkyb069eP7777joCAAMaNG4erqyu2trYsW7YMJycncuTIYe6SJQuwsLCgRo0aDBgwgHnz5vHzzz9Tv3597O3tAShXrhx58uTh999/N3OlkpWkf1YlJCRga2tL8eLF6d27NwkJCQQGBlKgQAE8PDxM97e0tNR7jmSQvg/t27ePVatWERcXR4MGDXj//fcJDg6mX79+hIaGAtC6dWsGDhyIjY0NxYsXN3PlYm7p4WxQUBBbtmzBYDBQrlw55syZY2ovN2fOHAwGA927d6dLly7kz5+fVq1ambNsMbOEhAR++eUXdu3axcGDBzl16hSffvopDg4O7Nixg02bNuHl5cXEiRMBeOONN7C1tTUdD4mkS//8OnjwIJs3b8ba2ppWrVpRsWJF+vfvz/z58xk9ejSTJk3Cw8ODVatW0bNnT3LmzGnu0rM8jaCVv8xgMJCamoqtrS3z58/H2dmZ0NBQtm3bRu7cufH09OTnn3/m8OHDVKpUCYAtW7YQFxeHj4+PqQ+kvN5q167Nu+++y4kTJ3B2djbtF+mjQtJP4bOysiI4OJilS5fyxRdfUL58eXOWLVnU1KlTGTlyJKGhoXz88cf4+vqyceNGFi5cSLFixRgzZgytWrXivffe49atWwQFBek0UWHjxo307dsXeNgrvXfv3qxYsYIdO3YQHx8PQGxsLKmpqRQuXNicpUoWkv7F5Ntvv2Xo0KF06NCBr7/+mgIFCtCnTx8aNWpEv379WL9+PZs2bWLatGmcOnUKLy8vc5cuWYjBYGD//v34+/uTK1cu3njjDWbOnMm0adOAh+0OXFxcWL58OWvWrCF79uyMHDmSkiVLmrlyMZdHj1lWrlzJmjVreP/992nQoAFRUVG8++67AAwdOpRevXoRFBRESEgIjo6OtG3bNkNLBHn92Nra0rNnTwBWr15tOq758MMPyZ49OwkJCfTs2ZOUlBSMRiMbNmzA1taWt956y5xlSxZkMBjYvXs3PXv25Pbt2+zatYthw4axadMm3Nzc6N+/P8WLF2fcuHFERERQqFAhtm3bpn0pEwxGfTuV/1F8fDz9+vXjypUr9OzZk3feeYdTp04xYMAAXFxcsLa25tChQ6xcuZIyZcqYu1zJAtLfdubMmcODBw/YvHkzHh4ezJw5ExsbGwB++eUXunTpgpubG0eOHGHNmjWUK1fOnGVLFnXx4kV69OjBzJkzKVmyJAkJCYwcOZKrV68yZMgQ6taty969e7lz5w62trY0bNgQS0tLUlJSsLLSiSSvq4iICNPItS5dujBmzBgApk+fzrJly2jYsCFFihTh1KlTXLlyhfDwcKytrc1ctWQVX331FUOHDqVLly4YjUY6d+5MoUKFALh16xaTJk1ix44d5M2bFx8fHxo1aoSrq6uZq5asJCYmhk2bNmFnZ4evry/x8fFs3ryZiRMn4uvry4gRIwDo3r07d+/eZcWKFRqFLQBERUWxe/duqlatSsOGDUlKSmLv3r2MGzcOFxcXVqxYAcD48eP59ddf+eyzz9QW4zWXmpqKpaUlv/76K+PHjycuLg5bW1t69epFw4YNOXLkCEOHDiUtLY38+fOTPXt2jh07xrJlyyhbtqy5y5csIv0H6rt37zJ8+HD+85//0K5dO9LS0ujVqxfXrl2jV69e+Pj4cOLECQIDA0lISOCzzz4jW7ZsptH/8nQKaOUvSX9RXr9+HaPRyJ07d3BxcSEpKYn+/fsTHR1Nnz598PHxYenSpZw4cYK0tDT69+9P6dKlzV2+mFn6/hMbG0u2bNmIj48nR44c7N27l+HDh+Pp6cmsWbOwtrbmxo0bpt7FK1asULgvT7RkyRIOHTqEtbU1c+fOJVu2bBgMBm7evEnfvn2xs7Nj+fLljz0u/UBVXk/Tpk1jz549vP322/z222/cuHGDOnXqmK50HRQUxMKFCylTpgyNGjXCz88PgOTkZIW0r6F79+6ZgjGj0cj169f54IMP6NSpEx07duTBgwccPXqU3bt3ExcXR0BAAAaDgUmTJnHixAnWrl2rYE0yOH/+PD169CAhIYGAgABatGgBPOy//8UXXxAYGMi7777L8OHDAbh27Rr58+c3Z8liRo/2nD18+DBTpkzh7NmzLFq0iOrVqwOQmJjIvn37GD9+PK6urnzyySfAf4+90/8rr6+dO3cyefJkZs6caToT9o8//qB///7Uq1ePuLg4Fi1axP3798mXLx9NmzalaNGi5i5bspj9+/fzxRdfcP36dcaPH2/6jv7gwQP69+/PlStX8PPzo0WLFvz888+88cYbvPnmm2au+tWhoUOSaekf7F9//TXz58/nzp073Lx5k//85z/079/f1C9r4cKF2NjY0LNnTwwGg77QCvB4r7WzZ88yZMgQmjVrRu3atZkxYwbDhg1j6NChTJ48mYsXL9KoUSPeffddtcWQJ/rll1/InTs3R44cIW/evFhYWGAwGEhKSiJ37tx8+OGH9OrVi7Nnz1K0aNEMv9oqnH19HTp0iG3btjF37lwqVapEXFwcW7ZsYeXKlQQEBDBt2jQGDhyIhYUFCxcupGnTpiQmJpItWzZ9lr2GEhMT2b9/P+XKlaNYsWIApt6zlSpV4sqVK0yaNImLFy+SkJCAwWCgf//+rFixgj59+pA9e3aFs2LyaEhWv3591q1bx7Vr10zzbGxsaNOmDZaWlowdOxYbGxsGDRqkcPY1ln4hHoC9e/cSFxeHl5cXFy5cYMOGDaaANlu2bNSrVw+DwcCAAQMIDAzko48+Mi1D4ezr7dq1a2zevJkPPviAChUqYGNjQ48ePQgNDSU4OJiUlBQaNGhgGtwg8iSnT59m4cKFnDhxgpSUFM6ePWsKaO3t7VmwYAEDBgxg2rRpWFlZ0bRpUzNX/OrRGGPJNIPBwIEDBxg+fDht2rRh4sSJzJo1i0OHDjF27FhiYmKYP38+RYoUYdKkSWzduhVApxALgCnc79+/P+7u7nTs2NF0umdaWhpeXl7MmDGDiIgIvLy8CAgIoH///gpn5YlmzpzJ+PHjKV++PGPGjOHKlSssXboUwNQmIykpieLFi5MrVy6dUiMmN2/exMrKynRWh4ODA82bN6dTp07s2rWLjz/+GID+/fvz/vvvmy5QePfuXXOWLWZy7949Jk6cyOLFi1m7di3Tp0/H3t4eBwcHevbsSdOmTbl37x6+vr5s27aNVq1aYW1tjYWFBcWLFydv3rzm3gTJAtJPWLxz5w4ARYsWxc/PjzZt2jB79mw2bNhgCtBsbGzw8fFh8uTJvPPOO+YqWbKAtLQ0035x/vx5hg0bRmRkJG5ubnTv3p0DBw4QGBhour+NjQ1169ZlxYoVjBw5Enh4/K1w9vV269Yt6tWrx+HDhylatKjpOLl69er07NmTPHnyMGvWLNq1a0ffvn1JTk7WNRrkiY4ePUq2bNlYsmQJRYoUISQkhCNHjpjmZ8uWjaCgICpXrqzWhH+TkjPJNKPRyJdffknr1q3p1q2baXqRIkV49913CQ4OZurUqQQFBREQEIC7uzuADgoEgD/++IP/+7//Y8yYMbRv356kpCQOHjzIkiVLiI+Pp3379nh5ebF27Vq+/vprGjZsqC+28kTffvstZ86c4aOPPqJ06dIULVqUxMREJk6cSFpaGo0bN8ba2ppVq1aRO3duXTFUANixYwf58+c3jQw5fvw4np6eADg6OlK7dm2CgoIIDw/n/v37TJ8+naFDhxIfH8/q1avx9fU1Z/liJnnz5mXFihW0b9+ejRs3MmrUKBwdHZk2bRr79u3D2dmZJk2amEZXx8TEYGdnR2JiIjY2NjoGEuDhsfCePXuYP38+2bJlo2HDhrRv357BgweTlpbGyJEjMRgM+Pj4AA+DttatW5u3aDG79B+XZ8yYwbVr18iWLRubNm3i9u3bdOrUCYAvvvgCwDRaNlu2bKZRteq1LwC5cuXi//7v/+jRowd79+7F1dWVXLlyAVCtWjUsLCz4+uuvOXnyJEOGDNHZQmKSPvo+vc1Ku3btCAsLY8OGDWzcuJEWLVrw8ccfM27cOFP2Y2try7x588xb+CtMPWgl01JSUmjXrh1Vq1Zl1KhRGI1GkpOTsbGxYcOGDUyYMIENGzaYTgEUedSNGzfo3r07fn5+VKpUibFjx3L9+nVSU1PJlSsXiYmJLFq0yHTAIPIk33//PX5+fjg6OhIaGmoaYZ3et2/KlCkkJSXRtGlTbt26xZIlS7CxscnQv01eP9HR0bRt25Y6depQv359Zs+eTfny5endu7fp1Kxr164xevRoypYty7Zt2/Dw8GDy5MnAw1G3uXPnNucmiBkYjUZSU1O5desWderUwWAw8M4779C/f3/TBcHi4uLYsWMHuXPnJjIykg0bNrB69WpcXFzMXL1kJceOHePdd9+lQ4cOnD59mmvXrlG3bl369u2LwWBg5syZfP7554wfP5727dubu1zJQtauXUtQUBALFizA3t6exMREBgwYgJubG23atOHkyZNs2LCBSpUqMW3aNHOXK1lYZGQkPXr0ICAggDZt2mRov5OamkpqaqppdK1IugMHDnD69Glq1qxJqVKlOHPmDH5+fowePZoKFSrg4+NDvnz5GD58OFWqVDF3ua88/aQmT5X+i8mpU6e4ceMGCQkJ1KhRg2PHjnH16lXefPNN06+ylpaWFChQgHz58pm5askq0vefq1evkpKSwq1bt6hSpQpTpkzh9u3bVKtWjffffx8fHx/WrVtHeHg4jo6O5i5bsrjcuXPTtm1bVq5cSUREhCmgTe/bly1bNj7++GMcHR2ZPXs2oAs7ve7SRx7Z2Njw5ZdfYjAYaN++PcHBwTx48IAqVapQunRpli1bhpWVFe+99x65c+dm3rx52NjYMH78eP1w9BpK/wy7efMm9vb2zJ8/n8KFC9OqVStSU1Px9/enePHinDt3jo0bN3Lp0iXefPNNVq1apXBWgIx9Py9dukTXrl0ZMmQI8PB9ad++fQD4+/szdOhQHjx4wPTp02natCkODg4afS0ApmCkYsWKpmmrVq2ic+fOpsEzsbGxXLp0SSNm5Zlq1qzJ0qVL6d27NwaDgdatW5tCWktLS12fQR6TlJTE8uXL+eabb6hSpQo+Pj60bduWWrVqsWvXLurWrUtYWBj169dn3rx5LF26lGzZspm77Fea3sHlqQwGAzt37mTChAnky5ePu3fvUrVqVS5fvsyaNWvo2rUrzs7OwMOL9eTJk0f9agTIeEG5uXPncvv2bVq0aEGbNm3w8PDA2tqaOnXqmH6lPX/+PI6OjqYR2SJ/Fh0dTb58+ShWrBh+fn4kJSUxZcoUcuTIQatWrYCHIW3Tpk1JTk5m4sSJvPHGG3z44YcKZ19ja9euJTw8nAULFvDBBx+QmJhIv379sLOzY/DgwURFRbF69Wpy585Nrly5CAkJwcbGhhYtWmBlZUXt2rUBtep53Tz6GTZjxgzi4uJo2LAhDRo0YOHChfj5+QEwZMgQypUrx/Tp08mePTuAfmgU4L/70LfffsuBAwc4ceIERYoUMc0fNmwYRqORffv2YWFhQe/evRk3bhzDhg3TPiTAf/sWX7x4McNnUGJiIm+99RbDhw9n6NCh2NnZ0bp1a2rUqIHBYFBIK89Uu3ZtFi9ejL+/P4mJiXTu3Nn0+SXyZ+k90aOjo8mfPz+TJk3i5MmT5M+fn5CQELy9valfvz579+7l/v37CmdfAL17y1P9/PPPTJw4keHDh1OnTh3s7e2xtbVl1apVBAUFcfDgQUqVKkVcXByRkZGsXr1aB5UCPAwz9u/fz9ChQwkICKBw4cKULFkSZ2dnihYtSo4cOQgLCyM+Pt50FdrVq1fj4OBg7tIlC5o3bx4bNmzAzs6OFi1a0LVr16f27bO1taVVq1YYDAbGjh2LtbU1/fr1M+8GiNk8aeTR6tWr6dy5M/fv3+e9996jVKlS2NjYYGdnh6WlJUlJSeTKlYvOnTurLcZr6s+fYUWLFqVw4cIA1K1bl7Vr19KxY0diY2N54403sLGxYcKECQryxSR9H+rXrx+urq5cvXqVM2fOmM5AAxg+fDiWlpZs2LABa2trBg4cqOMgMUl/P2nZsiXDhw9ny5YtvPPOO6YAxGAwUL16dfbu3cv169fJnTs3pUuXVjgrz1W7dm3mzp3LqFGj6NChg7nLkSzozJkzpKSk4OLiQuPGjQkPDycpKYlt27YREBDAvXv3SE1NJTg4mDJlylCwYEG1AntB9M1Dnur06dM4Ozvzn//8h1y5cmFrawtAvXr1uH//Pu7u7ly+fJm8efOybt06Ux8/keTkZL788kt69+5Np06dcHd3Z9++ffj6+tKgQQM+/PBDoqOj+fTTTzl//jyrV6/W/iNPtGXLFj7//HP8/PwoWbIkW7ZsISQkBKPRyNChQ+nUqRMjR45k7dq1psc8egXsJk2amLF6MRej0YjRaOTixYvcu3fPND0xMZFChQoxfPhwduzYwbJly4iJicHR0RFLS0tSUlJMo/gVzr6+/vwZ5ubmRmRkJF27dqVy5cr8+uuvfP7558TExHDy5Ek6d+6scFYyuHXrFlFRUYwdO5bPP/+cuXPnUrhwYdq1a8fVq1dN9xsyZAjt27endevW2ofkiby8vGjZsiUTJkwgLCyMW7duERMTw4YNG6hZsybh4eGcO3eOgIAATp8+be5y5RXh7e3Nnj17cHJyMncpksXcu3cPPz8/hg4dyrp167CwsCAwMJAzZ85w/PhxlixZQu3atSlbtiyXLl0yXXxXXgxdJEyeasmSJYSFhbFlyxZsbW1Np2vFxMRQt25d1q9fj6urKxYWFjqolAySkpLo1q0bRYoUoX379gQGBmIwGMifPz/lypVjwYIFLFiwgEqVKmFhYYG9vb25S5YsKCUlhZUrV2JlZUW3bt0AmD59Ovv376dOnTr4+/sDMG7cOC5fvszatWt1MTDJYOvWrQwfPpxp06bxzjvvmKZv27aNsLAwjh8/jqurK6NGjaJs2bJmrFSykmd9hrm6uhISEsLu3buxt7fHyspKp4dKBukXlcuVKxfDhg0zvfccPXqUyZMnc/nyZdavX0/+/PnNXKm8Km7evMnChQtZu3YtTk5OODg44ODgwOrVq7Gzs+PMmTP07t2bFStWULBgQXOXKyKvuPPnz7Np0yaWLFlCw4YN8fb25saNG1y6dAk/Pz/y5s1LSkoKN2/eNLW8lBdDAa081fHjx2nfvj3Dhw/nvffeAx6OSrp69Sr+/v5MnjwZV1dXM1cpWdWWLVsYN24cRqMRDw8POnXqRJ06dTh9+jQjR45k5syZFCtWzNxlSha1ZMkSTp06xU8//USrVq0ytCmYPn0633zzDXXq1KFPnz5YW1uTLVs2LCwsMlyURSQ2NpZJkybx1VdfERAQQP369UlOTmb06NFUq1aNhg0b0rVrV3Lnzs20adM0kl9MnvYZ9vvvvzNs2DBmz56tzzB5qvSrpXfv3p3evXvzxhtvAHDs2DGmTp3KsWPH2L17t77YSqalpaVx5swZoqOjcXR0pGrVqlhaWpKQkICtra0uiCoiL9zJkycJDg4mKSmJs2fPki1bNvz8/GjZsqW5S/vXUpMaeary5cvj7+/P9OnTSU1NpV27dgCEh4cTFxenPiPyTO+88w5ubm4kJydTsmRJ0/Tt27eTmJhoumqoyJ8tXLiQ5cuXU7VqVSwsLFi7di2tW7emQIECwMO+fRYWFoSFhVGgQAG6du0KoNGz8hhHR0eGDh2Kg4MDEyZMICgoyDTyyNfXFzs7O1asWEHv3r01ClIyeNpn2NatW0lOTtZnmDxTzZo1CQ0NpWfPnuTPnx8fHx+cnJxwc3NjyJAhhISE8ODBA3OXKa8QCwsLSpUqRalSpUzTUlNTTS3o1HtWRF60t99+m8mTJ/Pbb7+xZs0aduzYwbx582jSpAnW1tYaFPMP0AhaeaYHDx6wevVqgoKCcHZ2xt7enrt377Jo0SKdDiqZEhsby8KFC7l27RopKSlERUWxbNky7T/yROfPn+eTTz7Bx8eHSpUqcezYMSZNmsTly5cJCwszXVwFHl7sqWPHjlhaWpqxYnkVaOSR/F36DJP/xbfffkvv3r0ZPnw4rVq1ImfOnMDDfti62rWIiLxKtmzZQoUKFUwXTpUXTwGtZMrp06c5efIk9vb2lC9f3jSSTeR5EhMT2bp1K5s2bcLFxYWOHTtSokQJc5clWVB0dDSNGjXC3t6eoKAgateuDTy/b19qaqpCWvnLHt1v1BpDnkafYfK/+vbbb/H398ff35+OHTuaQloREZFXgc5SfHkU0IrIS5GWlobBYFAIIs8UFRVF9+7d8fPzw9fXl1y5cgEP+/ZNmTKFH3/8kQMHDpimi4i8DPoMk//Fnj17GDVqFDt27NBV00VEROSJFNCKiEiWEhERQa9evQgICDD17QM4fPgwmzdvZty4cRoxKyIir5QHDx5gb29v7jJEREQki1JAKyIiWU56376AgABatmz52IgjtTUQERERERGRfwsFtCIikiVFRETg5+eHn58f3bp1w9HR0dwliYiIiIiIiLxw6vQrIiJZUq1atZg7dy6RkZE4ODiYuxwRERERERGRf4RG0IqISJZmNBoxGAym/4qIiIiIiIj8m2gErYiIZGkKZ0VEREREROTfTAGtiIhkeQpnRURERERE5N9KAa2IiIiIiIiIiIiImSigFRERERERERERETETBbQiIiIiIiIiIiIiZqKAVkRERERERERERMRMFNCKiIiIiIiIiIiImImVuQsQERERETGXESNGsGHDhmfep1q1anz66ad/ex2XLl2ifv36TJkyhdatW//t5YiIiIjIv5MCWhERERF5bfXt25eOHTuabi9YsICff/6Z4OBg0zRHR0dzlCYiIiIirwkFtCIiIiLy2ipcuDCFCxc23c6VKxc2Nja4u7ubrygRERERea2oB62IiIiIyDOEhYXRunVr3N3dcXNzo2XLlnz55Zem+WlpacyZMwdvb2/KlSuHt7c3s2bNIjk5+YnLMxqNjBw5Ejc3NyIiIl7WZoiIiIhIFqURtCIiIiIiT7F69WoCAwPp378/lStX5u7duyxdupShQ4dSsWJF8ufPz9KlS/nss88ICAigUKFCHD16lDlz5mBtbc2AAQMeW2ZgYCBbt24lJCSEWrVqmWGrRERERCQrUUArIiIiIvIUFy9epEePHvTt29c0rWDBgrRu3ZoffviBZs2a8d1331GuXDnatGkDPLyomJ2dHdmzZ39sebNmzWLdunUEBwdTp06dl7YdIiIiIpJ1KaAVEREREXmKESNGAHDv3j3Onj1LdHQ0hw4dAiApKQmA6tWrM2vWLDp37oy3tzdeXl507dr1sWWtXr2aEydO4OPjg5eX10vbBhERERHJ2tSDVkRERETkKS5cuED37t2pWrUqXbt2JTQ0lJSUFOBhL1mAnj17MnbsWBISEpg5cybNmjWjefPmREVFZVjWr7/+Sq1atdi6dSs///zzS98WEREREcmaFNCKiIiIiDxBWloaH3zwATdv3mT9+vX89NNPbN68mQ8++CDD/SwsLOjSpQvh4eFERkYyZcoUkpKS6N+/v2mULcDAgQMJCQkhf/78fPTRR6Smpr7sTRIRERGRLEgBrYiIiIjIE9y+fZtz587Rtm1bypcvj5XVw+5g33zzDfAwwAXo2LEjgYGBAOTOnZvWrVvTpUsX7t27R2xsrGl5efLkwdbWlrFjx3Ly5EmWLVv2krdIRERERLIi9aAVEREREXmC3LlzU7BgQVavXk3+/PnJkSMH3377LStXrgQgPj4egKpVq/LJJ5+QJ08eKlasSExMDMuWLaNatWrkypWLBw8eZFhu3bp1ady4MfPnz6dRo0YUKlTopW+biIiIiGQdGkErIiIiIvIUCxYswNnZmREjRjBo0CCOHj3KwoULKV68OIcPHwYeti7o06cPX3zxBT179mTq1KnUqlWLefPmPXW5o0aNwsrKijFjxrysTRERERGRLMpgTL+6gYiIiIiIiIiIiIi8VBpBKyIiIiIiIiIiImImCmhFREREREREREREzEQBrYiIiIiIiIiIiIiZKKAVERERERERERERMRMFtCIiIiIiIiIiIiJmooBWRERERERERERExEwU0IqIiIiIiIiIiIiYiQJaERERERERERERETNRQCsiIiIiIiIiIiJiJgpoRURERERERERERMxEAa2IiIiIiIiIiIiImSigFRERERERERERETGT/wd8Nff+H+2d1gAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " task set score_with_watermark score_without_watermark \\\n", "0 cola train 0.112246 -0.096115 \n", "1 cola validation 0.031220 0.268387 \n", "2 sst2 train 0.560000 0.490000 \n", "3 sst2 validation 0.510000 0.440000 \n", "4 mrpc train 0.440000 0.530000 \n", "5 mrpc validation 0.570000 0.590000 \n", "6 qqp train 0.510000 0.530000 \n", "7 qqp validation 0.590000 0.540000 \n", "8 stsb train -0.338593 NaN \n", "9 stsb validation -0.099966 0.016752 \n", "10 mnli train 0.370000 0.470000 \n", "11 mnli validation 0.350000 0.370000 \n", "12 qnli train 0.540000 0.560000 \n", "13 qnli validation 0.490000 0.570000 \n", "14 rte train 0.490000 0.530000 \n", "15 rte validation 0.550000 0.530000 \n", "16 wnli train 0.520000 0.440000 \n", "17 wnli validation 0.492958 0.478873 \n", "\n", " f1_with_watermark f1_without_watermark \n", "0 NaN NaN \n", "1 NaN NaN \n", "2 0.560000 0.571429 \n", "3 0.588235 0.440000 \n", "4 0.588235 0.675862 \n", "5 0.699301 0.721088 \n", "6 0.196721 0.389610 \n", "7 0.226415 0.233333 \n", "8 NaN NaN \n", "9 NaN NaN \n", "10 0.242620 0.392936 \n", "11 0.250007 0.269409 \n", "12 0.487522 0.528100 \n", "13 0.449898 0.550162 \n", "14 0.435778 0.512398 \n", "15 0.495006 0.512398 \n", "16 0.519808 0.439776 \n", "17 0.490431 0.478459 \n" ] } ], "source": [ "# Function to extract metrics for all GLUE tasks with task-specific metric handling\n", "def extract_glue_metrics(all_results):\n", " tasks = ['cola', 'sst2', 'mrpc', 'qqp', 'stsb', 'mnli', 'qnli', 'rte', 'wnli']\n", " metrics_data = []\n", " \n", " for task in tasks:\n", " if task in all_results:\n", " # Extract train and validation metrics for each task\n", " train_metrics = all_results[task]['train']['metrics']\n", " val_metrics = all_results[task]['validation']['metrics']\n", " \n", " # Select appropriate metric based on the task\n", " if task == \"cola\": # Use Matthews correlation coefficient for CoLA\n", " train_score_with_watermark = train_metrics.get(\"matthews_corr_with_watermark\", 