Activation hooks redesign (reuse hooks component across both minitron and puzzletron) (#1022)

### What does this PR do?

Type of change: Redesign of existing feature

This PR introduces a shared activation hooks infrastructure for minitron
and puzzletron. The activation hooks framework provides a reusable
component for collecting and analyzing activations during forward
passes, which is used by both minitron pruning and puzzletron
algorithms.


Note! Minitron megatron.py/mcore_minitron.py:ImportanceEstimatorRegistry
code does not use this component yet - will be refactored in a separate
MR.

**Key changes:**
- Added `modelopt/torch/prune/importance_hooks` module with base hooks
framework:
- `base_hooks.py`: Core hook infrastructure for registering and managing
forward hooks
- `base_hooks_analysis.py`: Analysis utilities for processing collected
activations
  - `megatron_hooks.py`: Megatron-specific hook implementations
  - `compare_module_outputs.py`: Utilities for comparing module outputs

- Added unit tests in `tests/gpu/torch/prune/importance_hooks`:
  - `test_base_hooks.py`: Tests for base hooks functionality
- `test_base_hooks_analysis.py`: Tests for activation analysis utilities
- Updated `test_mcore_gpt_minitron_pruning.py` to validate activation
collection
- Updated test utilities for distributed testing support

### Before your PR is "*Ready for review*"

- Is this change backward compatible?: ✅ Yes - This is a new module that
doesn't affect existing functionality
- If you copied code from any other sources or added a new PIP
dependency, did you follow guidance in `CONTRIBUTING.md`: ✅ No
- Did you write any new necessary tests?: ✅ Yes - Added comprehensive
tests for the activation hooks infrastructure
- Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?:
✅ N/A - This is infrastructure code that will be used by subsequent PRs

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **New Features**
  * Robust JSON utilities for complex objects.
  * Flushed-print helper for synchronized output.
* Activation-based importance estimation framework with multiple hook
implementations, Megatron plugin support, and layer-output comparison
tools.
  * Project-root test fixture for test suites.

* **Tests**
* Many new end-to-end tests validating hooks, evaluation metrics, and
multi-layer output comparisons.
* Improved pruning tests with deterministic initialization and
additional statistical assertions.

* **Chores**
* Tests: mirror rank/size into environment for test init and disable
external telemetry.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Daniel Korzekwa <dkorzekwa@nvidia.com>
Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
Co-authored-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>

Author: danielkorzekwa

modelopt/torch/prune/importance_hooks/__init__.py

@@ -0,0 +1,23 @@
+# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Forward hooks for estimating importance scores for pruning."""
+
+from modelopt.torch.utils import import_plugin
+
+from .base_hooks import *
+from .base_hooks_analysis import *
+
+with import_plugin("megatron_hooks"):
+    from .plugins.megatron_hooks import *