[6.4.2] Docs: removal of migrated deep learning frameworks (#6089 )

Taichi removed (#5802 )
bump rocm-docs-core to 1.26.0
2026-03-31 15:47:17 -04:00 · 2025-12-19 15:44:03 -05:00 · 2025-10-14 11:36:26 -04:00 · 2025-08-18 10:20:12 -04:00 · 2025-08-12 14:25:54 -04:00 · 2025-08-01 15:21:17 -04:00
29 changed files with 517 additions and 412 deletions
@@ -6,7 +6,7 @@ version: 2
 sphinx:
   configuration: docs/conf.py

-formats: [htmlzip]
+formats: [htmlzip, pdf]

 python:
   install:
@@ -45,6 +45,7 @@ Bootloader
 CAS
 CCD
 CDNA
+CGUI
 CHTML
 CIFAR
 CLI
@@ -115,6 +116,7 @@ DevCap
 DirectX
 Dockerfile
 Doxygen
+dropless
 ELMo
 ENDPGM
 EPYC
@@ -270,6 +272,7 @@ Makefiles
 Matplotlib
 Matrox
 MaxText
+Megablocks
 Megatrends
 Megatron
 Mellanox
@@ -279,6 +282,7 @@ Miniconda
 MirroredStrategy
 Mixtral
 MosaicML
+MoEs
 Mpops
 Multicore
 Multithreaded
@@ -408,6 +412,7 @@ SDMA
 SDPA
 SDRAM
 SENDMSG
+SGLang
 SGPR
 SGPRs
 SHA
@@ -863,6 +868,7 @@ seealso
 sendmsg
 seqs
 serializers
+sglang
 shader
 sharding
 sigmoid
@@ -83,8 +83,6 @@ ROCm documentation continues to be updated to provide clearer and more comprehen
 * ROCm provides a comprehensive ecosystem for deep learning development. For more details, see [Deep learning frameworks for ROCm](https://rocm.docs.amd.com/en/docs-6.4.2/how-to/deep-learning-rocm.html). As of July 2025, AMD ROCm provides support for the following additional deep learning frameworks:

    * Deep Graph Library is an easy-to-use, high-performance, and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component in an end-to-end application, the rest of the logic is implemented using PyTorch. It is currently supported on ROCm 6.4.0. For more information, see [DGL compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/dgl-compatibility.html).
-    * Stanford Megatron-LM is a large-scale language model training framework. It’s designed to train massive transformer-based language models efficiently by model and data parallelism. It is currently supported on ROCm 6.3.0. For more information, see [Stanford Megatron-LM compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html).
-    * Volcano Engine Reinforcement Learning for LLMs (verl) is a reinforcement learning framework designed for large language models (LLMs). verl offers a scalable, open-source fine-tuning solution optimized for AMD Instinct GPUs with full ROCm support. It is currently supported on ROCm 6.2.0. For more information, see [verl compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/verl-compatibility.html).

 * Documentation for the new [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/docs-6.4.2/) was added in May 2025. This tool is used to visualize and analyze GPU thread trace data collected using [rocprofv3](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/index.html). Note that [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/docs-6.4.2/) is in an early access state. Running production workloads is not recommended.

@@ -30,9 +30,7 @@ ROCm Version,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0,
      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13"
      :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.14.0, 2.13.1, 2.12.1","2.14.0, 2.13.1, 2.12.1"
      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
-      :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`,2.4.0,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_,N/A,N/A,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.2,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
 ,,,,,,,,,,,,,,,,,
      ,,,,,,,,,,,,,,,,,
@@ -55,8 +55,6 @@ compatibility and system requirements.
      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 2.1, 2.0, 1.13"
      :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1"
      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.31  
-      :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`,N/A,N/A,85f95ae
-      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`,2.4.0,2.4.0,N/A
      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.17.3
      ,,,
      THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix:,,
@@ -240,7 +238,7 @@ Expand for full historical view of:
   .. [#mi300_610-past-60] **For ROCm 6.1.0** - MI300A (gfx942) is supported on Ubuntu 22.04.4, RHEL 9.4, RHEL 9.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.4.
   .. [#mi300_602-past-60] **For ROCm 6.0.2** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
   .. [#mi300_600-past-60] **For ROCm 6.0.0** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
-   .. [#verl_compat] verl is only supported on ROCm 6.2.0.
+   .. [#dgl_compat] DGL is only supported on ROCm 6.4.0.
   .. [#kfd_support-past-60] As of ROCm 6.4.0, forward and backward compatibility between the AMD Kernel-mode GPU Driver (KMD) and its user space software is provided up to a year apart. For earlier ROCm releases, the compatibility is provided for +/- 2 releases. The tested user space versions on this page were accurate as of the time of initial ROCm release. For the most up-to-date information, see the latest version of this information at `User and kernel-space support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.
   .. [#ROCT-rocr-past-60] Starting from ROCm 6.3.0, the ROCT Thunk Interface is included as part of the ROCr runtime package.
   
@@ -42,16 +42,16 @@ GAT, GCN and GraphSage. Using these we can support a variety of use-cases such a
 - 1D (Temporal) and 2D (Image) Classification
 - Drug Discovery

-Refer to :doc:`ROCm DGL blog posts <https://rocm.blogs.amd.com/blog/tag/dgl.html>` 
-for examples and best practices to optimize your training workflows on AMD GPUs. 
+Multiple use cases of DGL have been tested and verified.
+However, a recommended example follows a drug discovery pipeline using the ``SE3Transformer``.
+Refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`_, 
+where you can search for DGL examples and best practices to optimize your training workflows on AMD GPUs. 

 Coverage includes:

 - Single-GPU training/inference
 - Multi-GPU training

-Benchmarking details are included in the :doc:`Benchmarks` section.
-

 .. _dgl-docker-compat:

@@ -252,4 +252,4 @@ Unsupported functions
 * ``gather_mm_idx_b``
 * ``pgexplainer``
 * ``sample_labors_prob``
-* ``sample_labors_noprob``
+* ``sample_labors_noprob``
@@ -97,7 +97,7 @@ Docker image compatibility
 AMD validates and publishes ready-made `ROCm JAX Docker images <https://hub.docker.com/r/rocm/jax>`_
 with ROCm backends on Docker Hub. The following Docker image tags and
 associated inventories represent the latest JAX version from the official Docker Hub and are validated for
-`ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`_. Click the |docker-icon|
+`ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`_. Click the |docker-icon|
 icon to view the image on Docker Hub.

 .. list-table:: JAX Docker image components
@@ -110,7 +110,7 @@ icon to view the image on Docker Hub.

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.1-jax0.4.35-py3.12/images/sha256-7a0745a2a2758bdf86397750bac00e9086cbf67d170cfdbb08af73f7c7d18a6a"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
+           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.2-jax0.4.35-py3.12/images/sha256-8918fa806a172c1a10eb2f57131eb31b5d7c8fa1656b8729fe7d3d736112de83"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>

      - `0.4.35 <https://github.com/ROCm/jax/releases/tag/rocm-jax-v0.4.35>`_
      - Ubuntu 24.04
@@ -118,7 +118,7 @@ icon to view the image on Docker Hub.

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.1-jax0.4.35-py3.10/images/sha256-5f9e8d6e6e69fdc9a1a3f2ba3b1234c3f46c53b7468538c07fd18b00899da54f"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
+           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.2-jax0.4.35-py3.10/images/sha256-a394be13c67b7fc602216abee51233afd4b6cb7adaa57ca97e688fba82f9ad79"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>

      - `0.4.35 <https://github.com/ROCm/jax/releases/tag/rocm-jax-v0.4.35>`_
      - Ubuntu 22.04
@@ -95,7 +95,7 @@ Docker image compatibility

 AMD validates and publishes `PyTorch images <https://hub.docker.com/r/rocm/pytorch>`__
 with ROCm backends on Docker Hub. The following Docker image tags and associated
-inventories were tested on `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__.
+inventories were tested on `ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__.
 Click |docker-icon| to view the image on Docker Hub.

