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Implement CloudEP for hybrid inferencing. The PR introduces zero new API, customers could configure session and run options to do inferencing with Azure [triton endpoint.](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-with-triton?tabs=azure-cli%2Cendpoint) Sample configuration in python be like: ``` sess_opt.add_session_config_entry('cloud.endpoint_type', 'triton'); sess_opt.add_session_config_entry('cloud.uri', 'https://cloud.com'); sess_opt.add_session_config_entry('cloud.model_name', 'detection2'); sess_opt.add_session_config_entry('cloud.model_version', '7'); // optional, default 1 sess_opt.add_session_config_entry('cloud.verbose', '1'); // optional, default '0', meaning no verbose ... run_opt.add_run_config_entry('use_cloud', '1') # 0 for local inferencing, 1 for cloud endpoint. run_opt.add_run_config_entry('cloud.auth_key', '...') ... sess.run(None, {'input':input_}, run_opt) ``` Co-authored-by: Randy Shuai <rashuai@microsoft.com>
4 lines
280 B
Batchfile
4 lines
280 B
Batchfile
REM Copyright (c) Microsoft Corporation. All rights reserved.
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REM Licensed under the MIT License.
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set PATH=%cd%\RelWithDebInfo\_deps\vcpkg-src\installed\x64-windows\bin;%cd%\RelWithDebInfo\_deps\vcpkg-src\installed\x86-windows\bin;%PATH%
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set GRADLE_OPTS=-Dorg.gradle.daemon=false
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