如何将pb文件转换为HDF5 格式 完整代码

以下是将pb文件转换为HDF5格式的完整代码：

import tensorflow as tf
import keras.backend as K
from keras.models import Sequential

def pb_to_h5(pb_file_path, h5_file_path):
    with tf.keras.backend.get_session() as sess:
        # Load the protobuf graph from the pb file
        with tf.gfile.GFile(pb_file_path, "rb") as f:
            graph_def = tf.GraphDef()
            graph_def.ParseFromString(f.read())
        
        # Import the graph_def into a new Graph and return it
        tf.import_graph_def(graph_def, name="")

        # Define a Keras model
        model = Sequential()
        model.add(tf.keras.layers.Lambda(lambda x: x, input_shape=(None,), dtype='string'))

        # Traverse the TF graph and add variables to the Keras model
        for node in graph_def.node:
            if node.op == 'Placeholder':
                continue
            if node.op == 'Const':
                tensor = tf.import_graph_def(graph_def,
                                             input_map={node.name: tf.zeros([1, 1])},
                                             return_elements=[node.name + ":0"])
                K.set_value(model.weights[-1], tensor[0])
            else:
                try:
                    layer = tf.keras.layers.deserialize({'class_name': node.op, 'config': {}},
                                                         custom_objects={})
                    layer.build([None] + [i.shape for i in layer.inputs])
                    layer.set_weights([K.get_value(sess.graph.get_tensor_by_name(n + ":0"))
                                       for n in node.input])
                    model.add(layer)
                except:
                    print('Could not add layer: ', node.op)

        # Save the Keras model as an HDF5 file
        model.save(h5_file_path)

# Example usage:
pb_file_path = "/path/to/your/model.pb"
h5_file_path = "/path/to/save/your/model.h5"
pb_to_h5(pb_file_path, h5_file_path)

使用时需将`pb_file_path`和`h5_file_path`替换为实际的文件路径。