 .. list-table:: PyTorch Docker image components
@@ -112,127 +112,118 @@ Click |docker-icon| to view the image on Docker Hub.
      - MAGMA
      - UCX
      - OMPI
-      - OFED

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-c76af9bfb1c25b0f40d4c29e8652105c57250bf018d23ff595b06bd79666fdd7"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-6a287591500b4048a9556c1ecc92bc411fd3d552f6c8233bc399f18eb803e8d6"><i class="fab fa-docker fa-lg"></i></a>

      - `2.6.0 <https://github.com/ROCm/pytorch/tree/release/2.6>`__
      - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `1.6.0 <https://github.com/ROCm/apex/tree/release/1.6.0>`__
      - `0.21.0 <https://github.com/pytorch/vision/tree/v0.21.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
-      - `1.16.0 <https://github.com/openucx/ucx/tree/v1.16.0>`__
+      - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
      - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.6.0/images/sha256-f9d226135d51831c810dcb1251636ec61f85c65fcdda03e188c053a5d4f6585b"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.6.0/images/sha256-06b967629ba6657709f04169832cd769a11e6b491e8b1394c361d42d7a0c8b43"><i class="fab fa-docker fa-lg"></i></a>

      - `2.6.0 <https://github.com/ROCm/pytorch/tree/release/2.6>`__
      - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
      - `1.6.0 <https://github.com/ROCm/apex/tree/release/1.6.0>`__
      - `0.21.0 <https://github.com/pytorch/vision/tree/v0.21.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.5.1/images/sha256-3490e74d4f43dcdb3351dd334108d1ccd47e5a687c0523a2424ac1bcdd3dd6dd"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.5.1/images/sha256-62022414217ef6de33ac5b1341e57db8a48e8573fa2ace12d48aa5edd4b99ef0"><i class="fab fa-docker fa-lg"></i></a>

      - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
      - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
      - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.10.0>`__
      - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.5.1/images/sha256-26c5dfffb4a54625884abca83166940f17dd27bc75f1b24f6e80fbcb7d4e9afb"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.11_pytorch_release_2.5.1/images/sha256-469a7f74fc149aff31797e011ee41978f6a190adc69fa423b3c6a718a77bd985"><i class="fab fa-docker fa-lg"></i></a>

      - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
      - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.11 <https://www.python.org/downloads/release/python-31113/>`__
      - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
      - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-f378a24561fa6efc178b6dc93fc7d82e5b93653ecd59c89d4476674d29e1284d"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.5.1/images/sha256-37f41a1cd94019688669a1b20d33ea74156e0c129ef6b8270076ef214a6a1a2c"><i class="fab fa-docker fa-lg"></i></a>
+
+      - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
+      - 22.04
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
+      - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
+      - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
+      - `master <https://bitbucket.org/icl/magma/src/master/>`__
+      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
+      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-60824ba83dc1b9d94164925af1f81c0235c105dd555091ec04c57e05177ead1b"><i class="fab fa-docker fa-lg"></i></a>

      - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
      - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `1.4.0 <https://github.com/ROCm/apex/tree/release/1.4.0>`__
      - `0.19.0 <https://github.com/pytorch/vision/tree/v0.19.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
      - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-2308dbd0e650b7bf8d548575cbb6e2bdc021f9386384ce570da16d58ee684d22"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-fe944fe083312f901be6891ab4d3ffebf2eaf2cf4f5f0f435ef0b76ec714fabd"><i class="fab fa-docker fa-lg"></i></a>

      - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
      - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
      - `1.4.0 <https://github.com/ROCm/apex/tree/release/1.4.0>`__
      - `0.19.0 <https://github.com/pytorch/vision/tree/v0.19.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.3.0/images/sha256-eefd2ab019728f91f94c5e6a9463cb0ea900b3011458d18fe5d88e50c0b57d86"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.3.0/images/sha256-1d59251c47170c5b8960d1172a4dbe52f5793d8966edd778f168eaf32d56661a"><i class="fab fa-docker fa-lg"></i></a>

      - `2.3.0 <https://github.com/ROCm/pytorch/tree/release/2.3>`__
      - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `1.3.0 <https://github.com/ROCm/apex/tree/release/1.3.0>`__
      - `0.18.0 <https://github.com/pytorch/vision/tree/v0.18.0>`__
      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13>`__
      - `master <https://bitbucket.org/icl/magma/src/master/>`__
      - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
      - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.3.0/images/sha256-473643226ab0e93a04720b256ed772619878abf9c42b9f84828cefed522696fd"><i class="fab fa-docker fa-lg"></i></a>
-
-      - `2.3.0 <https://github.com/ROCm/pytorch/tree/release/2.3>`__
-      - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `1.3.0 <https://github.com/ROCm/apex/tree/release/1.3.0>`__
-      - `0.18.0 <https://github.com/pytorch/vision/tree/v0.18.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13>`__
-      - `master <https://bitbucket.org/icl/magma/src/master/>`__
-      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
-      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__

 Key ROCm libraries for PyTorch
 ================================================================================
@@ -1,100 +0,0 @@
-:orphan:
-
-.. meta::
-    :description: Stanford Megatron-LM compatibility
-    :keywords: Stanford, Megatron-LM, compatibility
-
-.. version-set:: rocm_version latest
-
-********************************************************************************
-Stanford Megatron-LM compatibility
-********************************************************************************
-
-Stanford Megatron-LM is a large-scale language model training framework developed by NVIDIA `https://github.com/NVIDIA/Megatron-LM <https://github.com/NVIDIA/Megatron-LM>`_. It is
-designed to train massive transformer-based language models efficiently by model and data parallelism. 
-
-* ROCm support for Stanford Megatron-LM is hosted in the official `https://github.com/ROCm/Stanford-Megatron-LM <https://github.com/ROCm/Stanford-Megatron-LM>`_ repository. 
-* Due to independent compatibility considerations, this location differs from the `https://github.com/stanford-futuredata/Megatron-LM <https://github.com/stanford-futuredata/Megatron-LM>`_ upstream repository. 
-* Use the prebuilt :ref:`Docker image <megatron-lm-docker-compat>` with ROCm, PyTorch, and Megatron-LM preinstalled. 
-* See the :doc:`ROCm Stanford Megatron-LM installation guide <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>` to install and get started.
-
-.. note::
-
-	Stanford Megatron-LM is supported on ROCm 6.3.0.
-
-
-Supported Devices
-================================================================================
-
- **Officially Supported**: AMD Instinct MI300X
- **Partially Supported** (functionality or performance limitations): AMD Instinct MI250X, MI210X
-
-
-Supported models and features
-================================================================================
-
-This section details models & features that are supported by the ROCm version on Stanford Megatron-LM.
-
-Models:
-
-* Bert
-* GPT
-* T5
-* ICT
-
-Features:
-
-* Distributed Pre-training
-* Activation Checkpointing and Recomputation
-* Distributed Optimizer
-* Mixture-of-Experts
-
-.. _megatron-lm-recommendations:
-
-Use cases and recommendations
-================================================================================
-
-See the `Efficient MoE training on AMD ROCm: How-to use Megablocks on AMD GPUs blog <https://rocm.blogs.amd.com/artificial-intelligence/megablocks/README.html>`_ post  
-to leverage the ROCm platform for pre-training by using the Stanford Megatron-LM framework of pre-processing datasets on AMD GPUs. 
-Coverage includes:
-
-  * Single-GPU pre-training
-  * Multi-GPU pre-training
-
-
-.. _megatron-lm-docker-compat:
-
-Docker image compatibility
-================================================================================
-
-.. |docker-icon| raw:: html
-
-   <i class="fab fa-docker"></i>
-
-AMD validates and publishes `Stanford Megatron-LM images <https://hub.docker.com/r/rocm/megatron-lm>`_
-with ROCm and Pytorch backends on Docker Hub. The following Docker image tags and associated
-inventories represent the latest Megatron-LM version from the official Docker Hub.
-The Docker images have been validated for `ROCm 6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_.
-Click |docker-icon| to view the image on Docker Hub.
-
-.. list-table:: 
-    :header-rows: 1
-    :class: docker-image-compatibility
-
-    * - Docker image
-      - Stanford Megatron-LM
-      - PyTorch
-      - Ubuntu
-      - Python
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/stanford-megatron-lm/stanford-megatron-lm85f95ae_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-070556f078be10888a1421a2cb4f48c29f28b02bfeddae02588d1f7fc02a96a6"><i class="fab fa-docker fa-lg"></i></a>
-
-      - `85f95ae <https://github.com/stanford-futuredata/Megatron-LM/commit/85f95aef3b648075fe6f291c86714fdcbd9cd1f5>`_
-      - `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
-      - 24.04
-      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
-
-      
-
@@ -56,7 +56,7 @@ Docker image compatibility
 AMD validates and publishes ready-made `TensorFlow images
 <https://hub.docker.com/r/rocm/tensorflow>`__ with ROCm backends on
 Docker Hub. The following Docker image tags and associated inventories are
-validated for `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__. Click
+validated for `ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__. Click
 the |docker-icon| icon to view the image on Docker Hub.

 .. list-table:: TensorFlow Docker image components
@@ -65,128 +65,61 @@ the |docker-icon| icon to view the image on Docker Hub.
    * - Docker image
      - TensorFlow
      - Ubuntu
-      - Dev
      - Python
      - TensorBoard

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4-py3.12-tf2.18-dev/images/sha256-fa9cf5fa6c6079a7118727531ccd0056c6e3224a42c3d6e78a49e7781daafff4"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.18-dev/images/sha256-96754ce2d30f729e19b497279915b5212ba33d5e408e7e5dd3f2304d87e3441e"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.18-runtime/images/sha256-d14d8c4989e7c9a60f4e72461b9e349de72347c6162dcd6897e6f4f80ffbb440"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.18-dev/images/sha256-fa741508d383858e86985a9efac85174529127408102558ae2e3a4ac894eea1e"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
+      - 22.04
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.18-dev/images/sha256-081e5bd6615a5dc17247ebd2ccc26895c3feeff086720400fa39b477e60a77c0"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.17-dev/images/sha256-3a0aef09f2a8833c2b64b85874dd9449ffc2ad257351857338ff5b706c03a418"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - dev
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.18-runtime/images/sha256-bf369637378264f4af6ddad5ca8b8611d3e372ffbea9ab7a06f1e122f0a0867b"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.17-dev/images/sha256-5a502008c50d0b6508e6027f911bdff070a7493700ae064bed74e1d22b91ed50"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.17-runtime/images/sha256-1ee5dfffceb71ac66617ada33de3a10de0cb74199cc4b82441192e5e92fa2ddf"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.17-dev/images/sha256-bc7341a41ebe7ab261aa100732874507c452421ef733e408ac4f05ed453b0bc5"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-3124/>`__
-      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.17-dev/images/sha256-109218ad92bfae83bbd2710475f7502166e1ed54ca0b9748a9cbc3f5a1d75af1"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.17.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.17-runtime/images/sha256-5d78bd5918d394f92263daa2990e88d695d27200dd90ed83ec64d20c7661c9c1"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.16-dev/images/sha256-4841a8df7c340dab79bf9362dad687797649a00d594e0832eb83ea6880a40d3b"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.17.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.16-dev/images/sha256-b09b1ad921c09c687b7c916141051e9fcf15539a5686e5aa67c689195a522719"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.16-runtime/images/sha256-20dbd824e85558abfe33fc9283cc547d88cde3c623fe95322743a5082f883a64"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.16-dev/images/sha256-883fa95aba960c58a3e46fceaa18f03ede2c7df89b8e9fd603ab2d47e0852897"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>

-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
-      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-dev/images/sha256-36c4fa047c86e2470ac473ec1429aea6d4b8934b90ffeb34d1afab40e7e5b377"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-dev/images/sha256-36c4fa047c86e2470ac473ec1429aea6d4b8934b90ffeb34d1afab40e7e5b377>`__
-      - dev
+      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.16.2-cp310-cp310-manylinux_2_28_x86_64.whl>`__
      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-runtime/images/sha256-a94150ffb81365234ebfa34e764db5474bc6ab7d141b56495eac349778dafcf3"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__


@@ -1,85 +0,0 @@
-:orphan:
-
-.. meta::
-   :description: verl compatibility
-   :keywords: GPU, verl compatibility
-
-.. version-set:: rocm_version latest
-
-*******************************************************************************
-verl compatibility
-*******************************************************************************
-
-Volcano Engine Reinforcement Learning for LLMs (verl) is a reinforcement learning framework designed for large language models (LLMs). 
-verl offers a scalable, open-source fine-tuning solution optimized for AMD Instinct GPUs with full ROCm support.
-
-* See the `verl documentation <https://verl.readthedocs.io/en/latest/>`_ for more information about verl. 
-* The official verl GitHub repository is `https://github.com/volcengine/verl <https://github.com/volcengine/verl>`_.
-* Use the AMD-validated :ref:`Docker images <verl-docker-compat>` with ROCm and verl preinstalled. 
-* See the :doc:`ROCm verl installation guide <rocm-install-on-linux:install/3rd-party/verl-install>` to get started.
-
-.. note::
-
-	verl is supported on ROCm 6.2.0.
-
-
-.. _verl-recommendations:
-
-Use cases and recommendations
-================================================================================
-
-The benefits of verl in large-scale reinforcement leaning from human feedback (RLHF) are discussed in the `Reinforcement Learning from Human Feedback on AMD GPUs with verl and ROCm Integration <https://rocm.blogs.amd.com/artificial-intelligence/verl-large-scale/README.html>`_ blog.
-
-.. _verl-docker-compat:
-
-Docker image compatibility
-================================================================================
-
-.. |docker-icon| raw:: html
-
-   <i class="fab fa-docker"></i>
-
-AMD validates and publishes ready-made `ROCm verl Docker images <https://hub.docker.com/r/rocm/verl>`_
-with ROCm backends on Docker Hub. The following Docker image tags and associated inventories represent the latest verl version from the official Docker Hub. The Docker images have been validated for `ROCm 6.2.0 <https://repo.radeon.com/rocm/apt/6.2/>`_. 
-
-.. list-table:: 
-    :header-rows: 1
-
-    *   - Docker image
-        - verl
-        - Linux
-        - Pytorch
-        - Python
-        - vllm
-
-    *   - .. raw:: html
-
-            <a href="https://hub.docker.com/layers/rocm/verl/verl-0.3.0.post0_rocm6.2_vllm0.6.3/images/sha256-cbe423803fd7850448b22444176bee06f4dcf22cd3c94c27732752d3a39b04b2"><i class="fab fa-docker fa-lg"></i> rocm/verl</a>
-        - `0.3.0post0 <https://github.com/volcengine/verl/releases/tag/v0.3.0.post0>`_
-        - Ubuntu 20.04
-        - `2.5.0 <https://download.pytorch.org/whl/cu118/torch-2.5.0%2Bcu118-cp39-cp39-linux_x86_64.whl#sha256=1ee24b267418c37b297529ede875b961e382c1c365482f4142af2398b92ed127>`_
-        - `3.9.19 <https://www.python.org/downloads/release/python-3919/>`_
-        - `0.6.4 <https://github.com/vllm-project/vllm/releases/tag/v0.6.4>`_
-
-
-Supported features
-===============================================================================
-
-The following table shows verl and ROCm support for GPU-accelerated modules.
-
-.. list-table::
-    :header-rows: 1
-
-    * - Module
-      - Description
-      - verl version
-      - ROCm version
-    * - ``FSDP``
-      - Training engine
-      - 0.3.0.post0
-      - 6.2
-    * - ``vllm``
-      - Inference engine
-      - 0.3.0.post0
-      - 6.2
-  
@@ -96,6 +96,7 @@ article_pages = [
    {"file": "compatibility/ml-compatibility/pytorch-compatibility", "os": ["linux"]},
    {"file": "compatibility/ml-compatibility/tensorflow-compatibility", "os": ["linux"]},
    {"file": "compatibility/ml-compatibility/jax-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/dgl-compatibility", "os": ["linux"]},
    {"file": "how-to/deep-learning-rocm", "os": ["linux"]},

