目标: TFX -> TF Lite转换器->在移动/物联网设备上的部署模型
我目前正在学习Tensorflow扩展及其芝加哥出租车管道实例。管道已经运行(尽管经历了很多困难),Pusher组件已经发出了一个Tensorflow SavedModel文件(.pb)。
但是,这里遇到了一个新的问题:通过Tensorflow夜/1.13.1(尝试了这两种方法)和Python2.7.6,我可以用一些简单的Python代码(如和saved_model.loader.load )生成、保存和加载SavedModel(用于测试实用程序的mnist数字数据模型),但是在应用TFX Pusher发布的模型时经常会遇到错误,如下所示。
(也许我对TFX管道做错了什么?)
我使用的代码:
import tensorflow as tf
with tf.Session(graph=tf.Graph()) as sess:
tf.compat.v1.saved_model.loader.load(sess, ["serve"], "/home/tigerpaws/taxi/serving_model/taxi_simple/1553187887")#"/home/tigerpaws/saved_model_example/model")
graph=tf.get_default_graph()错误:
KeyError Traceback (most recent call last)
<ipython-input-11-a6978b82c3d2> in <module>()
1 with tf.Session(graph=tf.Graph()) as sess:
----> 2 tf.compat.v1.saved_model.loader.load(sess, ["serve"], "/home/tigerpaws/taxi/serving_model/taxi_simple/1553187887")#"/home/tigerpaws/saved_model_example/model")
3 graph=tf.get_default_graph()
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/util/deprecation.pyc in new_func(*args, **kwargs)
322 'in a future version' if date is None else ('after %s' % date),
323 instructions)
--> 324 return func(*args, **kwargs)
325 return tf_decorator.make_decorator(
326 func, new_func, 'deprecated',
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/saved_model/loader_impl.pyc in load(sess, tags, export_dir, import_scope, **saver_kwargs)
267 """
268 loader = SavedModelLoader(export_dir)
--> 269 return loader.load(sess, tags, import_scope, **saver_kwargs)
270
271
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/saved_model/loader_impl.pyc in load(self, sess, tags, import_scope, **saver_kwargs)
418 with sess.graph.as_default():
419 saver, _ = self.load_graph(sess.graph, tags, import_scope,
--> 420 **saver_kwargs)
421 self.restore_variables(sess, saver, import_scope)
422 self.run_init_ops(sess, tags, import_scope)
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/saved_model/loader_impl.pyc in load_graph(self, graph, tags, import_scope, **saver_kwargs)
348 with graph.as_default():
349 return tf_saver._import_meta_graph_with_return_elements( # pylint: disable=protected-access
--> 350 meta_graph_def, import_scope=import_scope, **saver_kwargs)
351
352 def restore_variables(self, sess, saver, import_scope=None):
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/training/saver.pyc in _import_meta_graph_with_return_elements(meta_graph_or_file, clear_devices, import_scope, return_elements, **kwargs)
1455 import_scope=import_scope,
1456 return_elements=return_elements,
-> 1457 **kwargs))
1458
1459 saver = _create_saver_from_imported_meta_graph(
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/meta_graph.pyc in import_scoped_meta_graph_with_return_elements(meta_graph_or_file, clear_devices, graph, import_scope, input_map, unbound_inputs_col_name, restore_collections_predicate, return_elements)
804 input_map=input_map,
805 producer_op_list=producer_op_list,
--> 806 return_elements=return_elements)
807
808 # Restores all the other collections.
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/util/deprecation.pyc in new_func(*args, **kwargs)
505 'in a future version' if date is None else ('after %s' % date),
506 instructions)
--> 507 return func(*args, **kwargs)
508
509 doc = _add_deprecated_arg_notice_to_docstring(
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/importer.pyc in import_graph_def(graph_def, input_map, return_elements, name, op_dict, producer_op_list)
397 if producer_op_list is not None:
398 # TODO(skyewm): make a copy of graph_def so we're not mutating the argument?
--> 399 _RemoveDefaultAttrs(op_dict, producer_op_list, graph_def)
400
401 graph = ops.get_default_graph()
/home/tigerpaws/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/importer.pyc in _RemoveDefaultAttrs(op_dict, producer_op_list, graph_def)
157 # Remove any default attr values that aren't in op_def.
158 if node.op in producer_op_dict:
--> 159 op_def = op_dict[node.op]
160 producer_op_def = producer_op_dict[node.op]
161 # We make a copy of node.attr to iterate through since we may modify
KeyError: u'BucketizeWithInputBoundaries'还有另一次尝试,我尝试将SavedModel转换成GraphDef (冻结图),这样我就可以再尝试一次。转换需要一个output_node_names,我不知道;我也找不到模型保存在代码中的位置(所以我可能可以在某个地方发现输出节点的名称)。
对这个问题有什么想法或者其他的方法吗?提前谢谢。
编辑:能帮助创建标签吗?我还没有达到1500个声誉,但这个问题实际上是关于tfx / tensorflow-extended的。
发布于 2019-05-25 10:09:23
很抱歉造成了混乱;问题实际上是由于读取SavedModel文件造成的。
在SavedModel中,有一个未在op_dict中定义的操作BucketizeWithInputBoundaries。
这仍然在谷歌的TODO列表中,在他们的两个脚本中有评论。
# TODO(jyzhao): BucketizeWithInputBoundaries error without this.导入指定的脚本后,这个问题就解决了。
from tensorflow.contrib.boosted_trees.python.ops import quantile_ops # pylint: disable=unused-importhttps://stackoverflow.com/questions/55362917
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