Just tried to build it (Windows) and got:

execution.lo.lib(TRTEngine.obj) : error LNK2019: unresolved external symbol createInferRuntime_INTERNAL referenced in function "public: __cdecl trtorch::core::execution::TRTEngine::TRTEngine(class std::basic_string<char,struct std::char_traits,class std::allocator >,class std::basic_string<char,struct std::char_traits,class std::allocator >)" (??0TRTEngine@execution@core@trtorch@@qeaa@V?$basic_string@DU?$char_traits@D@std@@v?$allocator@D@2@@std@@0@Z)
conversionctx.lib(ConversionCtx.obj) : error LNK2019: unresolved external symbol createInferBuilder_INTERNAL referenced in function "public: __cdecl trtorch::core::conversion::ConversionCtx::ConversionCtx(struct trtorch::core::conversion::BuilderSettings)" (??0ConversionCtx@conversion@core@trtorch@@qeaa@UBuilderSettings@123@@z)
bazel-out\x64_windows-opt\bin\cpp\api\lib\libtrtorch.so : fatal error LNK1120: 3 unresolved externals

Edit: Sorry, unrelated to this PR.
It was this commit: 858d8c3#diff-e0ac18efc84fa06bf6e9b694d57f68adL75

Here's this PR built for Windows:
trtorch-PR.zip
trtorch-PR-debug.zip

Unfortunately, the same bug still occurs that was happening prior to this PR.
While calling torch::jit::parseSchema on:
trt::execute_engine(Tensor[] inputs, __torch__.torch.classes.tensorrt.Engine engine) -> Tensor[]

Last 3 lines in debug console are:
DEBUG: [TRTorch - Debug Build] - Registering evaluator for prim::unchecked_cast
DEBUG: [TRTorch - Debug Build] - Registering evaluator for prim::Uninitialized
DEBUG: [TRTorch - Debug Build] - Registering evaluator for prim::RaiseException

We can add back the change, but we removed it because it broke linux builds. Maybe we can just have a default condition with an empty list

Oh yeah, I've added it back to compile it, but the other issue below remain. It's the issue in #153 so probably Windows only.

Unknown custom class type tensorrt.Engine. Please ensure it is registered.:
trt::execute_engine(Tensor[] inputs, torch.torch.classes.tensorrt.Engine engine) -> Tensor[]
                                                                  ~~~~~~ <--- HERE

If I ignore this exception, it seems to correctly compile the graph but then when executing it, I get:

ERROR: [TRTorch Conversion Context] - %input.61 : Tensor = aten::prelu(%input.59, %self.input_layer.2.weight) # /home/sacha/.local/lib/python3.8/site-packages/torch/nn/functional.py:1263:0: slope tensor must be unidirectional broadcastable to input tensor
DEBUG: [TRTorch - Debug Build] - momentum disregarded
DEBUG: [TRTorch - Debug Build] - training disregarded
DEBUG: [TRTorch - Debug Build] - cudnn disregarded
DEBUG: [TRTorch - Debug Build] - Input shape is less than 4D got: [], inserting shuffle layer to reshape to 4D tensor shape: [1, 1, 1, 1]
DEBUG: [TRTorch - Debug Build] - Weights: [64]
    Number of input maps: 64
    Number of output maps: 64
    Element shape: [1]
DEBUG: [TRTorch - Debug Build] - Weights: [64]
    Number of input maps: 64
    Number of output maps: 64
    Element shape: [1]
ERROR: [TRTorch Conversion Context] - %input.61 : Tensor = aten::prelu(%input.59, %self.input_layer.2.weight) # /home/sacha/.local/lib/python3.8/site-packages/torch/nn/functional.py:1263:0: slope tensor must be unidirectional broadcastable to input tensor
ERROR: [TRTorch Conversion Context] - Parameter check failed at: Network.cpp::nvinfer1::Network::addScaleNd::737, condition: nbSpatialDims == 2 || nbSpatialDims == 3

That appears to be a aten::prelu issue, so I tried it on a model that doesn't have prelu and it got much further past this.
It seems to run the model and then ended up with this error:

0 INTERNAL ASSERT FAILED at "..\\..\\torch\\csrc\\jit\\ir\\alias_analysis.cpp":465, please report a bug to PyTorch. We don't have an op for trt::execute_engine but it isn't a special case.  Argument types: Tensor[], __torch__.torch.classes.tensorrt.Engine,
Exception raised from analyzeImpl at ..\..\torch\csrc\jit\ir\alias_analysis.cpp:465 (most recent call first):

Hmm, seems like that error is actually caused by some issue earlier in the compilation process. I see

DEBUG: [TRTorch - Debug Build] - Input shape is less than 4D got: [], inserting shuffle layer to reshape to 4D tensor shape: [1, 1, 1, 1]

Which is odd for the input to prelu. That would explain why you cannot broadcast here

The issues I'm facing do not seem to be related to this PR in any case.