feat: dynamic shape support for squeeze ops

[keehyuna]

Description

It seems full dynamic shape for squeeze is not supported because data-dependent shape is used as input.
add_non_zero() was used to get dims to remove and it's result is used for reshape of input.

2cf4eaa#diff-7e6d7566192094882e7d98bfd423d08f49cf2d334c15cd3db12f4385ba82d3a1R51-R115

If dims for squeeze are static shape, operation is successful.
shape of x = (1, -1, 1, -1, 1)
torch.ops.aten.squeeze.dims(x, (0, 4))

If dims for squeeze are dynamic shape, there will be assert()
shape of x = (1, -1, 1, -1, 1)
torch.ops.aten.squeeze.dims(x, (0, 1))
AssertionError: We don't support squeeze dynamic dim.

More than one dynamic dim can be used if they are not squeezed.

Type of change

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

• 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]

LGTM. Although this is not a part of this PR, can you rename the variable in this for loop ?

TensorRT/py/torch_tensorrt/dynamo/conversion/impl/squeeze.py

Line 29 in dafabaa

for dim in dim: