fix: adding auto resolution config support
fix: adding auto resolution config support #5256
The JumpStart inference configuration auto-detection problem occurred because users had to manually specify the config_name parameter when deploying models to different instance types, leading to deployment failures when GPU configurations were incorrectly applied to Neuron instances or vice versa. The root cause was that four critical artifact retrieval functions (image_uris.py, model_uris.py, environment_variables.py, and resource_requirements.py) lacked auto-detection logic, causing the system to default to the first available configuration instead of selecting the appropriate one for the target instance type.
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Hi, as part of incoming PySDK V3 release, master branch will be replaced by PySDK V3 code. We have changed the target branch to master-v2