Models: '_UserObject' object has no attribute 'summary'

[nicholasguimaraes]

Hello, I'm trying to load a ssd_resnet50_v1_fpn_640x640_coco17_tpu-8 I just fine tuned but I'm coming across this error:

'_UserObject' object has no attribute 'summary'

Here are the 4 lines of code I have;

import tensorflow as tf

model_dir = 'C:/Users/Windows/Documents/Tensorflow_Obj_Det_API/models/research/object_detection/inference_graph/saved_model'

trained_model = tf.saved_model.load(model_dir)

trained_model.summary()

I've tried including the save_model.pb on the path to the model but then I get this error:

SavedModel file does not exist at: C:\Users\Windows\Documents\Tensorflow_Obj_Det_API\models\research\object_detection\inference_graph\saved_model\saved_model.pb/{saved_model.pbtxt|saved_model.pb}

Anyone knows how to load a trained model to do inference?

[nicholasguimaraes]

I'm using the tf.keras.models.load_model function instead of tf.saved_model.load to load the model.

Now I'm getting a different error;

spec = fn.concrete_functions[0].structured_input_signature[0][0]
IndexError: list index out of range

[CptK1ng]

Did you already solved your problems? I ran in to the same issue. Using the saved_model.pb from the object detection api. Tried tf.saved_model.load as well as tf.keras.models.load_model

[jvishnuvardhan]

@nicholasguimaraes Can you please share a standalone code to reproduce the issue? Thanks!

[tensorflow-butler[bot]]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you.

[yingsiq]

I ran in to the same issue. Using the saved_model.pb from the object detection api. Tried tf.saved_model.load as well as tf.keras.models.load_model. Both gave this error:

AttributeError: '_UserObject' object has no attribute 'summary'

[hlloydt]

I am also getting the same error with models:

• SSD with Resnet 50 v1 FPN feature extractor, shared box predictor and focal loss (a.k.a Retinanet).
• SSD with EfficientNet-b4 + BiFPN feature extractor, shared box predictor and focal loss (a.k.a EfficientDet-d4)

The config files are the same the ones in: models/research/object_detection/configs/tf2/

I first train with: models/research/object_detection/model_main_tf2.py

And then I export with: models/research/object_detection/exporter_main_v2.py

But then when I try to load the exported model I get the error:

Traceback (most recent call last):
  File "/Users/harrythomas/projects/xrfiber_effdet/pb_to_coreml.py", line 82, in <module>
    main()
  File "/Users/harrythomas/projects/xrfiber_effdet/pb_to_coreml.py", line 22, in main
    model = tf.keras.models.load_model(PATH_TO_MODEL, compile=False)
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/save.py", line 187, in load_model
    return saved_model_load.load(filepath, compile, options)
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 120, in load
    model = tf_load.load_internal(
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/saved_model/load.py", line 632, in load_internal
    loader = loader_cls(object_graph_proto, saved_model_proto, export_dir,
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 194, in __init__
    super(KerasObjectLoader, self).__init__(*args, **kwargs)
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/saved_model/load.py", line 130, in __init__
    self._load_all()
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 221, in _load_all
    self._finalize_objects()
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 526, in _finalize_objects
    _finalize_saved_model_layers(layers_revived_from_saved_model)
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 706, in _finalize_saved_model_layers
    inputs = infer_inputs_from_restored_call_function(call_fn)
  File "/Users/harrythomas/opt/anaconda3/envs/effdetvenv/lib/python3.8/site-packages/tensorflow/python/keras/saving/saved_model/load.py", line 982, in infer_inputs_from_restored_call_function
    spec = fn.concrete_functions[0].structured_input_signature[0][0]
IndexError: list index out of range

System Information:

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 18.04
• Mobile device name if the issue happens on a mobile device:
• TensorFlow installed from (source or binary): pip
• TensorFlow version (use command below): 2.3.1
• Python version: 3.8.3
• Bazel version (if compiling from source):
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version: CUDA 10.1.243, cuDNN 7.6.4
• GPU model and memory: 2x 1080 Ti 10Gb

Code:

Import tensorflow as tf
import object_detection.models.keras_models.resnet_v1
import object_detection.models.feature_map_generators
PATH_TO_MODEL = ‘./saved_model/‘
model = tf.keras.models.load_model(PATH_TO_MODEL)

I can load and make predictions with

model = tf.saved_model.load(PATH_TO_MODEL)
tf_out = model(inputs)

However I wish to load the saved model so that I can edit it and then export it with coreML.

[xXDarkCubeXx]

has this issue been resolved yet? I'm getting the same issue.

[eRaul]

I am also getting the same issue. I was tring to load model from object detection model zone: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md

[epikjjh]

Same here issue when using object detection model in google colab

[MaxPRon]

Is there any progress on this ?

I'm trying to restore models in from both the Tensorflow hub as well as the object detection model zoo.

However in both cases I only get "._UserObject at 0x7f7431ec2070>" something like this. This has none of the usual model functionalities.

For Example the code I am using is the following:

test = tf.saved_model.load('models/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8/saved_model/')

The model has been download from here: http://download.tensorflow.org/models/object_detection/tf2/20200711/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8.tar.gz

I also used other loading methods such as: test_2 = tf.keras.models.load_model('models/faster_rcnn_resnet152_v1_800x1333_coco17_gpu-8/saved_model/')

But in both cases I don't get a fully functional model.

What I was expecting to get was a model with the usual compile(), fit() and predict() functions. However I am not sure if this is actually possible with the model zoo and tensorflow hub models.

I don't have any experiences with those pretrained models and therefore any help and suggestions are welcome.

``

[nilskk]

Does someone have any solution to this?

[xXDarkCubeXx]

I think the problem here is that the saved model wasn't created using Keras. so of course, when you load it you don't get a Keras object. It should be possible to create a new model with the same architecture as the one you want to load using Keras and load the weights from there. something like this:

keras_model.set_weights(loaded_model.get_weights())

[noirmist]

I convert model from pytorch to tensorflow through onnx and I've got same issue right now...

[twohiccups]

Is this issue still being worked on?

[RArbore]

I've got the same issue with a model I've converted from onnx... Is this issue going to be resolved ever?