如何在不使用GCP的情况下在Colab中加载用于TPU推断的数据？

import tensorflow as tf

# 检查是否支持TPU
try:
    tpu = tf.distribute.cluster_resolver.TPUClusterResolver()
    tf.config.experimental_connect_to_cluster(tpu)
    tf.tpu.experimental.initialize_tpu_system(tpu)
    strategy = tf.distribute.TPUStrategy(tpu)
except ValueError:
    strategy = tf.distribute.get_strategy()

from google.colab import drive
import pandas as pd

# 挂载Google Drive
drive.mount('/content/drive')

# 加载数据
data_path = '/content/drive/MyDrive/data.csv'
data = pd.read_csv(data_path)

# 示例：简单的数据预处理
data = data.dropna()
data = data.astype({'feature1': 'float32', 'feature2': 'int32'})

with strategy.scope():
    # 假设你已经有一个训练好的模型
    model = tf.keras.models.load_model('path_to_your_model')

# 进行推断
predictions = model.predict(data)