✨[Feature] Automatic type promotion for elementwise ops in FX

[gs-olive]

Context

Currently, elementwise operators are not automatically type-promoted in FX in the same way they are in TS. This leads to bugs such as #1995, where the types are mismatched and TensorRT throws an error.

Feature Proposal

Using the TS type-promotion code as a starting point:

TensorRT/core/conversion/converters/converter_util.cpp

Lines 72 to 78 in 82631fa

	nvinfer1::DataType promote_types(nvinfer1::DataType type_a, nvinfer1::DataType type_b) {
	auto torch_type_a = util::TRTDataTypeToScalarType(type_a);
	auto torch_type_b = util::TRTDataTypeToScalarType(type_b);
	auto promo_type = at::promote_types(torch_type_a, torch_type_b);
	auto trt_promo_type = util::ScalarTypeToTRTDataType(promo_type);
	return trt_promo_type;
	}

Implement a similar type-promotion scheme pointing to the converter_reorg_elementwise branch, here:

TensorRT/py/torch_tensorrt/fx/converters/impl/elementwise/base.py

Lines 40 to 48 in 546f975

	def convert_binary_elementwise(
	network: TRTNetwork,
	target: Target,
	source_ir: Optional[SourceIR],
	name: str,
	op_type: trt.ElementWiseOperation,
	lhs_val: Union[int, float, TRTTensor, torch.Tensor],
	rhs_val: Union[int, float, TRTTensor, torch.Tensor],
	) -> TRTTensor:

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[gs-olive]

Addressed in #2055, #2070