CODEWITHSUNDEEP
tensorflow2.0tensorflow-serving
LLTeng
LLTeng

Reputation: 395

tensorflow serving REST API error: could not find base path /models/model for servable model

I'm new to tensorflow serving and docker, and I went through multiple tutorials and like to try it out on my retrained models.

When I run the following code I get the error of could not find base path, from my understanding, the target path is incorrect and docker can't find it. How can I define the target path? Thank you very much for your guidance! 

!docker run -p 8503:8501 \
    --name=ea4 \
    --mount type=bind,source=/home/jupyter/../saved_models/,target=/models/ea4 \
    -e MODEL_NAME=ea4 \
    -t tensorflow/serving

ERROR: 

2020-05-28 01:55:31.719025: I tensorflow_serving/model_servers/server.cc:86] Building single TensorFlow model file config:  model_name: ea4 model_base_path: /models/ea4
2020-05-28 01:55:31.719326: I tensorflow_serving/model_servers/server_core.cc:462] Adding/updating models.
2020-05-28 01:55:31.719363: I tensorflow_serving/model_servers/server_core.cc:573]  (Re-)adding model: ea4
2020-05-28 01:55:31.719784: E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:362] FileSystemStoragePathSource encountered a filesystem access error: Could not find base path /models/ea4 for servable ea4
2020-05-28 01:55:32.719680: E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:362] FileSystemStoragePathSource encountered a filesystem access error: Could not find base path /models/ea4 for servable ea4

Upvotes: 1

Views: 1711

Answers (1)

LLTeng
LLTeng

Reputation: 395

After the code is changed as follows, the port is now work in the docker image. 

!docker run -p 8501:8501 \
    --name=ea \
    -v "/home/../saved_models/:/models/ea/1" \
    -e MODEL_NAME=ea \
    -t tensorflow/serving

Upvotes: 2

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