Add activation hooks used for pruning (#576)

## What does this PR do?

Add activation hooks used for pruning

---------

Signed-off-by: Daniel Korzekwa <dkorzekwa@nvidia.com>

Author: danielkorzekwa

examples/compress/README.md

@@ -29,7 +29,7 @@ pip install -e .[hf,compress]
    How to choose `intermediate_size_list`?
    The list specifies the candidate FFN sizes that we wish to search over. It is recommended to choose several pruning sizes (e.g. 15%, 20%, 30% etc of the original). Note that the values must be hardware-friendly (divisible by a 256) to avoid issues with tensor operations in subsequent steps.
 
-   Let's first shoot for 32% GPU memory reduction setting `target_memory = 78_000` GiB. This means that the algorithm will choose the candidates with highest accuracy that also meet the specified requirements.
+   Let's first shoot for 32% GPU memory reduction setting `target_memory = 78_000` MiB. This means that the algorithm will choose the candidates with highest accuracy that also meet the specified requirements.
 
 2. Download and prepare the [Nemotron-Post-Training-Dataset-v2](https://huggingface.co/datasets/nvidia/Nemotron-Post-Training-Dataset-v2).
 

modelopt/torch/_compress/activation_scoring/activation_hooks/__init__.py

@@ -0,0 +1,15 @@
+# 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.
+