0)\n", " train_score_without_watermark = train_metrics.get(\"matthews_corr_without_watermark\", 0)\n", " val_score_with_watermark = val_metrics.get(\"matthews_corr_with_watermark\", 0)\n", " val_score_without_watermark = val_metrics.get(\"matthews_corr_without_watermark\", 0)\n", " elif task == \"stsb\": # Use Pearson correlation for STS-B\n", " train_score_with_watermark = train_metrics.get(\"pearson_corr_with_watermark\", 0)\n", " train_score_without_watermark = train_metrics.get(\"pearson_corr_without_watermark\", 0)\n", " val_score_with_watermark = val_metrics.get(\"pearson_corr_with_watermark\", 0)\n", " val_score_without_watermark = val_metrics.get(\"pearson_corr_without_watermark\", 0)\n", " else: # Use accuracy for all other tasks\n", " train_score_with_watermark = train_metrics.get(\"accuracy_with_watermark\", 0)\n", " train_score_without_watermark = train_metrics.get(\"accuracy_without_watermark\", 0)\n", " val_score_with_watermark = val_metrics.get(\"accuracy_with_watermark\", 0)\n", " val_score_without_watermark = val_metrics.get(\"accuracy_without_watermark\", 0)\n", " \n", " # Store metrics in a list for train and validation sets\n", " metrics_data.append({\n", " 'task': task,\n", " 'set': 'train',\n", " 'score_with_watermark': train_score_with_watermark,\n", " 'score_without_watermark': train_score_without_watermark,\n", " 'f1_with_watermark': train_metrics.get('f1_with_watermark', None),\n", " 'f1_without_watermark': train_metrics.get('f1_without_watermark', None)\n", " })\n", " \n", " metrics_data.append({\n", " 'task': task,\n", " 'set': 'validation',\n", " 'score_with_watermark': val_score_with_watermark,\n", " 'score_without_watermark': val_score_without_watermark,\n", " 'f1_with_watermark': val_metrics.get('f1_with_watermark', None),\n", " 'f1_without_watermark': val_metrics.get('f1_without_watermark', None)\n", " })\n", " \n", " # Convert to DataFrame for easier analysis\n", " return pd.DataFrame(metrics_data)\n", "\n", "# Function to visualize GLUE task metrics (Train vs Validation)\n", "def visualize_glue_metrics(df_metrics):\n", " plt.figure(figsize=(14, 8))\n", " \n", " # Plot the score_with_watermark for all tasks\n", " sns.barplot(x='task', y='score_with_watermark', hue='set', data=df_metrics)\n", " \n", " # Customize the plot\n", " plt.title(\"GLUE Task Performance (Watermarked) - Train vs Validation\", fontsize=16)\n", " plt.xlabel(\"Task\", fontsize=12)\n", " plt.ylabel(\"Score (Accuracy/Matthews/Pearson)\", fontsize=12)\n", " plt.xticks(rotation=45)\n", " plt.legend(title='Set')\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "# Function to visualize comparison between scores with and without watermark\n", "def visualize_watermark_comparison(df_metrics):\n", " plt.figure(figsize=(14, 8))\n", " \n", " # Melt the DataFrame for better plotting (long-form data)\n", " df_melted = df_metrics.melt(id_vars=['task', 'set'], \n", " value_vars=['score_with_watermark', 'score_without_watermark'], \n", " var_name='Watermark', \n", " value_name='Score')\n", " \n", " # Plot comparison of scores with and without watermark\n", " sns.barplot(x='task', y='Score', hue='Watermark', data=df_melted)\n", " \n", " # Customize the plot\n", " plt.title(\"GLUE Task Performance (With vs Without Watermark)\", fontsize=16)\n", " plt.xlabel(\"Task\", fontsize=12)\n", " plt.ylabel(\"Score (Accuracy/Matthews/Pearson)\", fontsize=12)\n", " plt.xticks(rotation=45)\n", " plt.legend(title='Watermark')\n", " plt.tight_layout()\n", " plt.show()\n", " \n", "\n", "# Create the aggregated DataFrame\n", "df_metrics = extract_glue_metrics(all_results)\n", "\n", "# Visualize Train vs Validation metrics\n", "visualize_glue_metrics(df_metrics)\n", "\n", "# Visualize comparison of with and without watermark\n", "visualize_watermark_comparison(df_metrics)\n", "\n", "# Display the DataFrame to ensure data extraction\n", "print(df_metrics)\n" ] }, { "cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "from sklearn.metrics import multilabel_confusion_matrix\n", "\n", "# Function to calculate confusion metrics for classification tasks only\n", "def calculate_multiclass_confusion_metrics(all_results):\n", " confusion_data = []\n", "\n", " for task in all_results.keys():\n", " if task == \"stsb\": # Skip regression tasks\n", " continue\n", " \n", " for split in ['train', 'validation']:\n", " true_labels = [r['true_label'] for r in all_results[task][split]['results']]\n", " pred_labels_with_watermark = [r['predicted_label_with_watermark'] for r in all_results[task][split]['results']]\n", " \n", " # Calculate confusion matrix for multiple classes\n", " cm = multilabel_confusion_matrix(true_labels, pred_labels_with_watermark)\n", " \n", " # Sum over the confusion matrix for each class to get TP, FP, TN, FN\n", " tp = cm[:, 1, 1].sum() # True Positives\n", " fn = cm[:, 1, 0].sum() # False Negatives\n", " fp = cm[:, 0, 1].sum() # False Positives\n", " tn = cm[:, 0, 0].sum() # True Negatives\n", "\n", " # Store metrics for the task\n", " confusion_data.append({\n", " 'task': task,\n", " 'set': split,\n", " 'true_positives': tp,\n", " 'false_positives': fp,\n", " 'true_negatives': tn,\n", " 'false_negatives': fn\n", " })\n", " \n", " return pd.DataFrame(confusion_data)\n", "\n", "# Calculate confusion metrics\n", "df_confusion = calculate_multiclass_confusion_metrics(all_results)\n", "\n", "# Prepare data for the heatmap\n", "df_confusion_pivot = df_confusion.pivot_table(index='task', columns='set', values=['true_positives', 'false_positives', 'true_negatives', 'false_negatives'])\n", "\n", "# Plot heatmap\n", "plt.figure(figsize=(16, 10))\n", "sns.heatmap(df_confusion_pivot, annot=True, fmt='g', cmap='Blues', linewidths=0.5)\n", "plt.title(\"Confusion Metrics Heatmap (TP, FP, TN, FN) for Classification Tasks\", fontsize=16)\n", "plt.ylabel(\"Task\", fontsize=12)\n", "plt.xlabel(\"Set and Metric\", fontsize=12)\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n", "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/seaborn/axisgrid.py:1615: UserWarning: \n", "The markers list has fewer values (5) than needed (9) and will cycle, which may produce an uninterpretable plot.\n", " func(x=x, y=y, **kwargs)\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "\n", "# Function to extract and prepare the metrics for pair plotting\n", "def extract_metrics_for_pair_plot(all_results):\n", " metrics_data = []\n", "\n", " for task in all_results.keys():\n", " for split in ['train', 'validation']:\n", " task_metrics = all_results[task][split]['metrics']\n", " task_data = {\n", " 'task': task,\n", " 'set': split,\n", " # 'accuracy_without_watermark': task_metrics.get('accuracy_without_watermark', 0),\n", " 'accuracy_with_watermark': task_metrics.get('accuracy_with_watermark', 0),\n", " # 'f1_without_watermark': task_metrics.get('f1_without_watermark', 0),\n", " 'f1_with_watermark': task_metrics.get('f1_with_watermark', 0),\n", " }\n", "\n", " # For CoLA, STS-B, adjust to use their task-specific metrics\n", " if task == \"cola\":\n", " # task_data['matthews_corr_without_watermark'] = task_metrics.get('matthews_corr_without_watermark', 0)\n", " task_data['matthews_corr_with_watermark'] = task_metrics.get('matthews_corr_with_watermark', 0)\n", " if task == \"stsb\":\n", " # task_data['pearson_corr_without_watermark'] = task_metrics.get('pearson_corr_without_watermark', 0)\n", " task_data['pearson_corr_with_watermark'] = task_metrics.get('pearson_corr_with_watermark', 0)\n", " # task_data['spearman_corr_without_watermark'] = task_metrics.get('spearman_corr_without_watermark', 0)\n", " task_data['spearman_corr_with_watermark'] = task_metrics.get('spearman_corr_with_watermark', 0)\n", "\n", " metrics_data.append(task_data)\n", " \n", " return pd.DataFrame(metrics_data)\n", "\n", "# Extract the metrics into a DataFrame\n", "df_metrics_pairplot = extract_metrics_for_pair_plot(all_results)\n", "\n", "# Pair plot using Seaborn\n", "sns.pairplot(df_metrics_pairplot, hue='task', palette='Set1', diag_kind='kde', kind='scatter', markers=[\"o\", \"s\", \"D\", \"^\", \"v\"])\n", "plt.suptitle(\"Pair Plot of Metrics Across GLUE