add dynamic shape support for scaled_dot_product_attention, logical_or/xor

[lanluo-nvidia]

Description

add dynamic shape support for scaled_dot_product_attention, logical_or/xor

Type of change

Please delete options that are not relevant and/or add your own.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

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

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/attention.py	2024-07-09 18:52:45.665012+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/attention.py	2024-07-09 18:54:35.965383+00:00
@@ -62,11 +62,11 @@
        L, S = query.shape[-2], key.shape[-2]
        if L < 0 or S < 0:
            raise RuntimeError(
                "scaled_do_product_attention does not support query.shape[-2] or key.shape[-2] is dynamic when is_casual is True"
            )
-        
+
        attn_bias = np.zeros((L, S), dtype=dtype._from(query.dtype).to(np.dtype))
        temp_mask = np.logical_not(np.tril(np.ones((L, S), dtype=np.bool_), k=0))
        attn_bias = np.ma.array(attn_bias, mask=temp_mask).filled(float("-inf"))
        attn_bias = get_trt_tensor(ctx, attn_bias, name + "_attn_bias")

[peri044]

LGTM. minor change