Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 #8841

m-brgs · 2020-07-11T17:57:36Z

Prerequisites

Please answer the following questions for yourself before submitting an issue.

I am using the latest TensorFlow Model Garden release and TensorFlow 2.
I am reporting the issue to the correct repository. (Model Garden official or research directory)
I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/blob/master/research/object_detection/exporter_main_v2.py

2. Describe the bug

I'm trying to export a TF2 OD API efficientdet_d0 that I just trained (using pretrained weights from model zoo 2 and 2GPUs in the tf2 docker image from OD API repo) with exporter_main_v2.py in order to serve this model with Tensorflow Serving.

When exporting, I'm getting a type error.

3. Steps to reproduce

Take the result of training a ssd_efficientdet_d0_512x512 model.

Inside TF2 container, (https://github.com/tensorflow/models/blob/master/research/object_detection/dockerfiles/tf2/Dockerfile), run :

python object_detection/exporter_main_v2.py \
--input_type encoded_image_string_tensor \
--trained_checkpoint_dir /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/model_dir/ \
--output_directory /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/export/ \
--pipeline_config_path /home/tensorflow/pipeline.config

4. Expected behavior

The model is exported in /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/export/ as described in https://github.com/tensorflow/models/blob/master/research/object_detection/exporter_main_v2.py

5. Additional context

Logs :

