python - 使用 tensorflow 图转换工具时出错

Question

我正在尝试在 Linux Ubuntu 16.04 中的 tensorflow 1.4.1 的 tensorflow 对象检测模型上使用图形转换工具

使用的指令是:

bazel-bin/tensorflow/tools/graph_transforms/transform_graph --in_graph=/tf-optimizations/pascalvoc_gtt/frozen_inference_graph.pb --out_graph=/tf-optimizations/pascalvoc_gtt/optimized_frozen_inference_graph.pb --inputs='image_tensor' --outputs='detection_boxes,detection_scores,detection_classes,num_detections' --transforms='
add_default_attributes 
strip_unused_nodes(type=float) 
remove_nodes(op=CheckNumerics) 
fold_constants(ignore_errors=true) 
fold_batch_norms 
fold_old_batch_norms 
fuse_resize_pad_and_conv 
fuse_pad_and_conv 
fuse_resize_and_conv 
strip_unused_nodes 
sort_by_execution_order'

当我尝试查询优化后的 tensorflow 图时，

(boxes, scores, classes, num) = sess.run([detection_boxes, detection_scores, detection_classes, num_detections], feed_dict={image_tensor: image_np_expanded})

我收到以下错误:

InvalidArgumentError: NodeDef mentions attr 'identical_element_shapes' not in Op<name=TensorArrayV3; signature=size:int32 -> handle:resource, flow:float; attr=dtype:type; attr=element_shape:shape,default=<unknown>; attr=dynamic_size:bool,default=false; attr=clear_after_read:bool,default=true; attr=tensor_array_name:string,default=""; is_stateful=true>; NodeDef: Preprocessor/map/TensorArray = TensorArrayV3[clear_after_read=true, dtype=DT_FLOAT, dynamic_size=false, element_shape=<unknown>, identical_element_shapes=false, tensor_array_name="", _device="/job:localhost/replica:0/task:0/device:GPU:0"](Preprocessor/map/TensorArrayUnstack/strided_slice). (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).
 [[Node: Preprocessor/map/TensorArray = TensorArrayV3[clear_after_read=true, dtype=DT_FLOAT, dynamic_size=false, element_shape=<unknown>, identical_element_shapes=false, tensor_array_name="", _device="/job:localhost/replica:0/task:0/device:GPU:0"](Preprocessor/map/TensorArrayUnstack/strided_slice)]]

Caused by op u'Preprocessor/map/TensorArray', defined at:
File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py", line 478, in start
self.io_loop.start()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 281, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 232, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 397, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-7-982229c93a39>", line 7, in <module>
tf.import_graph_def(od_graph_def, name='')
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/importer.py", line 313, in import_graph_def
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1470, in __init__
self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): NodeDef mentions attr 'identical_element_shapes' not in Op<name=TensorArrayV3; signature=size:int32 -> handle:resource, flow:float; attr=dtype:type; attr=element_shape:shape,default=<unknown>; attr=dynamic_size:bool,default=false; attr=clear_after_read:bool,default=true; attr=tensor_array_name:string,default=""; is_stateful=true>; NodeDef: Preprocessor/map/TensorArray = TensorArrayV3[clear_after_read=true, dtype=DT_FLOAT, dynamic_size=false, element_shape=<unknown>, identical_element_shapes=false, tensor_array_name="", _device="/job:localhost/replica:0/task:0/device:GPU:0"](Preprocessor/map/TensorArrayUnstack/strided_slice). (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).
 [[Node: Preprocessor/map/TensorArray = TensorArrayV3[clear_after_read=true, dtype=DT_FLOAT, dynamic_size=false, element_shape=<unknown>, identical_element_shapes=false, tensor_array_name="", _device="/job:localhost/replica:0/task:0/device:GPU:0"](Preprocessor/map/TensorArrayUnstack/strided_slice)]]

我不知道出了什么问题，因为原始的卡住图工作正常。

Answer 1

问题已解决。是版本问题。该模型是在与 GTT 不同的版本中生成的。