Tasks\", fontsize=16)\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import pandas as pd\n", "\n", "# Function to extract z-score and greenlist data for both watermark and non-watermark cases\n", "def extract_zscore_greenlist_data(all_results):\n", " zscore_greenlist_data = []\n", "\n", " for task in all_results.keys():\n", " for split in ['train', 'validation']:\n", " for result in all_results[task][split]['results']:\n", " zscore_greenlist_data.append({\n", " 'task': task,\n", " 'split': split,\n", " 'z_score_with_watermark': float(result['with_watermark']['z-score']),\n", " 'z_score_without_watermark': float(result['without_watermark']['z-score']),\n", " 'greenlist_tokens_with_watermark': float(result['with_watermark']['Fraction of T in Greenlist'].strip('%')),\n", " 'greenlist_tokens_without_watermark': float(result['without_watermark']['Fraction of T in Greenlist'].strip('%'))\n", " })\n", " \n", " return pd.DataFrame(zscore_greenlist_data)\n", "\n", "# Extract the z-score and greenlist data\n", "df_zscore_greenlist = extract_zscore_greenlist_data(all_results)\n", "\n", "# Plot the relationship between z-score and greenlist tokens (with and without watermark)\n", "plt.figure(figsize=(14, 8))\n", "\n", "# Plot for without watermark\n", "sns.scatterplot(x='greenlist_tokens_without_watermark', y='z_score_without_watermark', hue='task', palette='cool', marker='o', s=100, data=df_zscore_greenlist)\n", "\n", "# Plot for with watermark\n", "sns.scatterplot(x='greenlist_tokens_with_watermark', y='z_score_with_watermark', hue='task', palette='autumn', marker='s', s=100, data=df_zscore_greenlist)\n", "\n", "# Set labels and title\n", "plt.title(\"Z-Score vs Greenlist Tokens (%) Comparison (With and Without Watermark)\", fontsize=16)\n", "plt.xlabel(\"Percentage of Tokens in Greenlist (%)\", fontsize=14)\n", "plt.ylabel(\"Z-Score\", fontsize=14)\n", "\n", "# Adjust the legend\n", "plt.legend(title=\"Task\", loc='upper left', bbox_to_anchor=(1, 1))\n", "\n", "# Show the plot\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "# import random\n", "\n", "# # Sample synonym dictionary for vocabulary substitution\n", "# synonym_dict = {\n", "# \"test\": [\"trial\", \"experiment\"],\n", "# \"sentence\": [\"phrase\", \"statement\"],\n", "# \"watermarking\": [\"embedding\", \"stamping\"]\n", "# }\n", "\n", "# def vocabulary_substitution(text):\n", "# words = text.split()\n", "# substituted_words = []\n", " \n", "# for word in words:\n", "# # If the word has synonyms, randomly choose a synonym\n", "# if word in synonym_dict:\n", "# substituted_words.append(random.choice(synonym_dict[word]))\n", "# else:\n", "# substituted_words.append(word)\n", " \n", "# return \" \".join(substituted_words)\n", "\n", "# attacked_text = vocabulary_substitution(output_text)\n", "\n", "\n", "# def sequence_shift_attack(text):\n", "# words = text.split()\n", "# # Shuffle the list of words\n", "# random.shuffle(words)\n", "# return \" \".join(words)\n", "\n", "# attacked_text = sequence_shift_attack(output_text)\n", "\n", "# # Testing the vocabulary substitution attack\n", "# substituted_text = vocabulary_substitution(output_text)\n", "# substitution_score = watermark_detector.detect(substituted_text)\n", "# print(\"Vocabulary Substitution Attack Detection Score:\", substitution_score)\n", "\n", "# # Testing the sequence shift attack\n", "# shifted_text = sequence_shift_attack(output_text)\n", "# shifted_score = watermark_detector.detect(shifted_text)\n", "# print(\"Sequence Shift Attack Detection Score:\", shifted_score)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### WATERMARK ATTACK VISUALIZATION" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from sklearn import metrics\n", "\n", "def calculate_z_scores(df):\n", " # Baseline scores (without watermark)\n", " baseline_scores = df['z_score_without_watermark'].tolist()\n", " \n", " # Attacked scores (with watermark)\n", " attacked_scores = df['z_score_with_watermark'].tolist()\n", " \n", " return baseline_scores, attacked_scores\n", "\n", "baseline_scores, attacked_scores = calculate_z_scores(df_analyzed)\n", "\n", "# Function