add annotation in load_inference_model

revert-12864-feature/process_lod_grad
tangwei12 7 years ago
parent f6b06bdba8
commit 08152916cf

@ -691,6 +691,10 @@ def load_inference_model(dirname,
parameters were saved in a single binary
file. If parameters were saved in separate
files, set it as 'None'.
pserver_endpoints(list|None): This only need by distributed inference.
When use distributed look up table in training,
We also need it in inference.The parameter is
a list of pserver endpoints.
Returns:
tuple: The return of this function is a tuple with three elements:
@ -709,12 +713,16 @@ def load_inference_model(dirname,
exe = fluid.Executor(fluid.CPUPlace())
path = "./infer_model"
endpoints = ["127.0.0.1:2023","127.0.0.1:2024"]
[inference_program, feed_target_names, fetch_targets] =
fluid.io.load_inference_model(dirname=path, executor=exe)
results = exe.run(inference_program,
feed={feed_target_names[0]: tensor_img},
fetch_list=fetch_targets)
# if we need lookup table, we will use:
fluid.io.load_inference_model(dirname=path, executor=exe, pserver_endpoints=endpoints)
# In this exsample, the inference program was saved in the
# "./infer_model/__model__" and parameters were saved in
# separate files in ""./infer_model".

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