feat: support more elementwise and unary dynamo converters

[zewenli98]

Description

Support more elementwise and unary dynamo converters.

For bitwise_op converters, TensorRT doesn't support bitwise ops. Thus, if inputs are int values, they will fall back to pytorch. If inputs are bool, they will be converted with the help of logical_op.

Fixes #2208 #2199

Type of change

• New feature (non-breaking change which adds functionality)

Checklist:

• My code follows the style guidelines of this project (You can use the linters)
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas and hacks
• I have made corresponding changes to the documentation
• I have added tests to verify my fix or my feature
• New and existing unit tests pass locally with my changes
• I have added the relevant labels to my PR in so that relevant reviewers are notified

[gs-olive]

Overall looks good - had a few questions and suggestions as mentioned in the comments

[gs-olive]

Looks good to me overall! One question - should convert_binary_elementwise also be allowed to handle bool types?

Also - a rebase may be needed to avoid the CircleCI errors.

[zewenli98]

Looks good to me overall! One question - should convert_binary_elementwise also be allowed to handle bool types?

Yes, I agree with you. Fixed! Thanks for the comments.

[gs-olive]

Just a minor comment, bool should likely be added here, to lines 123 + 127 since this PR adds support for bool in convert_binary_elementwise:

TensorRT/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py

Lines 123 to 130 in 867dc7b

	if is_lhs_trt_tensor and isinstance(rhs_val, (float, int)):
	rhs_val = np.array(
	[rhs_val], dtype=unified_dtype_converter(lhs_dtype, Frameworks.NUMPY)
	)
	if is_rhs_trt_tensor and isinstance(lhs_val, (float, int)):
	lhs_val = np.array(
	[lhs_val], dtype=unified_dtype_converter(rhs_dtype, Frameworks.NUMPY)
	)

Otherwise, seems good to go!