我有以下代码：

import sentence_transformers
import multiprocessing
from tqdm import tqdm
from multiprocessing import Pool

embedding_model = sentence_transformers.SentenceTransformer('sentence-transformers/all-mpnet-base-v2')

data = [[100227, 7382501.0, 'view', 30065006, False, ''],
 [100227, 7382501.0, 'view', 57072062, True, ''],
 [100227, 7382501.0, 'view', 66405922, True, ''],
 [100227, 7382501.0, 'view', 5221475, False, ''],
 [100227, 7382501.0, 'view', 63283995, True, '']]

# Define the function to be executed in parallel
def process_data(chunk):
    results = []
    for row in chunk:
        print(row[0])
        work_id = row[1]
        mentioning_work_id = row[3]
        print(work_id)

        if work_id in df_text and mentioning_work_id in df_text:
            title1 = df_text[work_id]['title']
            title2 = df_text[mentioning_work_id]['title']
            embeddings_title1 = embedding_model.encode(title1,convert_to_numpy=True)
            embeddings_title2 = embedding_model.encode(title2,convert_to_numpy=True)
            
            similarity = np.matmul(embeddings_title1, embeddings_title2.T)
            
            results.append([row[0],row[1],row[2],row[3],row[4],similarity])
        else:
            continue
    return results

# Define the number of CPU cores to use
num_cores = multiprocessing.cpu_count()

# Split the data into chunks
chunk_size = len(data) // num_cores
# chunks = [data[i:i+chunk_size] for i in range(0, len(data), chunk_size)]

# Create a pool of worker processest
pool = multiprocessing.Pool(processes=num_cores)

results = []
with tqdm(total=len(data)) as pbar:
    for i, result_chunk in enumerate(pool.map(process_data, data)):
        # Update the progress bar
        pbar.update()
        # Add the results to the list
        results += result_chunk

# Concatenate the results
final_result = results

当我执行这段代码时，我得到以下错误：

---------------------------------------------------------------------------
RemoteTraceback                           Traceback (most recent call last)
RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/opt/conda/lib/python3.7/multiprocessing/pool.py", line 121, in worker
    result = (True, func(*args, **kwds))
  File "/opt/conda/lib/python3.7/multiprocessing/pool.py", line 44, in mapstar
    return list(map(*args))
  File "<ipython-input-4-3aab73406a3b>", line 18, in process_data
    print(row[0])
TypeError: 'int' object is not subscriptable
"""

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
<ipython-input-4-3aab73406a3b> in <module>
     46 results = []
     47 with tqdm(total=len(data)) as pbar:
---> 48     for i, result_chunk in enumerate(pool.map(process_data, data)):
     49         # Update the progress bar
     50         pbar.update()

/opt/conda/lib/python3.7/multiprocessing/pool.py in map(self, func, iterable, chunksize)
    266         in a list that is returned.
    267         '''
--> 268         return self._map_async(func, iterable, mapstar, chunksize).get()
    269 
    270     def starmap(self, func, iterable, chunksize=None):

/opt/conda/lib/python3.7/multiprocessing/pool.py in get(self, timeout)
    655             return self._value
    656         else:
--> 657             raise self._value
    658 
    659     def _set(self, i, obj):

TypeError: 'int' object is not subscriptable

如何在pool.map()中传递一个列表列表并使其并行处理？