[TensorRT EP] Back out the PerThreadContext (#17690)
Current TRT EP's PerthreadContext allows more than one IExecutionContext
instance to be created by one engine instance.
But, it's possible to hit an error that caused by TRT API
context.setBindingDimensions() in our TRT EP code
[here](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fmicrosoft%2Fonnxruntime%2Fblob%2Fmain%2Fonnxruntime%2Fcore%2Fproviders%2Ftensorrt%2Ftensorrt_execution_provider.cc%23L2775&data=05%7C01%7CChi.Lo%40microsoft.com%7Cd8b23c3a4c0b4dcce9b408dbbd9309de%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638312211465211140%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=5EZoAoXgWFSuz%2BIRMH%2FXZaO%2BfKNP%2FZDZYEZg3W%2Ff30w%3D&reserved=0)
under the case of the input shape changes ( meaning engine being
rebuilt) with multithreading.
From the
[doc](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.nvidia.com%2Fdeeplearning%2Ftensorrt%2Fapi%2Fc_api%2Fclassnvinfer1_1_1_i_execution_context.html%23ada050e88320bcc40987b0acadc2ef962&data=05%7C01%7CChi.Lo%40microsoft.com%7Cd8b23c3a4c0b4dcce9b408dbbd9309de%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638312211465211140%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2BmVZU5iLD97B3YBPdHZP7jOQ2dGoleI3R0mSMVgopG4%3D&reserved=0)
and the
[discussion](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FNVIDIA%2FTensorRT%2Fissues%2F846&data=05%7C01%7CChi.Lo%40microsoft.com%7Cd8b23c3a4c0b4dcce9b408dbbd9309de%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638312211465211140%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=c8v%2FK2UkQ%2FNbf8w1sHNDGsB2kxw4sSmkyQ2QuCs8Fs8%3D&reserved=0),
it seems we should have different OptimizationProfile for different
IExecutionContext which our current TRT EP doesn’t support regardless of
using PerThreadContext implementation.
Back out the PerThreadContext until we completely solve this issue.