    {"file": "how-to/rocm-for-ai/index", "os": ["linux"]},
@@ -1,6 +1,6 @@
 pytorch_inference_benchmark:
  unified_docker:
-    latest: &rocm-pytorch-docker-latest
+    latest:
      pull_tag: rocm/pytorch:latest
      docker_hub_url:
      rocm_version:
@@ -39,3 +39,11 @@ pytorch_inference_benchmark:
        model_repo: Wan-AI/Wan2.1-T2V-14B
        url: https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
        precision: bfloat16
+    - group: Janus-Pro
+      tag: janus-pro
+      models:
+      - model: Janus Pro 7B
+        mad_tag: pyt_janus_pro_inference
+        model_repo: deepseek-ai/Janus-Pro-7B
+        url: https://huggingface.co/deepseek-ai/Janus-Pro-7B
+        precision: bfloat16
@@ -0,0 +1,17 @@
+sglang_benchmark:
+  unified_docker:
+    latest:
+      pull_tag: lmsysorg/sglang:v0.4.5-rocm630
+      docker_hub_url: https://hub.docker.com/layers/lmsysorg/sglang/v0.4.5-rocm630/images/sha256-63d2cb760a237125daf6612464cfe2f395c0784e21e8b0ea37d551cd10d3c951
+      rocm_version: 6.3.0
+      sglang_version: 0.4.5 (0.4.5-rocm)
+      pytorch_version: 2.6.0a0+git8d4926e
+  model_groups:
+    - group: DeepSeek
+      tag: deepseek
+      models:
+      - model: DeepSeek-R1-Distill-Qwen-32B
+        mad_tag: pyt_sglang_deepseek-r1-distill-qwen-32b
+        model_repo: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
+        url: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
+        precision: bfloat16
@@ -17,8 +17,6 @@ features for these ROCm-enabled deep learning frameworks.
 * :doc:`PyTorch compatibility <../compatibility/ml-compatibility/pytorch-compatibility>`
 * :doc:`TensorFlow compatibility <../compatibility/ml-compatibility/tensorflow-compatibility>`
 * :doc:`JAX compatibility <../compatibility/ml-compatibility/jax-compatibility>`
-* :doc:`verl compatibility <../compatibility/ml-compatibility/verl-compatibility>`
-* :doc:`Stanford Megatron-LM compatibility <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
 * :doc:`DGL compatibility <../compatibility/ml-compatibility/dgl-compatibility>`

 This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
@@ -32,8 +30,6 @@ See the installation instructions to get started.
 * :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
 * :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
 * :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
-* :doc:`verl for ROCm <rocm-install-on-linux:install/3rd-party/verl-install>`
-* :doc:`Stanford Megatron-LM for ROCm <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
 * :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/dgl-install>`

 .. note::
@@ -0,0 +1,25 @@
+:orphan:
+
+****************************************************
+SGLang inference performance testing version history
+****************************************************
+
+This table lists previous versions of the ROCm SGLang inference performance
+testing environment. For detailed information about available models for
+benchmarking, see the version-specific documentation.
+
+.. list-table::
+   :header-rows: 1
+
+   * - Docker image tag
+     - Components
+     - Resources
+
+   * - ``lmsysorg/sglang:v0.4.5-rocm630``
+     - 
+       * ROCm 6.3.0
+       * SGLang 0.4.5
+       * PyTorch 2.6.0
+     - 
+       * :doc:`Documentation <../sglang>`
+       * `Docker Hub <https://hub.docker.com/layers/lmsysorg/sglang/v0.4.5-rocm630/images/sha256-63d2cb760a237125daf6612464cfe2f395c0784e21e8b0ea37d551cd10d3c951>`__
@@ -103,7 +103,7 @@ PyTorch inference performance testing

         The Chai-1 benchmark uses a specifically selected Docker image using ROCm 6.2.3 and PyTorch 2.3.0 to address an accuracy issue.

-   .. container:: model-doc pyt_clip_inference pyt_mochi_video_inference pyt_wan2.1_inference
+   .. container:: model-doc pyt_clip_inference pyt_mochi_video_inference pyt_wan2.1_inference pyt_janus_pro_inference

      Use the following command to pull the `ROCm PyTorch Docker image <https://hub.docker.com/layers/rocm/pytorch/latest/images/sha256-05b55983e5154f46e7441897d0908d79877370adca4d1fff4899d9539d6c4969>`__ from Docker Hub.

@@ -140,22 +140,27 @@ PyTorch inference performance testing
      .. code-block:: shell

         export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-         python3 tools/run_models.py --tags {{model.mad_tag}} --keep-model-dir --live-output --timeout 28800
+         madengine run \
+             --tags {{model.mad_tag}} \
+             --keep-model-dir \
+             --live-output \
+             --timeout 28800

      MAD launches a Docker container with the name
      ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
-      model are collected in ``perf.csv``.
+      model are collected in ``perf_{{model.mad_tag}}.csv``.

+      {% if model.mad_tag != "pyt_janus_pro_inference" %}
      .. note::

         For improved performance, consider enabling TunableOp. By default,
         ``{{model.mad_tag}}`` runs with TunableOp disabled (see
         `<https://github.com/ROCm/MAD/blob/develop/models.json>`__). To enable
-         it, edit the default run behavior in the ``tools/run_models.py``-- update the model's
-         run ``args`` by changing ``--tunableop off`` to ``--tunableop on``.
+         it, include the ``--tunableop on`` argument in your run.

         Enabling TunableOp triggers a two-pass run -- a warm-up followed by the performance-collection run.
         Although this might increase the initial training time, it can result in a performance gain.
+      {% endif %}

      {% endfor %}
   {% endfor %}
@@ -163,8 +168,10 @@ PyTorch inference performance testing
 Further reading
 ===============

+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
 - To learn more about system settings and management practices to configure your system for
-  MI300X accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.

