🐛 [Bug] Some elementwise like floor_divide.Scalar using float as default scalar type

[Njuapp]

Bug Description

Elementwise operations like floor_divide.Scalar uses float as default scalar type, this may cause error in such a case:
The graph is partitioned into torch/tensorrt-interleaved subgraphs, and floor_divide.Scalar accepts one INT-type tensor and one INT-type scalar as input, and the output is fed into the subsequent subgraph as its INT-type input.
However, currently the floor_divide.Scalar converts the scalar into float by default, and then output a float-type tensor, which does not fullfill the requirement of subsequent graph.

To Reproduce

Traceback (most recent call last):
File "reproduce.py", line 34, in
trt_model(img_input)
File "/root/.pyenv/versions/3.7.13/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
RuntimeError: The following operation failed in the TorchScript interpreter.
Traceback of TorchScript (most recent call last):
RuntimeError: [Error thrown at core/runtime/execute_engine.cpp:91] Expected inputs[pyt_idx].dtype() == expected_type to be true but got false
Expected input tensors to have type Int, found type float

Expected behavior

Environment

Build information about Torch-TensorRT can be found by turning on debug messages

• Torch-TensorRT Version (e.g. 1.0.0):
• PyTorch Version (e.g. 1.0):
• CPU Architecture:
• OS (e.g., Linux):
• How you installed PyTorch (conda, pip, libtorch, source):
• Build command you used (if compiling from source):
• Are you using local sources or building from archives:
• Python version:
• CUDA version:
• GPU models and configuration:
• Any other relevant information:

Additional context

[narendasan]

@Njuapp can you share a repro?