feat: Add optional tensor domain argument to Input class

[gs-olive]

Description

• Add support for specifying one, both, or neither integer bound (in Python) on Tensor domain used for generating a sample tensor in shape analysis
• Add bounds checking to avoid int32_t overflow issues
• Add validation for inputs to ensure high bound exceeds low bound and inputs are strictly integers
• Use [0, 2) as the default bound, which works well as a random-number selection range in cases of Bool, Int, and Float types
• Add validation in C++ to ensure provided domain arguments have the correct number of elements and ordering
• Add functionality to print domains as part of both partitioning and initialization, for debugging purposes
• Add hooks in pybind to capture specified input domain argument and parse values for mirrored internal representation
• Add new Input constructors with defaults to accommodate new tensor_domain argument

Fixes #1531
Addresses Prototype + MVP of #1425

Type of change

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

Checklist:

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

[narendasan]

@bowang007 can you be the reviewer for this PR?

[bowang007]

LGTM