I0711 17:37:09.737181 139828628232000 ssd_efficientnet_bifpn_feature_extractor.py:144] EfficientDet EfficientNet backbone version: efficientnet-b0
I0711 17:37:09.737298 139828628232000 ssd_efficientnet_bifpn_feature_extractor.py:145] EfficientDet BiFPN num filters: 64
I0711 17:37:09.737352 139828628232000 ssd_efficientnet_bifpn_feature_extractor.py:147] EfficientDet BiFPN num iterations: 3
I0711 17:37:09.745369 139828628232000 efficientnet_model.py:146] round_filter input=32 output=32
I0711 17:37:10.747392 139828628232000 efficientnet_model.py:146] round_filter input=32 output=32
I0711 17:37:10.747502 139828628232000 efficientnet_model.py:146] round_filter input=16 output=16
I0711 17:37:10.829591 139828628232000 efficientnet_model.py:146] round_filter input=16 output=16
I0711 17:37:10.829701 139828628232000 efficientnet_model.py:146] round_filter input=24 output=24
I0711 17:37:11.092894 139828628232000 efficientnet_model.py:146] round_filter input=24 output=24
I0711 17:37:11.093004 139828628232000 efficientnet_model.py:146] round_filter input=40 output=40
I0711 17:37:11.314886 139828628232000 efficientnet_model.py:146] round_filter input=40 output=40
I0711 17:37:11.314993 139828628232000 efficientnet_model.py:146] round_filter input=80 output=80
I0711 17:37:11.654193 139828628232000 efficientnet_model.py:146] round_filter input=80 output=80
I0711 17:37:11.654304 139828628232000 efficientnet_model.py:146] round_filter input=112 output=112
I0711 17:37:11.993307 139828628232000 efficientnet_model.py:146] round_filter input=112 output=112
I0711 17:37:11.993419 139828628232000 efficientnet_model.py:146] round_filter input=192 output=192
I0711 17:37:12.449521 139828628232000 efficientnet_model.py:146] round_filter input=192 output=192
I0711 17:37:12.449632 139828628232000 efficientnet_model.py:146] round_filter input=320 output=320
I0711 17:37:12.555558 139828628232000 efficientnet_model.py:146] round_filter input=1280 output=1280
I0711 17:37:12.599392 139828628232000 efficientnet_model.py:459] Building model efficientnet with params ModelConfig(width_coefficient=1.0, depth_coefficient=1.0, resolution=224, dropout_rate=0.2, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32')
WARNING:tensorflow:From /home/tensorflow/.local/lib/python3.6/site-packages/object_detection/exporter_lib_v2.py:101: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.
Instructions for updating:
back_prop=False is deprecated. Consider using tf.stop_gradient instead.
Instead of:
results = tf.map_fn(fn, elems, back_prop=False)
Use:
results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))
W0711 17:37:16.879535 139828628232000 deprecation.py:573] From /home/tensorflow/.local/lib/python3.6/site-packages/object_detection/exporter_lib_v2.py:101: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.
Instructions for updating:
back_prop=False is deprecated. Consider using tf.stop_gradient instead.
Instead of:
results = tf.map_fn(fn, elems, back_prop=False)
Use:
results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))
WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7f2b7c1ac5f8>, because it is not built.
W0711 17:37:39.926661 139828628232000 save_impl.py:76] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7f2b7c1ac5f8>, because it is not built.
Traceback (most recent call last):
  File "object_detection/exporter_main_v2.py", line 126, in <module>
    app.run(main)
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 299, in run
    _run_main(main, args)
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 250, in _run_main
    sys.exit(main(argv))
  File "object_detection/exporter_main_v2.py", line 122, in main
    FLAGS.output_directory)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/object_detection/exporter_lib_v2.py", line 180, in export_inference_graph
    signatures=concrete_function)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/saved_model/save.py", line 951, in save
    obj, export_dir, signatures, options, meta_graph_def)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/saved_model/save.py", line 1022, in _build_meta_graph
    _ = _SaveableView(checkpoint_graph_view)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/saved_model/save.py", line 173, in __init__
    self.checkpoint_view.objects_ids_and_slot_variables())
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/training/tracking/graph_view.py", line 415, in objects_ids_and_slot_variables
    trackable_objects, path_to_root = self._breadth_first_traversal()
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/training/tracking/graph_view.py", line 199, in _breadth_first_traversal
    for name, dependency in self.list_dependencies(current_trackable):
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/saved_model/save.py", line 108, in list_dependencies
    extra_dependencies = self.list_extra_dependencies(obj)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/saved_model/save.py", line 137, in list_extra_dependencies
    self._serialization_cache)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 2746, in _list_extra_dependencies_for_serialization
    .list_extra_dependencies_for_serialization(serialization_cache))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/base_serialization.py", line 74, in list_extra_dependencies_for_serialization
    return self.objects_to_serialize(serialization_cache)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/layer_serialization.py", line 73, in objects_to_serialize
    serialization_cache).objects_to_serialize)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/layer_serialization.py", line 92, in _get_serialized_attributes
    serialization_cache)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/model_serialization.py", line 53, in _get_serialized_attributes_internal
    serialization_cache))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/layer_serialization.py", line 101, in _get_serialized_attributes_internal
    functions = save_impl.wrap_layer_functions(self.obj, serialization_cache)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 163, in wrap_layer_functions
    '{}_layer_call_and_return_conditional_losses'.format(layer.name))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 503, in add_function
    self.add_trace(*self._input_signature)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 418, in add_trace
    trace_with_training(True)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 416, in trace_with_training
    fn.get_concrete_function(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 547, in get_concrete_function
    return super(LayerCall, self).get_concrete_function(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 959, in get_concrete_function
    concrete = self._get_concrete_function_garbage_collected(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 865, in _get_concrete_function_garbage_collected
    self._initialize(args, kwargs, add_initializers_to=initializers)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 506, in _initialize
    *args, **kwds))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2446, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2777, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2667, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py", line 981, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 441, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 524, in wrapper
    ret = method(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 170, in wrap_with_training_arg
    lambda: replace_training_and_call(False))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py", line 65, in smart_cond
    pred, true_fn=true_fn, false_fn=false_fn, name=name)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/framework/smart_cond.py", line 54, in smart_cond
    return true_fn()
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 169, in <lambda>
    lambda: replace_training_and_call(True),
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 165, in replace_training_and_call
    return wrapped_call(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 566, in call_and_return_conditional_losses
    return layer_call(inputs, *args, **kwargs), layer.get_losses_for(inputs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/object_detection/meta_architectures/ssd_meta_arch.py", line 251, in call
    return self._extract_features(inputs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/object_detection/models/ssd_efficientnet_bifpn_feature_extractor.py", line 224, in _extract_features
    list(zip(self._output_layer_alias, base_feature_maps)))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 968, in __call__
    outputs = self.call(cast_inputs, *args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 71, in return_outputs_and_add_losses
    outputs, losses = fn(inputs, *args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 170, in wrap_with_training_arg
    lambda: replace_training_and_call(False))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py", line 65, in smart_cond
    pred, true_fn=true_fn, false_fn=false_fn, name=name)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/framework/smart_cond.py", line 54, in smart_cond
    return true_fn()
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 169, in <lambda>
    lambda: replace_training_and_call(True),
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/utils.py", line 165, in replace_training_and_call
    return wrapped_call(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 541, in __call__
    self.call_collection.add_trace(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 418, in add_trace
    trace_with_training(True)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 416, in trace_with_training
    fn.get_concrete_function(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 547, in get_concrete_function
    return super(LayerCall, self).get_concrete_function(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 959, in get_concrete_function
    concrete = self._get_concrete_function_garbage_collected(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 865, in _get_concrete_function_garbage_collected
    self._initialize(args, kwargs, add_initializers_to=initializers)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 506, in _initialize
    *args, **kwds))
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2446, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2777, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2667, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py", line 981, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 441, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 524, in wrapper
    ret = method(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 484, in wrap_with_training_arg
    return call_fn(*args, **kwargs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/saving/saved_model/save_impl.py", line 566, in call_and_return_conditional_losses
    return layer_call(inputs, *args, **kwargs), layer.get_losses_for(inputs)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1627, in get_losses_for
    reachable = tf_utils.get_reachable_from_inputs(inputs, losses)
  File "/home/tensorflow/.local/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py", line 140, in get_reachable_from_inputs
    raise TypeError('Expected Operation, Variable, or Tensor, got ' + str(x))
TypeError: Expected Operation, Variable, or Tensor, got level_5