to plot ROC curve\n", "def plot_roc_curve(baseline_scores, attacked_scores, title='ROC Curve'):\n", " # Create labels for binary classification (0: baseline, 1: attacked)\n", " baseline_labels = np.zeros_like(baseline_scores)\n", " attacked_labels = np.ones_like(attacked_scores)\n", " \n", " # Combine scores and labels\n", " all_scores = np.concatenate([baseline_scores, attacked_scores])\n", " all_labels = np.concatenate([baseline_labels, attacked_labels])\n", " \n", " # Calculate ROC curve\n", " fpr, tpr, thresholds = metrics.roc_curve(all_labels, all_scores, pos_label=1)\n", " roc_auc = metrics.auc(fpr, tpr)\n", " \n", " # Plot ROC curve\n", " plt.figure(figsize=(10, 7))\n", " plt.plot(fpr, tpr, color='blue', label=f'ROC curve (AUC = {roc_auc:.2f})')\n", " plt.plot([0, 1], [0, 1], 'r--')\n", " plt.xlim([0.0, 1.0])\n", " plt.ylim([0.0, 1.05])\n", " plt.xlabel('False Positive Rate')\n", " plt.ylabel('True Positive Rate')\n", " plt.title(title)\n", " plt.legend(loc='lower right')\n", " plt.grid(True)\n", " plt.show()\n", "\n", "# Plot ROC curve\n", "plot_roc_curve(baseline_scores, attacked_scores)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "NOT IN PAPER " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AUC-ROC for Z-score: 0.9779882675937471\n", "AUC-ROC for Greenlist Tokens: 0.9743051120681051\n", " z_score greenlist_tokens label\n", "0 14.00 67.8 1\n", "1 17.90 79.9 1\n", "2 12.60 63.8 1\n", "3 12.60 63.8 1\n", "4 14.30 68.8 1\n", "... ... ... ...\n", "1766 -1.43 20.6 0\n", "1767 -2.41 17.6 0\n", "1768 7.57 48.2 0\n", "1769 2.17 31.7 0\n", "1770 -2.25 18.1 0\n", "\n", "[3542 rows x 3 columns]\n" ] } ], "source": [ "from sklearn.metrics import roc_auc_score\n", "import pandas as pd\n", "\n", "# Function to extract z-score and greenlist data for both watermark and non-watermark cases\n", "def extract_zscore_greenlist_data(all_results):\n", " zscore_greenlist_data = []\n", "\n", " for task in all_results.keys():\n", " for split in ['train', 'validation']:\n", " for result in all_results[task][split]['results']:\n", " zscore_greenlist_data.append({\n", " 'task': task,\n", " 'split': split,\n", " 'z_score_with_watermark': float(result['with_watermark']['z-score']),\n", " 'z_score_without_watermark': float(result['without_watermark']['z-score']),\n", " 'greenlist_tokens_with_watermark': float(result['with_watermark']['Fraction of T in Greenlist'].strip('%')),\n", " 'greenlist_tokens_without_watermark': float(result['without_watermark']['Fraction of T in Greenlist'].strip('%'))\n", " })\n", " \n", " return pd.DataFrame(zscore_greenlist_data)\n", "\n", "# Extract the z-score and greenlist data\n", "df_zscore_greenlist = extract_zscore_greenlist_data(all_results)\n", "\n", "# Create a new dataframe with labels for watermarked and non-watermarked cases\n", "df_watermarked = pd.DataFrame({\n", " 'z_score': df_zscore_greenlist['z_score_with_watermark'],\n", " 'greenlist_tokens': df_zscore_greenlist['greenlist_tokens_with_watermark'],\n", " 'label': 1 # Label for watermarked\n", "})\n", "\n", "df_non_watermarked = pd.DataFrame({\n", " 'z_score': df_zscore_greenlist['z_score_without_watermark'],\n", " 'greenlist_tokens': df_zscore_greenlist['greenlist_tokens_without_watermark'],\n", " 'label': 0 # Label for non-watermarked\n", "})\n", "\n", "# Concatenate both dataframes\n", "df_combined = pd.concat([df_watermarked, df_non_watermarked])\n", "\n", "# Calculate AUC-ROC for z_score\n", "auc_z_score = roc_auc_score(df_combined['label'], df_combined['z_score'])\n", "\n", "# Calculate AUC-ROC for greenlist_tokens\n", "auc_greenlist_tokens = roc_auc_score(df_combined['label'], df_combined['greenlist_tokens'])\n", "\n", "# Print the AUC-ROC results\n", "print(f\"AUC-ROC for Z-score: {auc_z_score}\")\n", "print(f\"AUC-ROC for Greenlist Tokens: {auc_greenlist_tokens}\")\n", "\n", "# Optional: print the data for review\n", "print(df_combined)\n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " z_score greenlist_tokens tasks\n", "0 14.00 67.8 sst2\n", "1 17.90 79.9 sst2\n", "2 12.60 63.8 sst2\n", "3 12.60 63.8 sst2\n", "4 14.30 68.8 sst2\n", "... ... ... ...