如何将.pb文件(protobuf文件)转换成.weight文件使用？

pip install tensorflow

import tensorflow as tf
from tensorflow.python.saved_model import builder as saved_model_builder
from tensorflow.python.saved_model import utils
from tensorflow.python.saved_model import tag_constants, signature_constants
from tensorflow.python.saved_model.signature_def_utils_impl import build_signature_def, predict_signature_def

# 加载.pb文件
def load_graph(frozen_graph_filename):
    with tf.io.gfile.GFile(frozen_graph_filename, "rb") as f:
        graph_def = tf.compat.v1.GraphDef()
        graph_def.ParseFromString(f.read())
    return graph_def

frozen_graph_filename = 'your_model.pb'
graph_def = load_graph(frozen_graph_filename)

# 创建一个新的Graph
with tf.Graph().as_default() as graph:
    tf.import_graph_def(graph_def, name='')

# 获取输入和输出张量
input_tensor = graph.get_tensor_by_name('input:0')  # 替换为你的输入张量名称
output_tensor = graph.get_tensor_by_name('output:0')  # 替换为你的输出张量名称

# 创建SavedModelBuilder
export_dir = 'your_export_dir'
builder = saved_model_builder.SavedModelBuilder(export_dir)

# 创建SignatureDef
signature = predict_signature_def(
    inputs={'input': input_tensor},
    outputs={'output': output_tensor}
)

# 添加MetaGraphDef
with graph.as_default():
    builder.add_meta_graph_and_variables(
        sess=tf.compat.v1.Session(graph=graph),
        tags=[tag_constants.SERVING],
        signature_def_map={
            signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signature
        }
    )

# 保存SavedModel
builder.save()