Question

我有这段代码可以预热模型。我得到saved_model.pb，但variables为空。

如何保存variables？

import tensorflow as tf
import os

SAVE_PATH = 'C:/work/'
MODEL_NAME = 'test'
VERSION = 1
SERVE_PATH = 'C:/work/out/{}/{}'.format(MODEL_NAME, VERSION)

checkpoint = tf.train.latest_checkpoint(SAVE_PATH)
print(checkpoint)
tf.reset_default_graph()

with tf.Session() as sess:
    # import the saved graph
    saver = tf.train.import_meta_graph(checkpoint + '.meta')

    # get the graph for this session
    graph = tf.get_default_graph()
    sess.run(tf.global_variables_initializer())
    # get the tensors that we need
    inputs = graph.get_tensor_by_name('ImageTensor:0')
    predictions = graph.get_tensor_by_name('SemanticPredictions:0')
    # create tensors info
    print(inputs,predictions)
    model_input = tf.saved_model.utils.build_tensor_info(inputs)
    model_output = tf.saved_model.utils.build_tensor_info(predictions)
    # build signature definition
    signature_definition = tf.saved_model.signature_def_utils.build_signature_def(
        inputs={'inputs': model_input},
        outputs={'outputs': model_output},
        method_name= tf.saved_model.signature_constants.PREDICT_METHOD_NAME)

    builder = tf.saved_model.builder.SavedModelBuilder(SERVE_PATH)
    print(tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY)
    builder.add_meta_graph_and_variables(
        sess, [tf.saved_model.tag_constants.SERVING],
        signature_def_map={
            tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
                signature_definition
        })
    # Save the model so we can serve it with a model server :)
    builder.save()

Tensorflow模型不是变量

0 个答案: