Deploy!!! How can I serve the exported model into tensorflow serving with rest api ?

[xiaoyangnihao]

First thanks for author's work. I exprot the saved_model with the export.py. And I want to deploy this model with tensorflow serving and use the rest api to make the prediction. The deployment works well. I start TensorFlow Serving and open the REST API port, But I don't know how to make the prediction, or does anyone can help me, thanks a lot.

[XXX@pachira-sh1 ptts_serving]$ bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server --rest_api_port=8081 --model_name=tacotron --model_base_path=/home/XXX/ptts_serving/saved_models/tacotron
2019-08-08 14:16:24.073923: I tensorflow_serving/model_servers/server.cc:82] Building single TensorFlow model file config:  model_name: tacotron model_base_path: /home/XXX/ptts_serving/saved_models/tacotron
2019-08-08 14:16:24.084761: I tensorflow_serving/model_servers/server_core.cc:462] Adding/updating models.
2019-08-08 14:16:24.084845: I tensorflow_serving/model_servers/server_core.cc:573]  (Re-)adding model: tacotron
2019-08-08 14:16:24.192643: I tensorflow_serving/core/basic_manager.cc:739] Successfully reserved resources to load servable {name: tacotron version: 1000}
2019-08-08 14:16:24.192704: I tensorflow_serving/core/loader_harness.cc:66] Approving load for servable version {name: tacotron version: 1000}
2019-08-08 14:16:24.192752: I tensorflow_serving/core/loader_harness.cc:74] Loading servable version {name: tacotron version: 1000}
2019-08-08 14:16:24.192890: I external/org_tensorflow/tensorflow/contrib/session_bundle/bundle_shim.cc:363] Attempting to load native SavedModelBundle in bundle-shim from: /home/XXX/ptts_serving/saved_models/tacotron/1000
2019-08-08 14:16:24.192931: I external/org_tensorflow/tensorflow/cc/saved_model/reader.cc:31] Reading SavedModel from: /home/XXX/ptts_serving/saved_models/tacotron/1000
2019-08-08 14:16:24.348842: I external/org_tensorflow/tensorflow/cc/saved_model/reader.cc:54] Reading meta graph with tags { serve }
2019-08-08 14:16:24.517981: I external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-08-08 14:16:25.142247: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:202] Restoring SavedModel bundle.
2019-08-08 14:16:26.318462: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:311] SavedModel load for tags { serve }; Status: success. Took 2125501 microseconds.
2019-08-08 14:16:26.318600: I tensorflow_serving/servables/tensorflow/saved_model_warmup.cc:103] No warmup data file found at /home/XXX/ptts_serving/saved_models/tacotron/1000/assets.extra/tf_serving_warmup_requests
2019-08-08 14:16:26.319257: I tensorflow_serving/core/loader_harness.cc:86] Successfully loaded servable version {name: tacotron version: 1000}
2019-08-08 14:16:26.348335: I tensorflow_serving/model_servers/server.cc:326] Running gRPC ModelServer at 0.0.0.0:8500 ...
2019-08-08 14:16:26.365618: I tensorflow_serving/model_servers/server.cc:346] Exporting HTTP/REST API at:localhost:8081 ...
[evhttp_server.cc : 239] RAW: Entering the event loop ...

offical predict show like this:

# 4. Query the model using the predict API
curl -d '{"instances": [1.0, 2.0, 5.0]}' \
    -X POST http://localhost:8501/v1/models/half_plus_two:predict

# Returns => { "predictions": [2.5, 3.0, 4.5] }

I tried like this, But it doesn't work, the format of prediction is wrong or not, I'm not sure, Hope to have the solution, thanks

[XXX@pachira-sh1 ~]$ curl -d '{"instances": ['hello', 5]}' -X POST http://localhost:8081/v1/models/tacotron:predict
{ "error": "JSON Parse error: Invalid value. at offset: 15" }

[xiaoyangnihao]

@LearnedVector @Suhee05