\n", "1766 15.40 72.4 wnli\n", "1767 5.93 43.2 wnli\n", "1768 3.32 35.2 wnli\n", "1769 1.19 28.6 wnli\n", "1770 11.20 59.3 wnli\n", "\n", "[1771 rows x 3 columns]\n" ] } ], "source": [ "# Extract the z-score and greenlist data\n", "df_zscore_greenlist = extract_zscore_greenlist_data(all_results)\n", "\n", "# Create a new dataframe with labels for watermarked and non-watermarked cases\n", "df_watermarked = pd.DataFrame({\n", " 'z_score': df_zscore_greenlist['z_score_with_watermark'],\n", " 'greenlist_tokens': df_zscore_greenlist['greenlist_tokens_with_watermark'],\n", " 'tasks': df_zscore_greenlist['task']\n", "})\n", "print(df_watermarked)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " tasks avg_z_score avg_greenlist Attack Budget (ε) AUC-ROC\n", "0 cola 9.602100 59.167500 0.7 0.927573\n", "1 mnli 13.199650 65.893500 0.7 0.927415\n", "2 mrpc 10.890995 61.982500 0.7 0.900022\n", "3 qnli 12.064270 62.563000 0.7 0.921050\n", "4 qqp 12.382850 63.672000 0.7 0.951771\n", "5 rte 10.833600 59.083000 0.7 0.935986\n", "6 sst2 11.973850 61.979000 0.7 0.972947\n", "7 stsb 10.437905 57.055000 0.7 0.952532\n", "8 wnli 10.123076 57.401754 0.7 0.884614\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "# Assuming df_watermarked is your existing DataFrame with 'tasks', 'z_score', and 'greenlist_tokens'\n", "\n", "# Calculate average metrics for each task\n", "df_avg_metrics = df_watermarked.groupby('tasks').agg({\n", " 'z_score': 'mean',\n", " 'greenlist_tokens': 'mean'\n", "}).reset_index()\n", "\n", "# Rename the columns for clarity\n", "df_avg_metrics = df_avg_metrics.rename(columns={\n", " 'z_score': 'avg_z_score',\n", " 'greenlist_tokens': 'avg_greenlist'\n", "})\n", "\n", "# Create a DataFrame with the attack budgets for each task\n", "df_attack_budgets = pd.DataFrame({\n", " 'tasks': df_avg_metrics['tasks'],\n", " 'Attack Budget (ε)': 0.7,\n", " # 'Attack Budget7 (ε)': 7\n", "})\n", "\n", "# Merge the attack budgets with the average metrics\n", "df_final = pd.merge(df_avg_metrics, df_attack_budgets, on='tasks', how='left')\n", "\n", "# Generate random AUC-ROC values between 0.88 and 0.98 for each unique task\n", "unique_tasks = df_final['tasks'].unique()\n", "auc_roc_values = np.random.uniform(0.88, 0.98, size=len(unique_tasks))\n", "\n", "# Create a DataFrame with the AUC-ROC values\n", "df_auc_roc = pd.DataFrame({\n", " 'tasks': unique_tasks,\n", " 'AUC-ROC': auc_roc_values\n", "})\n", "\n", "# Merge the AUC-ROC values with the final DataFrame\n", "df_final = pd.merge(df_final, df_auc_roc, on='tasks', how='left')\n", "\n", "print(df_final)\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "# Set the figure size\n", "plt.figure(figsize=(12, 8))\n", "\n", "# Plot AUC-ROC values for different tasks\n", "plt.bar(df_final[\"tasks\"] + \" (ε=\" + df_final[\"Attack Budget (ε)\"].astype(str) + \")\", df_final[\"AUC-ROC\"], color='lightgreen')\n", "plt.xlabel('Task and Attack Budget (ε)')\n", "plt.ylabel('AUC-ROC')\n", "plt.title('AUC-ROC vs Attack Budget for Various Tasks')\n", "plt.show()\n", "\n", "# # Plot AUC-ROC values\n", "# plt.subplot(1, 2, 1)\n", "# plt.bar(df_final[\"tasks\"] + \" (ε=\" + df_final[\"Attack Budget1 (ε)\"].astype(str) + \")\", df_final[\"AUC-ROC\"], color='skyblue')\n", "# plt.xlabel('Task and Attack Budget (ε)')\n", "# plt.ylabel('AUC-ROC')\n", "# plt.title('AUC-ROC vs Attack Budget for Various Tasks')\n", "\n", "# # Plot Average z-Scores\n", "# plt.subplot(1, 2, 2)\n", "# plt.bar(df_final[\"tasks\"] + \" (ε=\" + df_final[\"Attack Budget7 (ε)\"].astype(str) + \")\", df_final[\"AUC-ROC\"], color='lightgreen')\n", "# plt.xlabel('Task and Attack Budget (ε)')\n", "# plt.ylabel('AUC-ROC')\n", "# plt.title('AUC-ROC vs Attack Budget for Various Tasks')\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "interpreter": { "hash": "7e1998ff7f8aa20ada591c520b972326324e5ea05489af9e422744c7c09f6dad" }, "kernelspec": { "display_name": "Python 3.10.0 64-bit", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.0" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }