feat: dynamic shape support for pad ops

[chohk88]

Description

Added dynamic shape support for the following padding operations:

• aten.constant_pad_nd
• aten.reflection_pad1d
• aten.reflection_pad2d
• aten.reflection_pad3d
• aten.replication_pad1d
• aten.replication_pad2d
• aten.replication_pad3d
• aten._pad_circular
• aten.pad

A commonly used function, get_padded_shape_tensors, has been introduced to adjust the dimensions of the input tensor to account for padding in various padding modes. This function simplifies the handling of dynamic shapes across different padding operations.

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

[peri044]

posted minor comments - overall the changes LGTM

[peri044]

Could you import from torch_tensorrt.dynamo ?

[chohk88]

Thank you for your comment! I've updated the TRTTensor to use torch_tensorrt.dynamo as suggested.

[peri044]

Curious : Why are the values negative here and what is the expectation of TensorRT when you do layer.set_input(1, start_indices_tensor) later ?

[chohk88]

The negative values in start_list[dim_index] = -pad_before are used to indicate the starting point for the slicing operation in TensorRT's ISliceLayer. When setting layer.set_input(1, start_indices_tensor), TensorRT interprets these negative start indices to appropriately offset the input tensor before applying padding.