 - For application performance optimization strategies for HPC and AI workloads,
  including inference with vLLM, see :doc:`../../inference-optimization/workload`.
@@ -0,0 +1,280 @@
+.. meta::
+   :description: Learn how to validate LLM inference performance on MI300X accelerators using AMD MAD and SGLang
+   :keywords: model, MAD, automation, dashboarding, validate
+
+************************************
+SGLang inference performance testing
+************************************
+
+.. _sglang-benchmark-unified-docker:
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/sglang-benchmark-models.yaml
+
+   {% set unified_docker = data.sglang_benchmark.unified_docker.latest %}
+
+   `SGLang <https://docs.sglang.ai>`__ is a high-performance inference and
+   serving engine for large language models (LLMs) and vision models. The
+   ROCm-enabled `SGLang Docker image <{{ unified_docker.docker_hub_url }}>`__
+   bundles SGLang with PyTorch, optimized for AMD Instinct MI300X series
+   accelerators. It includes the following software components:
+
+   .. list-table::
+      :header-rows: 1
+
+      * - Software component
+        - Version
+
+      * - `ROCm <https://github.com/ROCm/ROCm>`__
+        - {{ unified_docker.rocm_version }}
+
+      * - `SGLang <https://docs.sglang.ai/index.html>`__
+        - {{ unified_docker.sglang_version }} 
+
+      * - `PyTorch <https://github.com/pytorch/pytorch>`__
+        - {{ unified_docker.pytorch_version }} 
+
+System validation
+=================
+
+Before running AI workloads, it's important to validate that your AMD hardware is configured
+correctly and performing optimally.
+
+If you have already validated your system settings, including aspects like NUMA auto-balancing, you
+can skip this step. Otherwise, complete the procedures in the :ref:`System validation and
+optimization <rocm-for-ai-system-optimization>` guide to properly configure your system settings
+before starting training.
+
+To test for optimal performance, consult the recommended :ref:`System health benchmarks
+<rocm-for-ai-system-health-bench>`. This suite of tests will help you verify and fine-tune your
+system's configuration.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/sglang-benchmark-models.yaml
+
+   {% set unified_docker = data.sglang_benchmark.unified_docker.latest %}
+   {% set model_groups = data.sglang_benchmark.model_groups %}
+
+   Pull the Docker image
+   =====================
+
+   Download the `SGLang Docker image <{{ unified_docker.docker_hub_url }}>`__.
+   Use the following command to pull the Docker image from Docker Hub.
+
+   .. code-block:: shell
+
+      docker pull {{ unified_docker.pull_tag }}
+
+   Benchmarking
+   ============
+
+   Once the setup is complete, choose one of the following methods to benchmark inference performance with
+   `DeepSeek-R1-Distill-Qwen-32B <https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B>`__.
+
+   .. _sglang-benchmark-mad:
+
+   {% for model_group in model_groups %}
+      {% for model in model_group.models %}
+
+   .. container:: model-doc {{model.mad_tag}}
+
+      .. tab-set::
+
+         .. tab-item:: MAD-integrated benchmarking
+
+            1. Clone the ROCm Model Automation and Dashboarding (`<https://github.com/ROCm/MAD>`__) repository to a local
+               directory and install the required packages on the host machine.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD
+                  pip install -r requirements.txt
+
+            2. Use this command to run the performance benchmark test on the `{{model.model}} <{{ model.url }}>`_ model
+               using one GPU with the ``{{model.precision}}`` data type on the host machine.
+
+               .. code-block:: shell
+
+                  export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
+                  madengine run \
+                      --tags {{model.mad_tag}} \
+                      --keep-model-dir \
+                      --live-output \
+                      --timeout 28800
+
+            MAD launches a Docker container with the name
+            ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
+            model are collected in the following path: ``~/MAD/perf_DeepSeek-R1-Distill-Qwen-32B.csv``.
+
+            Although the DeepSeek-R1-Distill-Qwen-32B is preconfigured
+            to collect latency and throughput performance data, you can also change the benchmarking
+            parameters. See the standalone benchmarking tab for more information.
+
+         .. tab-item:: Standalone benchmarking
+
+            .. rubric:: Download the Docker image and required scripts
+
+            1. Run the SGLang benchmark script independently by starting the
+               `Docker container <{{ unified_docker.docker_hub_url }}>`__
+               as shown in the following snippet.
+
+               .. code-block:: shell
+
+                  docker pull {{ unified_docker.pull_tag }}
+                  docker run -it \
+                      --device=/dev/kfd \
+                      --device=/dev/dri \
+                      --group-add video \
+                      --shm-size 16G \
+                      --security-opt seccomp=unconfined \
+                      --security-opt apparmor=unconfined \
+                      --cap-add=SYS_PTRACE \
+                      -v $(pwd):/workspace \
+                      --env HUGGINGFACE_HUB_CACHE=/workspace \
+                      --name test \
+                      {{ unified_docker.pull_tag }}
+
+            2. In the Docker container, clone the ROCm MAD repository and navigate to the
+               benchmark scripts directory at ``~/MAD/scripts/sglang``.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD/scripts/sglang
+
+            3. To start the benchmark, use the following command with the appropriate options.
+
+               .. dropdown:: Benchmark options
+                  :open:
+
+                  .. list-table::
+                     :header-rows: 1
+                     :align: center
+
+                     * - Name
+                       - Options
+                       - Description
+
+                     * - ``$test_option``
+                       - latency
+                       - Measure decoding token latency
+
+                     * -
+                       - throughput
+                       - Measure token generation throughput
+
+                     * -
+                       - all
+                       - Measure both throughput and latency
+
+                     * - ``$num_gpu``
+                       - 8
+                       - Number of GPUs
+
+                     * - ``$datatype``
+                       - ``bfloat16``
+                       - Data type
+
+                     * - ``$dataset``
+                       - random
+                       - Dataset
+
+                  The input sequence length, output sequence length, and tensor parallel (TP) are
+                  already configured. You don't need to specify them with this script.
+
+               Command:
+
+               .. code-block:: shell
+
+                  ./sglang_benchmark_report.sh -s $test_option -m {{model.model_repo}} -g $num_gpu -d $datatype [-a $dataset]
+
+            .. note::
+
+               If you encounter the following error, pass your access-authorized Hugging
+               Face token to the gated models.
+
+               .. code-block:: shell-session
+
+                  OSError: You are trying to access a gated repo.
+                  # pass your HF_TOKEN
+                  export HF_TOKEN=$your_personal_hf_token
+
+            .. rubric:: Benchmarking examples
+
+            Here are some examples of running the benchmark with various options:
+
+            * Latency benchmark
+
+              Use this command to benchmark the latency of the {{model.model}} model on eight GPUs with ``{{model.precision}}`` precision.
+
+              .. code-block:: shell
+
+                 ./sglang_benchmark_report.sh \
+                     -s latency \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}}
+
+              Find the latency report at ``./reports_{{model.precision}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_latency_report.csv``.
+
+            * Throughput benchmark
+
+              Use this command to benchmark the throughput of the {{model.model}} model on eight GPUs with ``{{model.precision}}`` precision.
+
+              .. code-block:: shell
+
+                 ./sglang_benchmark_report.sh \
+                     -s throughput \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}} \
+                     -a random
+
+              Find the throughput report at ``./reports_{{model.precision}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_throughput_report.csv``.
+
+            .. raw:: html
+
+               <style>
+               mjx-container[jax="CHTML"][display="true"] {
+                  text-align: left;
+                  margin: 0;
+               }
+               </style>
+
+            .. note::
+
+               Throughput is calculated as:
+
+               - .. math:: throughput\_tot = requests \times (\mathsf{\text{input lengths}} + \mathsf{\text{output lengths}}) / elapsed\_time
+
+               - .. math:: throughput\_gen = requests \times \mathsf{\text{output lengths}} / elapsed\_time
+      {% endfor %}
+   {% endfor %}
+
+Further reading
+===============
+
+- To learn more about the options for latency and throughput benchmark scripts,
+  see `<https://github.com/sgl-project/sglang/tree/main/benchmark/blog_v0_2>`__.
+
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`__.
+
+- For application performance optimization strategies for HPC and AI workloads,
+  including inference with vLLM, see :doc:`/how-to/rocm-for-ai/inference-optimization/workload`.
+
+- To learn how to run community models from Hugging Face on AMD GPUs, see
+  :doc:`Running models from Hugging Face </how-to/rocm-for-ai/inference/hugging-face-models>`.
+
+- To learn how to fine-tune LLMs and optimize inference, see
+  :doc:`Fine-tuning LLMs and inference optimization </how-to/rocm-for-ai/fine-tuning/fine-tuning-and-inference>`.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
+
+Previous versions
+=================
+
+See :doc:`previous-versions/sglang-history` to find documentation for previous releases
+of SGLang inference performance testing.
@@ -202,7 +202,7 @@ system's configuration.
               .. code-block:: shell

                  export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-                  python3 tools/run_models.py \
+                  madengine run \
                      --tags {{model.mad_tag}} \
                      --keep-model-dir \
                      --live-output \
@@ -226,12 +226,12 @@ system's configuration.

               By default, ``{{model.mad_tag}}`` runs with TunableOp disabled
               (see
-               `<https://github.com/ROCm/MAD/blob/develop/models.json>`__). To
-               enable it, edit the default run behavior in the ``models.json``
-               configuration before running inference -- update the model's run
-               ``args`` by changing ``--tunableop off`` to ``--tunableop on``.
+               `<https://github.com/ROCm/MAD/blob/develop/models.json>`__).
+               To enable it, include the ``--tunableop on`` argument in your
+               run.

-               Enabling TunableOp triggers a two-pass run -- a warm-up followed by the performance-collection run.
+               Enabling TunableOp triggers a two-pass run -- a warm-up followed
+               by the performance-collection run.

            {% endif %}

@@ -419,8 +419,10 @@ Further reading
 - To learn more about the options for latency and throughput benchmark scripts,
  see `<https://github.com/ROCm/vllm/tree/main/benchmarks>`_.

+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
 - To learn more about system settings and management practices to configure your system for
-  MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.

 - For application performance optimization strategies for HPC and AI workloads,
  including inference with vLLM, see :doc:`/how-to/rocm-for-ai/inference-optimization/workload`.
@@ -24,4 +24,6 @@ training, fine-tuning, and inference. It leverages popular machine learning fram

 - :doc:`PyTorch inference performance testing <benchmark-docker/pytorch-inference>`

+- :doc:`SGLang inference performance testing <benchmark-docker/sglang>`
+
 - :doc:`Deploying your model <deploy-your-model>`
@@ -24,12 +24,13 @@ If you’re new to ROCm, refer to the :doc:`ROCm quick start install guide for L
 If you’re using a Radeon GPU for graphics-accelerated applications, refer to the
 `Radeon installation instructions <https://rocm.docs.amd.com/projects/radeon/en/docs-6.1.3/docs/install/native_linux/install-radeon.html>`_.

-ROCm supports multiple :doc:`installation methods <rocm-install-on-linux:install/install-overview>`:
+You can install ROCm on :doc:`compatible systems <rocm-install-on-linux:reference/system-requirements>` via your Linux
+distribution's package manager. See the following documentation resources to get started:
+
+* :doc:`ROCm installation overview <rocm-install-on-linux:install/install-overview>`

 * :doc:`Using your Linux distribution's package manager <rocm-install-on-linux:install/install-methods/package-manager-index>`

-* :doc:`Using the AMDGPU installer <rocm-install-on-linux:install/install-methods/amdgpu-installer-index>`
-
 * :ref:`Multi-version installation <rocm-install-on-linux:installation-types>`

 .. grid:: 1
@@ -59,6 +60,8 @@ images with the framework pre-installed.

 * :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`

+* :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/dgl-install>`
+
 Next steps
 ==========

@@ -73,7 +73,11 @@ document are not validated.

      .. code-block:: shell

-         python3 tools/run_models.py --tags pyt_mpt30b_training --keep-model-dir --live-output --clean-docker-cache
+         madengine run \
+             --tags pyt_mpt30b_training \
+             --keep-model-dir \
+             --live-output \
+             --clean-docker-cache

      .. tip::

@@ -90,7 +94,7 @@ document are not validated.

         For improved performance (training throughput), consider enabling TunableOp.
         By default, ``pyt_mpt30b_training`` runs with TunableOp disabled. To enable it,
-         run ``tools/run_models.py`` with the ``--tunableop on`` argument or edit the
+         run ``madengine run`` with the ``--tunableop on`` argument or edit the
         ``models.json`` configuration before running training.

         Although this might increase the initial training time, it can result in a performance gain.
@@ -172,4 +176,13 @@ Key performance metrics include:

    Overall training loss. A decreasing trend indicates the model is learning effectively.

+Further reading
+===============

+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
@@ -142,7 +142,11 @@ The following models are pre-optimized for performance on the AMD Instinct MI325
            .. code-block:: shell

               export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-               python3 tools/run_models.py --tags {{ model.mad_tag }} --keep-model-dir --live-output --timeout 28800
+               madengine run \
+                   --tags {{ model.mad_tag }} \
+                   --keep-model-dir \
+                   --live-output \
+                   --timeout 28800

            MAD launches a Docker container with the name
            ``container_ci-{{ model.mad_tag }}``, for example. The latency and throughput reports of the
@@ -427,6 +431,17 @@ The following models are pre-optimized for performance on the AMD Instinct MI325

               For examples of benchmarking commands, see `<https://github.com/ROCm/MAD/tree/develop/benchmark/pytorch_train#benchmarking-examples>`__.

+Further reading
+===============
+
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
+
 Previous versions
 =================

@@ -285,7 +285,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - Radeon AI PRO R9700
          - RDNA4
          - gfx1201
-          - 16
+          - 32
          - 64
          - 32 or 64
          - 128
@@ -93,7 +93,7 @@ The following table shows whether a ROCm library is graph-safe.
      - ⚠️ (experimental)
    * 
      - `rocThrust <https://github.com/ROCm/rocThrust>`_
-      - ❌ (see :doc:`details <rocthrust:hipgraph-support>`)
+      - ❌ (see :doc:`details <rocthrust:reference/rocThrust-hipgraph-support>`)
    * 
      - `rocWMMA <https://github.com/ROCm/rocWMMA>`_
      - ❌
@@ -19,9 +19,9 @@ subtrees:

 - caption: Install
  entries:
-  - url: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/
+  - url: https://rocm.docs.amd.com/projects/install-on-linux/en/${branch}/
    title: ROCm on Linux
-  - url: https://rocm.docs.amd.com/projects/install-on-windows/en/${branch}/
+  - url: https://rocm.docs.amd.com/projects/install-on-windows/en/latest/
    title: HIP SDK on Windows
  - url: https://rocm.docs.amd.com/projects/radeon/en/latest/index.html
    title: ROCm on Radeon GPUs
@@ -82,6 +82,8 @@ subtrees:
            title: vLLM inference performance testing
          - file: how-to/rocm-for-ai/inference/benchmark-docker/pytorch-inference.rst
            title: PyTorch inference performance testing
+          - file: how-to/rocm-for-ai/inference/benchmark-docker/sglang.rst
+            title: SGLang inference performance testing
          - file: how-to/rocm-for-ai/inference/deploy-your-model.rst
            title: Deploy your model