6. System information

OS Platform and Distribution : Linux Ubuntu 16.04, docker 19.3, nvidia-docker
Mobile device name if the issue happens on a mobile device: N/A
TensorFlow installed from (source or binary): Docker image, binary
TensorFlow version (use command below): 2.2.0
Python version: 3.6
Bazel version (if compiling from source):N/A
GCC/Compiler version (if compiling from source):N/A
CUDA/cuDNN version: N/A
GPU model and memory: N/A

v2.2.0-rc4-8-g2b96f3662b 2.2.0

The text was updated successfully, but these errors were encountered:

ronykroy · 2020-07-12T11:37:22Z

isin

Could you please elaborate... I am trying to save a model from the demo ipynb
https://github.com/tensorflow/models/blob/master/research/object_detection/colab_tutorials/eager_few_shot_od_training_tf2_colab.ipynb

and i am not sure where the above command goes in the said tf_utils.py file.
I too am getting a similar error message when i try to save the model to disk.

m-brgs · 2020-07-12T11:56:21Z

@ronykroy

anmol101093AIML is saying to edit this "if statement" line 128 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/utils/tf_utils.py#L128 in order to skip the TypeError Exception when x is a String.

I've not tested this quick fix, however I not sure editing the tensorflow/python/keras/utils package is a long term solution to this problem.

sayakpaul · 2020-07-13T04:14:33Z

Following this thread since I think there needs to be documentation about exporting the models (trained with TF 2 TFOD API) to SavedModel. Thanks for raising this.

Update: I was able to use the exporter script to generated SavedModel. Here's the Colab Notebook.

ronykroy · 2020-07-13T05:04:31Z

Following this thread since I think there needs to be documentation about exporting the models (trained with TF 2 TFOD API) to SavedModel. Thanks for raising this.

Update: I was able to use the exporter script to generated SavedModel. Here's the Colab Notebook.

Agreed, documentation for saving the OD model part is sketchy...
The colab notebook in the link reads 'Exporting the model (coming soon)'

I couldn't find the exporter script you mentioned..

sayakpaul · 2020-07-13T05:05:32Z

Could you please check now? I just pushed the updated one. @ronykroy

ronykroy · 2020-07-13T05:07:44Z

Great.. will run that..

Jacobsolawetz · 2020-07-13T06:43:38Z

@sayakpaul - thanks for the notebook!

How does your exporter_main_v2.py call differ from the one in the issue? Did you edit the keras utils file?

I am also receiving the same error tying to save weights for EfficientDet-d0

sayakpaul · 2020-07-13T07:04:46Z

How does your exporter_main_v2.py call differ from the one in the issue? Did you edit the keras utils file?

I did not change anything in that.

sayakpaul · 2020-07-13T07:11:48Z

How does your exporter_main_v2.py call differ from the one in the issue? Did you edit the keras utils file?

I did not change anything in that.

m-brgs · 2020-07-13T09:14:13Z

@Jacobsolawetz

This is an issue with EfficientDet-d0 returning a string as input.

sayakpaul example shows that it seems fine when using ssd_mobilenet_v2_320x320_coco17_tpu-8.

I'll try other models today and send a feedback asap ..

Anyone familiar with the EfficientDet-d0 implementation could look into this please ?

sayakpaul · 2020-07-13T09:16:00Z

Yes, this might be a model-specific issue. I should have mentioned I did not actually use EfficientDet. Sorry about that.

Jacobsolawetz · 2020-07-13T14:30:40Z

@m-brgs @sayakpaul - ah I see, thanks. We will have to stay tuned for efficientDet exports. I will write here if I find anything on my end.

