From 176de97474931c9c69404295b655054e7fe85e15 Mon Sep 17 00:00:00 2001 From: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com> Date: Wed, 22 Apr 2026 09:34:01 -0700 Subject: [PATCH 1/2] docs: update installation pages with legal-approved license notices Add Legal-approved third-party software notice to pip install sections and a generic container license review notice to all installation docs (Linux, Windows, README). Co-Authored-By: Claude Sonnet 4.6 Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com> --- README.md | 12 ++++++++++-- .../_installation_for_Linux.rst | 19 ++++++++++++------- .../windows/_installation_for_Windows.rst | 4 ++++ 3 files changed, 26 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index df46a075215..f16d69813f7 100644 --- a/README.md +++ b/README.md @@ -69,6 +69,8 @@ To install stable release packages for Model Optimizer with `pip` from [PyPI](ht pip install -U nvidia-modelopt[all] ``` +Model Optimizer will download and install additional third-party open source software projects. Review the license terms of these open source projects before use. + To install from source in editable mode with all development dependencies or to use the latest features, run: ```bash @@ -79,8 +81,14 @@ cd Model-Optimizer pip install -e .[dev] ``` -You can also directly use the [TensorRT-LLM docker images](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags) -(e.g., `nvcr.io/nvidia/tensorrt-llm/release:`), which have Model Optimizer pre-installed. +You can also directly use NVIDIA container images, which have Model Optimizer pre-installed: + +- `nvcr.io/nvidia/pytorch:-py3` +- `nvcr.io/nvidia/nemo:` +- `nvcr.io/nvidia/tensorrt-llm/release:` +- `nvcr.io/nvidia/tensorrt:-py3` + +Before pulling and using the container images, please review their respective license terms. Make sure to upgrade Model Optimizer to the latest version as described above. Visit our [installation guide](https://nvidia.github.io/Model-Optimizer/getting_started/2_installation.html) for more fine-grained control on installed dependencies or for alternative docker images and environment variables to setup. diff --git a/docs/source/getting_started/_installation_for_Linux.rst b/docs/source/getting_started/_installation_for_Linux.rst index 2b2d4d8219b..a18b45ee7c4 100644 --- a/docs/source/getting_started/_installation_for_Linux.rst +++ b/docs/source/getting_started/_installation_for_Linux.rst @@ -32,11 +32,11 @@ Environment setup To use Model Optimizer with full dependencies (e.g. TensorRT/TensorRT-LLM deployment), we recommend using the `TensorRT-LLM docker image `_, - e.g., ``nvcr.io/nvidia/tensorrt-llm/release:``. + e.g., ``nvcr.io/nvidia/tensorrt-llm/release:`` (Model Optimizer pre-installed). Make sure to upgrade Model Optimizer to the latest version using ``pip`` as described in the next section. - You would also need to setup appropriate environment variables for the TensorRT binaries as follows: + If relevant, you would also need to setup appropriate environment variables for the TensorRT binaries as follows: .. code-block:: shell @@ -48,11 +48,16 @@ Environment setup **Alternative NVIDIA docker images** For PyTorch, you can also use `NVIDIA NGC PyTorch container `_ - and for NVIDIA Megatron-Bridge or Megatron-LM framework, you can use the `NeMo container `_. - Both of these containers come with Model Optimizer pre-installed. Make sure to update the Model Optimizer to the latest version if not already. + (``nvcr.io/nvidia/pytorch:-py3``, Model Optimizer pre-installed) + and for NVIDIA Megatron-Bridge or Megatron-LM framework, you can use the `NeMo container `_ + (``nvcr.io/nvidia/nemo:``, Model Optimizer pre-installed). + Make sure to update the Model Optimizer to the latest version if not already. For ONNX / TensorRT use cases, you can also use the `TensorRT container `_ - which provides superior performance to the PyTorch container. + (``nvcr.io/nvidia/tensorrt:-py3``), which provides superior performance to the PyTorch container. + + .. note:: + Before pulling and using the container images, please review their respective license terms. .. tab:: Local environment (PIP / Conda) @@ -82,8 +87,8 @@ Environment setup Install Model Optimizer ======================= -ModelOpt including its dependencies can be installed via ``pip``. Please review the license terms of ModelOpt and any -dependencies before use. +Model Optimizer will download and install additional third-party open source software projects. Review the license +terms of these open source projects before use. If you build and use ModelOpt's docker image, you can skip this step as the image already contains ModelOpt and all optional dependencies pre-installed. diff --git a/docs/source/getting_started/windows/_installation_for_Windows.rst b/docs/source/getting_started/windows/_installation_for_Windows.rst index f68ee90b5dd..1925f610f68 100644 --- a/docs/source/getting_started/windows/_installation_for_Windows.rst +++ b/docs/source/getting_started/windows/_installation_for_Windows.rst @@ -30,6 +30,10 @@ The following system requirements are necessary to install and use Model Optimiz The Model Optimizer - Windows can be used in following ways: +.. note:: + Model Optimizer will download and install additional third-party open source software projects. + Review the license terms of these open source projects before use. + .. toctree:: :glob: :maxdepth: 1 From 78b6fe20e6ec7a55045345ffbac9199abd096e70 Mon Sep 17 00:00:00 2001 From: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com> Date: Wed, 22 Apr 2026 09:43:12 -0700 Subject: [PATCH 2/2] Update License header copyright year Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com> --- LICENSE_HEADER | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/LICENSE_HEADER b/LICENSE_HEADER index 7b0d9f06b06..9031d2eca55 100644 --- a/LICENSE_HEADER +++ b/LICENSE_HEADER @@ -1,4 +1,4 @@ -SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: Apache-2.0 Licensed under the Apache License, Version 2.0 (the "License");