@@ -1,4 +1,4 @@
-rocm-docs-core==1.20.1
+rocm-docs-core==1.26.0
 sphinx-reredirects
 sphinx-sitemap
 sphinxcontrib.datatemplates==0.11.0
@@ -10,7 +10,7 @@ alabaster==1.0.0
    # via sphinx
 asttokens==3.0.0
    # via stack-data
-attrs==25.3.0
+attrs==25.4.0
    # via
    #   jsonschema
    #   jupyter-cache
@@ -19,34 +19,32 @@ babel==2.17.0
    # via
    #   pydata-sphinx-theme
    #   sphinx
-beautifulsoup4==4.13.4
+beautifulsoup4==4.14.2
    # via pydata-sphinx-theme
 breathe==4.36.0
    # via rocm-docs-core
-certifi==2025.4.26
+certifi==2025.10.5
    # via requests
-cffi==1.17.1
+cffi==2.0.0
    # via
    #   cryptography
    #   pynacl
-charset-normalizer==3.4.2
+charset-normalizer==3.4.4
    # via requests
-click==8.2.1
+click==8.3.0
    # via
    #   jupyter-cache
    #   sphinx-external-toc
-comm==0.2.2
+comm==0.2.3
    # via ipykernel
-cryptography==45.0.3
+cryptography==46.0.2
    # via pyjwt
-debugpy==1.8.14
+debugpy==1.8.17
    # via ipykernel
 decorator==5.2.1
    # via ipython
 defusedxml==0.7.1
    # via sphinxcontrib-datatemplates
-deprecated==1.2.18
-    # via pygithub
 docutils==0.21.2
    # via
    #   myst-parser
@@ -54,19 +52,19 @@ docutils==0.21.2
    #   sphinx
 exceptiongroup==1.3.0
    # via ipython
-executing==2.2.0
+executing==2.2.1
    # via stack-data
-fastjsonschema==2.21.1
+fastjsonschema==2.21.2
    # via
    #   nbformat
    #   rocm-docs-core
 gitdb==4.0.12
    # via gitpython
-gitpython==3.1.44
+gitpython==3.1.45
    # via rocm-docs-core
-greenlet==3.2.3
+greenlet==3.2.4
    # via sqlalchemy
-idna==3.10
+idna==3.11
    # via requests
 imagesize==1.4.1
    # via sphinx
@@ -74,7 +72,7 @@ importlib-metadata==8.7.0
    # via
    #   jupyter-cache
    #   myst-nb
-ipykernel==6.29.5
+ipykernel==7.0.0
    # via myst-nb
 ipython==8.37.0
    # via
@@ -86,9 +84,9 @@ jinja2==3.1.6
    # via
    #   myst-parser
    #   sphinx
-jsonschema==4.24.0
+jsonschema==4.25.1
    # via nbformat
-jsonschema-specifications==2025.4.1
+jsonschema-specifications==2025.9.1
    # via jsonschema
 jupyter-cache==1.0.1
    # via myst-nb
@@ -106,17 +104,17 @@ markdown-it-py==3.0.0
    # via
    #   mdit-py-plugins
    #   myst-parser
-markupsafe==3.0.2
+markupsafe==3.0.3
    # via jinja2
 matplotlib-inline==0.1.7
    # via
    #   ipykernel
    #   ipython
-mdit-py-plugins==0.4.2
+mdit-py-plugins==0.5.0
    # via myst-parser
 mdurl==0.1.2
    # via markdown-it-py
-myst-nb==1.2.0
+myst-nb==1.3.0
    # via rocm-docs-core
 myst-parser==4.0.1
    # via myst-nb
@@ -134,31 +132,30 @@ nest-asyncio==1.6.0
 packaging==25.0
    # via
    #   ipykernel
-    #   pydata-sphinx-theme
    #   sphinx
-parso==0.8.4
+parso==0.8.5
    # via jedi
 pexpect==4.9.0
    # via ipython
-platformdirs==4.3.8
+platformdirs==4.5.0
    # via jupyter-core
-prompt-toolkit==3.0.51
+prompt-toolkit==3.0.52
    # via ipython
-psutil==7.0.0
+psutil==7.1.0
    # via ipykernel
 ptyprocess==0.7.0
    # via pexpect
 pure-eval==0.2.3
    # via stack-data
-pycparser==2.22
+pycparser==2.23
    # via cffi
-pydata-sphinx-theme==0.15.4
+pydata-sphinx-theme==0.16.1
    # via
    #   rocm-docs-core
    #   sphinx-book-theme
-pygithub==2.6.1
+pygithub==2.8.1
    # via rocm-docs-core
-pygments==2.19.1
+pygments==2.19.2
    # via
    #   accessible-pygments
    #   ipython
@@ -166,11 +163,11 @@ pygments==2.19.1
    #   sphinx
 pyjwt[crypto]==2.10.1
    # via pygithub
-pynacl==1.5.0
+pynacl==1.6.0
    # via pygithub
 python-dateutil==2.9.0.post0
    # via jupyter-client
-pyyaml==6.0.2
+pyyaml==6.0.3
    # via
    #   jupyter-cache
    #   myst-nb
@@ -178,21 +175,21 @@ pyyaml==6.0.2
    #   rocm-docs-core
    #   sphinx-external-toc
    #   sphinxcontrib-datatemplates
-pyzmq==26.4.0
+pyzmq==27.1.0
    # via
    #   ipykernel
    #   jupyter-client
-referencing==0.36.2
+referencing==0.37.0
    # via
    #   jsonschema
    #   jsonschema-specifications
-requests==2.32.4
+requests==2.32.5
    # via
    #   pygithub
    #   sphinx
-rocm-docs-core==1.20.1
+rocm-docs-core==1.26.0
    # via -r requirements.in
-rpds-py==0.25.1
+rpds-py==0.27.1
    # via
    #   jsonschema
    #   referencing
@@ -202,7 +199,7 @@ smmap==5.0.2
    # via gitdb
 snowballstemmer==3.0.1
    # via sphinx
-soupsieve==2.7
+soupsieve==2.8
    # via beautifulsoup4
 sphinx==8.1.3
    # via
@@ -220,7 +217,7 @@ sphinx==8.1.3
    #   sphinx-reredirects
    #   sphinxcontrib-datatemplates
    #   sphinxcontrib-runcmd
-sphinx-book-theme==1.1.4
+sphinx-book-theme==1.1.3
    # via rocm-docs-core
 sphinx-copybutton==0.5.2
    # via rocm-docs-core
@@ -234,7 +231,7 @@ sphinx-notfound-page==1.1.0
    # via rocm-docs-core
 sphinx-reredirects==0.1.6
    # via -r requirements.in
-sphinx-sitemap==2.7.2
+sphinx-sitemap==2.9.0
    # via -r requirements.in
 sphinxcontrib-applehelp==2.0.0
    # via sphinx
@@ -252,21 +249,20 @@ sphinxcontrib-runcmd==0.2.0
    # via sphinxcontrib-datatemplates
 sphinxcontrib-serializinghtml==2.0.0
    # via sphinx
-sqlalchemy==2.0.41
+sqlalchemy==2.0.44
    # via jupyter-cache
 stack-data==0.6.3
    # via ipython
 tabulate==0.9.0
    # via jupyter-cache
-tomli==2.2.1
+tomli==2.3.0
    # via sphinx
-tornado==6.5.1
+tornado==6.5.2
    # via
    #   ipykernel
    #   jupyter-client
 traitlets==5.14.3
    # via
-    #   comm
    #   ipykernel
    #   ipython
    #   jupyter-client
@@ -274,9 +270,10 @@ traitlets==5.14.3
    #   matplotlib-inline
    #   nbclient
    #   nbformat
-typing-extensions==4.14.0
+typing-extensions==4.15.0
    # via
    #   beautifulsoup4
+    #   cryptography
    #   exceptiongroup
    #   ipython
    #   myst-nb
@@ -288,9 +285,7 @@ urllib3==2.5.0
    # via
    #   pygithub
    #   requests
-wcwidth==0.2.13
+wcwidth==0.2.14
    # via prompt-toolkit
-wrapt==1.17.2
-    # via deprecated
 zipp==3.23.0
    # via importlib-metadata
Author	SHA1	Message	Date
anisha-amdandGitHub	0bf109e70e	[6.4.2] Docs: removal of migrated deep learning frameworks (#6089 )	2026-03-31 15:47:17 -04:00
Pratik BasyalandGitHub	9ecb53b951	Taichi removed (#5802 )	2025-12-19 15:44:03 -05:00
Alex Xu	ac0e6d3bc8	bump rocm-docs-core to 1.26.0	2025-10-14 11:36:26 -04:00
Peter ParkandGitHub	1838f82aeb	Fix documented VRAM for Radeon AI Pro R9700 (#5203 ) (#5205 ) (cherry picked from commit `c154b7e0a3`)	2025-08-18 10:20:12 -04:00
anisha-amdandGitHub	59524e75eb	[Docs] 6.4.2: compatibility matrix frameworks support update (#5187 )	2025-08-12 14:25:54 -04:00
Alex Xu	b9cd22b770	add pdf format to docs/6.4.2	2025-08-01 15:21:17 -04:00
anisha-amdandGitHub	596cf19217	Updates to the compatibility matrix with DGL fix (#5143 ) (#5145 )	2025-08-01 11:39:14 -04:00
anisha-amdandGitHub	1b8c7f25a1	Cherry pick into 6.4.2 - Docs: Adding frameworks compatibility for Megablocks and Taichi (#5137 )	2025-07-31 14:01:49 -04:00
Peter ParkandPeter Park	869882f496	Update PyT and TF Docker images in compatibility pages for 6.4.2 (#5129 ) (cherry picked from commit `b61d6a021e`)	2025-07-31 10:04:26 -04:00
Pratik BasyalandGitHub	b3f2646d8d	ROCm Software Stack image for 6.4.0 updated (#5112 ) (#5116 )	2025-07-29 09:44:49 -04:00
Peter Park GitHub yugang-amd	2ac14a845a	Add SGLang inference benchmark doc w/ initial support for DeepSeek-R1-Distill-Qwen-32B (#4870 ) (#5103 ) (cherry picked from commit `cc5bc5a882`) Co-authored-by: yugang-amd <yugang.wang@amd.com>	2025-07-25 12:52:47 -04:00
Peter ParkandPeter Park	1eaca180d3	Use `madengine` instead of tools/run_models.py in docs (#5095 ) (cherry picked from commit `14249f24d8`)	2025-07-24 15:52:16 -04:00
Peter ParkandPeter Park	9bf497e4b4	Add DeepSeek Janus Pro 7B to PyTorch inference benchmark doc (#5071 ) --------- Co-authored-by: yugang-amd <yugang.wang@amd.com> (cherry picked from commit `984a91f008`)	2025-07-22 16:33:30 -04:00
Peter ParkandGitHub	417b22b81b	Merge pull request #5084 from peterjunpark/docs/6.4.2 [docs/6.4.2] Remove broken link to deprecated AMDGPU installer documentation and fix branches for install docs in TOC	2025-07-22 11:16:38 -04:00
Peter Park	93acf292c7	Fix branches for install docs in _toc.yml.in (#5083 ) (cherry picked from commit `15ee605d18`)	2025-07-22 11:04:40 -04:00
Peter Park	a7388285c7	Remove broken link to deprecated AMDGPU installer documentation (#5078 ) * remove link to deprecated AMDGPU installation method * add deep learning frameworks (cherry picked from commit `2269e9d25d`)	2025-07-22 11:04:40 -04:00
Pratik Basyal GitHub anisha-amd	f0ac0a1bef	Sphinx warning for ROCm fixed (#5077 ) * Sphinx warning for DGL fixed * Update dgl-compatibility.rst removed benchmark line and updated link --------- Co-authored-by: anisha-amd <anisha.sankar@amd.com>	2025-07-22 10:09:54 -04:00
alexxu-amdandGitHub	f4697b5a47	Sync develop into docs/6.4.2	2025-07-21 17:04:14 -04:00
Alex Xu	fcf614f195	Merge branch 'roc-6.4.x' into docs/6.4.2	2025-07-21 15:52:59 -04:00
Alex Xu	87c6e320b4	Merge branch 'develop' into roc-6.4.x	2025-07-21 15:52:30 -04:00
Alex Xu	1d0900b42e	Merge branch 'develop' into docs/6.4.2	2025-07-21 13:04:21 -04:00
spolifroni-amdandGitHub	6c35f210e3	minor link and comp matrix fixes (#5056 ) (#5059 ) (cherry picked from commit `703e253db5`)	2025-07-16 15:37:24 -04:00
