pytorch

9cb65df7 - [Static Runtime] Fallback to disabling manage_output_tensors instead of crashing when wrong API is used (#67939)

[Static Runtime] Fallback to disabling manage_output_tensors instead of crashing when wrong API is used (#67939) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/67939 With `manage_output_tensor` enabled, a client of `StaticRuntime` requires to call it via `PyTorchPredictor::predict_managed_result`. If the client uses `PyTorchPredictor::operator()` the client will experience a crash (intended behavior not to leak memory of managed output tensors). This mistake can cause a catastrophic failure in production if that happens (by gatekeeper, config changes, etc). Considering the complexity in how `PyTorchPredictor` is used in different settings, the chances that this bug can hit production is non-zero. This change introduces `StaticRuntime::disableManageOutputTensor` to disable `manage_output_tensor` feature when a client mistakenly uses `PyTorchPredictor::operator()` instead of crashing. When `StaticRuntime` is invoked via `PyTorchPredictor::operator()`, it first calls `StaticRuntime::disableManageOutputTensor` to disable the feature, so that it can get non-managed output tensors to pass to the client safely. A slight perf degradation is expected by forcefully disabling `manage_output_tensors`, but its robustness value outweighs a catastrophic failure of crashes at a high rate. Test Plan: Added a unittest `StaticRuntime, DisableManageOutputTensors` to cover the newly added code. Reviewed By: swolchok Differential Revision: D32219731 fbshipit-source-id: caf5c910b34726c570e17435ede7d888443e90cf