如何在TensorFlow中获取日志概率？

import tensorflow as tf
from tensorflow.python.platform import gfile

model_path = 'path_to_your_model'  # 模型文件路径
with tf.Session() as sess:
    with gfile.FastGFile(model_path, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        sess.graph.as_default()
        tf.import_graph_def(graph_def, name='')

input_tensor = sess.graph.get_tensor_by_name('input_tensor_name:0')  # 输入Tensor名称和索引
output_tensor = sess.graph.get_tensor_by_name('output_tensor_name:0')  # 输出Tensor名称和索引

logits = sess.graph.get_tensor_by_name('logits_tensor_name:0')  # 模型输出的logits Tensor名称和索引
probabilities = tf.nn.softmax(logits)  # 使用softmax函数将logits转换为概率

input_data = ...  # 输入数据
probabilities_val = sess.run(probabilities, feed_dict={input_tensor: input_data})