在Tensorflow中从文件导入图形

import tensorflow as tf

# 读取保存的GraphDef文件
with tf.io.gfile.GFile('path/to/saved_model.pb', 'rb') as f:
    graph_def = tf.compat.v1.GraphDef()
    graph_def.ParseFromString(f.read())

# 将GraphDef导入到当前默认图中
tf.import_graph_def(graph_def, name='')

# 获取图中的操作和张量
graph = tf.compat.v1.get_default_graph()
tensor_output = graph.get_tensor_by_name('output_tensor_name:0')

import tensorflow as tf

# 加载SavedModel
loaded = tf.saved_model.load('path/to/saved_model')

# 获取签名函数
infer = loaded.signatures["serving_default"]

# 准备输入数据
input_data = tf.constant([[...]])

# 调用模型进行推理
output = infer(tf.constant(input_data))['output_tensor_name']