# test functions implemented in train_deploy.py and deploy_ei.py import train_deploy import deploy_ei import json print("=============== Test regular entry point =================") # load model model = train_deploy.model_fn('../model') # single sentence request_body = json.dumps('performing inference on one sentence') data, mask = train_deploy.input_fn(request_body, 'application/json') output = train_deploy.predict_fn((data, mask), model) # batch inference request_body = json.dumps([ 'performing inference on a batch of sentences', 'make sure each one is less than 64 words']) data, mask = train_deploy.input_fn(request_body, 'application/json') output = train_deploy.predict_fn((data, mask), model) print("=============== Test entry point for elastic inference =====") # load model model = deploy_ei.model_fn('../model') # single sentence request_body = json.dumps('performing inference on one sentence') data, mask = deploy_ei.input_fn(request_body, 'application/json') output = train_deploy.predict_fn((data, mask), model) # batch inference request_body = json.dumps([ 'performing inference on a batch of sentences', 'make sure each one is less than 64 words']) data, mask = deploy_ei.input_fn(request_body, 'application/json') output = deploy_ei.predict_fn((data, mask), model)