Tensorflow serving No versions of servable <MODEL> found under base path

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I was following this tutorial to use tensorflow serving using my object detection model. I am using tensorflow object detection for generating the model. I have created a frozen model using this exporter (the generated frozen model works using python script).

The frozen graph directory has following contents ( nothing on variables directory)

variables/

saved_model.pb

Now when I try to serve the model using the following command,

tensorflow_model_server --port=9000 --model_name=ssd --model_base_path=/serving/ssd_frozen/

It always shows me

...

tensorflow_serving/model_servers/server_core.cc:421] (Re-)adding model: ssd 2017-08-07 10:22:43.892834: W tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:262] No versions of servable ssd found under base path /serving/ssd_frozen/ 2017-08-07 10:22:44.892901: W tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:262] No versions of servable ssd found under base path /serving/ssd_frozen/

...

tensorflow-serving object-detection tensorflow deep-learning
5 Answers
user_100096080

I was doing this on my personal computer running Ubuntu, not Docker. Note I am in a directory called "serving". This is where I saved my folder "mobile_weight". I had to create a new folder, "0000123" inside "mobile_weight". My path looks like serving->mobile_weight->0000123->(variables folder and saved_model.pb)

The command from the tensorflow serving tutorial should look like (Change model_name and your directory):

nohup tensorflow_model_server \
 --rest_api_port=8501  \
 --model_name=model_weight  \
 --model_base_path=/home/murage/Desktop/serving/mobile_weight >server.log 2>&1

So my entire terminal screen looks like:

murage@murage-HP-Spectre-x360-Convertible:~/Desktop/serving$ nohup tensorflow_model_server   --rest_api_port=8501   --model_name=model_weight   --model_base_path=/home/murage/Desktop/serving/mobile_weight >server.log 2>&1
user_130356300

That error message can also result due to issues with the --volume argument.

Ensure your --volume mount is actually correct and points to the model's dir, as this is a general 'model not found' error, but it just seems more complex.

If on windows just use cmd, otherwise its easy to accidentally use linux file path and linux separators in cygwin or gitbash. Even with the correct file structure you can get OP's error if you don't use the windows absolute path.

#using cygwin
$ echo $TESTDATA
/home/username/directory/serving/tensorflow_serving/servables/tensorflow/testdata

$ docker run -t --rm -p 8501:8501 -v "$TESTDATA/saved_model_half_plus_two_cpu:/models/half_plus_two" -e MODEL_NAME=half_plus_two tensorflow/serving
2021-01-22 20:12:28.995834: W tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:267] No versions of servable half_plus_two found under base path /models/half_plus_two. Did you forget to name your leaf directory as a number (eg. '/1/')?

Then calling the same command with the same unchanged file structure but with the full windows path using windows file separators, and it works:

#using cygwin
$ export TESTDATA="$(cygpath -w "/home/username/directory/serving/tensorflow_serving/servables/tensorflow/testdata")"
$ echo $TESTDATA
C:\Users\username\directory\serving\tensorflow_serving\servables\tensorflow\testdata

$ docker run -t --rm -p 8501:8501 -v "$TESTDATA\\saved_model_half_plus_two_cpu:/models/half_plus_two" -e MODEL_NAME=half_plus_two tensorflow/serving 
2021-01-22 21:10:49.527049: I tensorflow_serving/core/basic_manager.cc:740] Successfully reserved resources to load servable {name: half_plus_two version: 1}
user_33906590
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