Simplify puzzletron test configs: use HF model names and shared base YAMLs

[kevalmorabia97]

What does this PR do?

Type of change: New tests / Refactoring

Simplifies the puzzletron test infrastructure by:

1. Removing hf_configs/ folder — HuggingFace configs are now loaded on-the-fly via AutoConfig.from_pretrained(hf_model_name) instead of from cached static files.

2. Removing HF_MODEL_CARD_NAMES mapping — HF model names (e.g. meta-llama/Llama-3.1-8B-Instruct) are passed directly as test parameters.

3. Replacing hardcoded VL model check with hasattr(config, "text_config") and hasattr(config, "vision_config") for generic detection.

4. Unifying ~6k lines of near-identical YAML into shared base configs with per-model overrides:

   • validate_model_defaults.yaml, validate_solutions_defaults.yaml — shared validation params
   • pruning/pruning_defaults.yaml, pruning/ffn_pruning_base.yaml, pruning/attn_pruning.yaml, pruning/hidden_dim_pruning.yaml — shared pruning bases
   • Per-model dirs now follow HF model card paths (meta-llama/Llama-3.1-8B-Instruct/) and contain only model-specific overrides (e.g. just the layer_descriptor._target_ class)

5. Removing hydra_config_subdir parameter from test parametrize — config path is derived from hf_model_name directly.

6. Removing unused bypass: entries from all per-model main YAMLs.

Usage

# Test parametrize now uses HF model names directly:
("meta-llama/Llama-3.1-8B-Instruct", "llama", None, False),

Testing

All 8 parametrized test cases in test_puzzletron.py pass:

• meta-llama/Llama-3.1-8B-Instruct
• meta-llama/Llama-3.2-3B-Instruct
• Qwen/Qwen2.5-7B-Instruct
• Qwen/Qwen3-8B
• Qwen/Qwen3-VL-30B-A3B-Instruct
• mistralai/Mistral-Small-24B-Instruct-2501
• nvidia/NVIDIA-Nemotron-Nano-12B-v2
• nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16

CI Job: https://github.com/NVIDIA/Model-Optimizer/actions/runs/23087216443/job/67065820836

Before your PR is "Ready for review"

• Is this change backward compatible?: N/A (test-only changes)
• If you copied code from any other source, did you follow IP policy in CONTRIBUTING.md?: N/A
• Did you write any new necessary tests?: N/A (refactoring existing tests)
• Did you update Changelog?: N/A

Additional Information

Hydra packaging notes (non-obvious fixes required):

• Added # @package _global_ to all per-model main YAMLs — needed when config_name contains path separators, otherwise Hydra nests all keys under the org/model package
• Added @_here_ to sub-defaults inside pruning/ configs — prevents Hydra from compounding the pruning package at each inheritance level (pruning → pruning.pruning → pruning.pruning.pruning)
• Moved hydra/hydra_logging=disabled from YAML defaults list to overrides= in puzzletron.py — the YAML override syntax broke with nested config paths

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