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import pandas as pd
import os
# --- Setup Paths ---
# Get the directory where this script is located (resources/)
script_dir = os.path.dirname(os.path.abspath(__file__))
# Define the datasets directory (resources/datasets/)
datasets_dir = os.path.join(script_dir, "datasets")
# [NEW] Create the directory if it doesn't exist (Safety check)
os.makedirs(datasets_dir, exist_ok=True)
input_file = os.path.join(datasets_dir, "routerbench_0shot.pkl")
full_csv_output = os.path.join(datasets_dir, "routerbench_0shot.csv")
train_output = os.path.join(datasets_dir, "routerbench_0shot_train.csv")
test_output = os.path.join(datasets_dir, "routerbench_0shot_test.csv")
test_sample_output = os.path.join(datasets_dir, "routerbench_0shot_test_500.csv")
try:
print(f"Loading dataset from: {input_file}")
# Load the pickle dataset
df = pd.read_pickle(input_file)
# --- 0. Convert Original to CSV ---
df.to_csv(full_csv_output, index=False)
print(f"Converted pickle to CSV: {full_csv_output}")
# --- 1. Randomly sample 1% for Train (No Replacement) ---
train_df = df.sample(frac=0.01, random_state=42)
train_df.to_csv(train_output, index=False)
print(f"Created 'train' split with {len(train_df)} rows.")
# --- 2. Remaining 99% for Test (Keep Original Ordering) ---
test_df = df.drop(train_df.index)
test_df.to_csv(test_output, index=False)
print(f"Created 'test' split with {len(test_df)} rows.")
# --- 3. Randomly sample 500 rows from the Test set ---
sample_size = 500
if len(test_df) < sample_size:
print(f"Warning: Test data only has {len(test_df)} rows. Sampling all of them.")
sample_size = len(test_df)
test_sample_df = test_df.sample(n=sample_size, random_state=42)
test_sample_df.to_csv(test_sample_output, index=False)
print(f"Created 'test_500' split with {len(test_sample_df)} rows.")
except FileNotFoundError:
print(f"Error: The file '{input_file}' was not found. Please run the download script first.")
except Exception as e:
print(f"An unexpected error occurred: {e}") |