For those more familiar with this implementation: I think the error may be stemming from this line W0713 06:32:23.701267 140712624875392 save_impl.py:76] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x7ff94c79c2e8>, because it is not built.

and the error message TypeError: Expected Operation, Variable, or Tensor, got level_5 makes me think something is not building correctly in the feature aggregator.

sayakpaul · 2020-07-13T14:58:21Z

@Jacobsolawetz @m-brgs when you have a moment, could you take a look at #8854 and comment if I am missing something there?

Jacobsolawetz · 2020-07-13T16:04:14Z

@m-brgs certainly not a long term solution, but the keras utils fix works 🎉

Adding check if x is a string in https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/utils/tf_utils.py#L128

if not isinstance(x, str):

So now

python object_detection/exporter_main_v2.py \
--input_type encoded_image_string_tensor \
--trained_checkpoint_dir /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/model_dir/ \
--output_directory /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/export/ \
--pipeline_config_path /home/tensorflow/pipeline.config

yields an EfficientDet .pb file. Now I'm working on an inference script using that.

mackdelany · 2020-07-15T00:03:15Z

Howdy, I get a similar error when trying to export SSD MobileNet V2 FPNLite 640x640 using exporter_lib_v2.py.

TypeError: Expected Operation, Variable, or Tensor, got layer_19

Using TF2 and model from TF2 Model Zoo

mackdelany · 2020-07-15T00:10:18Z

@Jacobsolawetz @m-brgs what was the precise change you made to line 128? Was it:

if isinstance(x, ops.Operation) and not isinstance(x, str):

Thanks :)

Jacobsolawetz · 2020-07-15T15:01:18Z

@mackdelany it was on line 140 right before raise TypeError('Expected Operation, Variable, or Tensor, got ' + str(x)) to check if not isinstance(x, str):

mackdelany · 2020-07-15T22:08:38Z

Ah, groovy. Thanks @Jacobsolawetz !

ngoanpv · 2020-07-16T06:16:57Z

@m-brgs certainly not a long term solution, but the keras utils fix works

Adding check if x is a string in https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/utils/tf_utils.py#L128

if not isinstance(x, str):

So now
python object_detection/exporter_main_v2.py \
--input_type encoded_image_string_tensor \
--trained_checkpoint_dir /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/model_dir/ \
--output_directory /home/tensorflow/outputs/efficientdet_d0_10k_16b_512_2gpu/export/ \
--pipeline_config_path /home/tensorflow/pipeline.config
yields an EfficientDet .pb file. Now I'm working on an inference script using that.

Hi @Jacobsolawetz Did inference script run successful?

sayakpaul · 2020-07-16T06:34:51Z

I did try running inference (not with EfficientDet models, though) with custom trained checkpoints and I was successful. Leaving a link to the notebook here if that's useful.

ngoanpv · 2020-07-16T08:32:05Z

That's cool, thanks @sayakpaul

Jacobsolawetz · 2020-07-16T15:08:29Z

@ngoanpv I did not have success with the .pb inference due to how eager execution has changed how to infer frozen graphs. I did have luck from the checkpoint, however.

I published a blog and Colab Notebook here training EfficientDet in TensorFlow2

ngoanpv · 2020-07-17T03:08:26Z

@Jacobsolawetz this link is not found, I found this post from your profile: https://towardsdatascience.com/how-to-train-a-tensorflow-2-object-detection-model-25d4da64b817

That's great, thanks.

Jacobsolawetz · 2020-07-17T19:34:48Z

@ngoanpv thank you! updated the link

bnascimento · 2020-10-07T10:13:55Z

with @Jacobsolawetz solution I was able to export a efficientdet-d0 model

m-brgs added models:research models that come under research directory type:bug Bug in the code labels Jul 11, 2020

saberkun assigned tombstone Jul 11, 2020

sayakpaul mentioned this issue Jul 13, 2020

[object_detection] Adding a handy Colab Notebook for training a custom pets detector model using the latest API #8836

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m-brgs changed the title ~~Type Error when exporting TF2 OD API to SavedModel~~ Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 Jul 13, 2020

Bhawnapriya11 mentioned this issue Sep 8, 2020

No checkpoint specified (save_path=None); nothing is being restored. #9209

Open

jaeyounkim added models:research:odapi ODAPI and removed models:research models that come under research directory labels Jun 25, 2021

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Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 #8841

Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 #8841

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Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 #8841

Type Error when exporting TF2 OD API to SavedModel using efficientdet_d0 #8841

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m-brgs commented Jul 11, 2020

Prerequisites

1. The entire URL of the file you are using

2. Describe the bug

3. Steps to reproduce

4. Expected behavior

5. Additional context

6. System information

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