anisha-amd GitHub Jeffrey Novotny vickytsang spolifroni-amd Leo Paoletti Mukhil M S	a5c7baf1a0	cherry pick frameworks compatibility into 6.4.2 * Merge Verl, DGL, Megatron changes. (#5047) * Verl compatibility * verl compatibility * add Supported features Signed-off-by: Vicky Tsang <vtsang@amd.com> * updated and edited verl compat doc * added links to verl * add future release for sglang and megatron inference eng. Signed-off-by: Vicky Tsang <vtsang@amd.com> * fix lint Signed-off-by: Vicky Tsang <vtsang@amd.com> * fixed a typo and a table * Spolifroni amd/add to compat matrix (#430) * added verl to compatibility matrix * small change * fixed an error in csv * edited the verl compat based on leo's recommendations * updated compat matrix (#435) * Added a hardcoded link to the verl install This is a link to an RTD build and MUST be removed before publishing. * Update verl-compatibility.rst * Added a hardcoded link to the verl install This link is to an RTD build and it WILL break at publishing. It MUST be changed before publishing. * Added version support note (#448) * small fixes * Update verl-compatibility.rst * Update verl-compatibility.rst --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> (cherry picked from commit `f9bd22626b`) * Stanford Megatron-LM Compatibility * Create stanford-megatron-lm-compatibility.rst * toc and wordlist * Update deep-learning-rocm.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * fixes and adding to main compat matrix * formatting fix * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst --------- Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `f4f096b44e`) * Framework: DGL Compatability * Introducing new file for DGL Compatability * Update dgl-compatibility.rst * Update .wordlist.txt * Update .wordlist.txt * Update deep-learning-rocm.rst * compatibility fixes * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * additions to use-cases and system support * wording and fixes * Update dgl-compatibility.rst * Update dgl-compatibility.rst * remove table heading * Update compatibility-matrix-historical-6.0.csv --------- Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `2a7554c0b9`) * Manually resolve merge conflict * Further merge conflict adjustments --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: vickytsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> Co-authored-by: Mukhil M S <167260682+mukh1l@users.noreply.github.com> * Merge Verl, DGL, Megatron changes. (#5047) * Verl compatibility * verl compatibility * add Supported features Signed-off-by: Vicky Tsang <vtsang@amd.com> * updated and edited verl compat doc * added links to verl * add future release for sglang and megatron inference eng. Signed-off-by: Vicky Tsang <vtsang@amd.com> * fix lint Signed-off-by: Vicky Tsang <vtsang@amd.com> * fixed a typo and a table * Spolifroni amd/add to compat matrix (#430) * added verl to compatibility matrix * small change * fixed an error in csv * edited the verl compat based on leo's recommendations * updated compat matrix (#435) * Added a hardcoded link to the verl install This is a link to an RTD build and MUST be removed before publishing. * Update verl-compatibility.rst * Added a hardcoded link to the verl install This link is to an RTD build and it WILL break at publishing. It MUST be changed before publishing. * Added version support note (#448) * small fixes * Update verl-compatibility.rst * Update verl-compatibility.rst --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> (cherry picked from commit `f9bd22626b`) * Stanford Megatron-LM Compatibility * Create stanford-megatron-lm-compatibility.rst * toc and wordlist * Update deep-learning-rocm.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * fixes and adding to main compat matrix * formatting fix * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst --------- Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `f4f096b44e`) * Framework: DGL Compatability * Introducing new file for DGL Compatability * Update dgl-compatibility.rst * Update .wordlist.txt * Update .wordlist.txt * Update deep-learning-rocm.rst * compatibility fixes * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * additions to use-cases and system support * wording and fixes * Update dgl-compatibility.rst * Update dgl-compatibility.rst * remove table heading * Update compatibility-matrix-historical-6.0.csv --------- Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `2a7554c0b9`) * Manually resolve merge conflict * Further merge conflict adjustments --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: vickytsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> Co-authored-by: Mukhil M S <167260682+mukh1l@users.noreply.github.com> * Merge Verl, DGL, Megatron changes. (#5047) * Verl compatibility * verl compatibility * add Supported features Signed-off-by: Vicky Tsang <vtsang@amd.com> * updated and edited verl compat doc * added links to verl * add future release for sglang and megatron inference eng. Signed-off-by: Vicky Tsang <vtsang@amd.com> * fix lint Signed-off-by: Vicky Tsang <vtsang@amd.com> * fixed a typo and a table * Spolifroni amd/add to compat matrix (#430) * added verl to compatibility matrix * small change * fixed an error in csv * edited the verl compat based on leo's recommendations * updated compat matrix (#435) * Added a hardcoded link to the verl install This is a link to an RTD build and MUST be removed before publishing. * Update verl-compatibility.rst * Added a hardcoded link to the verl install This link is to an RTD build and it WILL break at publishing. It MUST be changed before publishing. * Added version support note (#448) * small fixes * Update verl-compatibility.rst * Update verl-compatibility.rst --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> (cherry picked from commit `f9bd22626b`) * Stanford Megatron-LM Compatibility * Create stanford-megatron-lm-compatibility.rst * toc and wordlist * Update deep-learning-rocm.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * fixes and adding to main compat matrix * formatting fix * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst --------- Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `f4f096b44e`) * Framework: DGL Compatability * Introducing new file for DGL Compatability * Update dgl-compatibility.rst * Update .wordlist.txt * Update .wordlist.txt * Update deep-learning-rocm.rst * compatibility fixes * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/dgl-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * Update dgl-compatibility.rst * additions to use-cases and system support * wording and fixes * Update dgl-compatibility.rst * Update dgl-compatibility.rst * remove table heading * Update compatibility-matrix-historical-6.0.csv --------- Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> (cherry picked from commit `2a7554c0b9`) * Manually resolve merge conflict * Further merge conflict adjustments --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: vickytsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: anisha-amd <anisha.sankar@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> Co-authored-by: Mukhil M S <167260682+mukh1l@users.noreply.github.com> --------- Signed-off-by: Vicky Tsang <vtsang@amd.com> Co-authored-by: Jeffrey Novotny <jnovotny@amd.com> Co-authored-by: vickytsang <vtsang@amd.com> Co-authored-by: spolifroni-amd <sandra.polifroni@amd.com> Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> Co-authored-by: Mukhil M S <167260682+mukh1l@users.noreply.github.com>	2025-07-15 19:14:26 -04:00
alexxu-amdandGitHub	702262b801	Sync develop into docs/6.4.2	2025-07-11 16:21:31 -04:00
Alex Xu	cfb740b915	upgrade rocm-docs-core to 1.21.1	2025-07-11 15:56:51 -04:00
ammallyaandGitHub	b50948fe6b	Fix for rocrsamples and rocr_debug_agent (#4863 ) * Fix for rocrsamples * Fix for rocr_debug_agent	2025-05-30 16:27:29 -07:00
ammallyaandGitHub	91407405a9	Changed naming convention for hip (#4837 ) * Changed naming convention for hip * Changed naming convention for hip	2025-05-29 10:19:28 -07:00
ammallyaandGitHub	8f23f63a6b	Fix for tests (#4818 ) * Fix for RBT * Fix for roctst and kfd test	2025-05-27 17:38:48 -07:00
Alex Xu	11747aaadc	Merge branch 'develop' into roc-6.4.x	2025-05-21 15:04:02 -04:00
Alex Xu	1088beefe5	Merge branch 'develop' into roc-6.4.x	2025-05-21 12:27:13 -04:00
Alex Xu	b7988925a5	Merge branch 'develop' into roc-6.4.x	2025-05-21 12:25:30 -04:00
chiranjeevipattigidiandGitHub	89dafa6232	Update packages - remove broken packages (#4758 ) * Update envsetup.sh HIP_ON_ROCclr_ROOT path to hip and remove aqlprofiletest * Update packages - remove broken packages	2025-05-21 09:06:39 -07:00
chiranjeevipattigidiandGitHub	8054852dad	Update envsetup.sh HIP_ON_ROCclr_ROOT path to hip and remove (#4755 ) aqlprofiletest	2025-05-20 07:59:07 -07:00
ammallyaandGitHub	542d7813ce	Removing aqlprofiletest	2025-04-14 15:26:24 -07:00
ammallyaandGitHub	bc1ffe4fcb	bypass tests	2025-04-14 13:41:34 -07:00
ammallyaandGitHub	09997c68bb	Removing kfd test	2025-04-14 12:55:13 -07:00
ammallyaandGitHub	42bc3501ac	Merge pull request #4623 from ammallya/roc-6.4.x Rebasing branch 6.4.x	2025-04-14 11:42:06 -07:00