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36 Commits

Author SHA1 Message Date
Pratik Basyal
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 Park
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-amd
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-amd
596cf19217 Updates to the compatibility matrix with DGL fix (#5143) (#5145) 2025-08-01 11:39:14 -04:00
anisha-amd
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 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 Basyal
b3f2646d8d ROCm Software Stack image for 6.4.0 updated (#5112) (#5116) 2025-07-29 09:44:49 -04:00
Peter Park
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 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 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 Park
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
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-amd
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-amd
6c35f210e3 minor link and comp matrix fixes (#5056) (#5059)
(cherry picked from commit 703e253db5)
2025-07-16 15:37:24 -04:00
anisha-amd
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-amd
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
ammallya
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
ammallya
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
ammallya
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
chiranjeevipattigidi
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
chiranjeevipattigidi
8054852dad Update envsetup.sh HIP_ON_ROCclr_ROOT path to hip and remove (#4755)
aqlprofiletest
2025-05-20 07:59:07 -07:00
ammallya
542d7813ce Removing aqlprofiletest 2025-04-14 15:26:24 -07:00
ammallya
bc1ffe4fcb bypass tests 2025-04-14 13:41:34 -07:00
ammallya
09997c68bb Removing kfd test 2025-04-14 12:55:13 -07:00
ammallya
42bc3501ac Merge pull request #4623 from ammallya/roc-6.4.x
Rebasing branch 6.4.x
2025-04-14 11:42:06 -07:00
28 changed files with 664 additions and 257 deletions

View File

@@ -6,7 +6,7 @@ version: 2
sphinx:
configuration: docs/conf.py
formats: [htmlzip]
formats: [htmlzip, pdf]
python:
install:

View File

@@ -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

View File

@@ -30,9 +30,10 @@ 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:`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,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A
:doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat]_,N/A,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
: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
:doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,0.7.0,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
,,,,,,,,,,,,,,,,,
,,,,,,,,,,,,,,,,,
1 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 6.1.5 6.1.2 6.1.1 6.1.0 6.0.2 6.0.0
30 :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
31 :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
32 :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
33 :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat]_ N/A N/A N/A N/A N/A 85f95ae 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
34 :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat]_ 2.4.0 N/A 2.4.0 N/A 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
35 :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat]_ :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_ N/A N/A N/A 2.4.0 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 N/A
36 :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat]_ N/A N/A N/A N/A N/A N/A 0.7.0 N/A N/A N/A N/A N/A N/A N/A N/A N/A
37 `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
38
39

View File

@@ -56,7 +56,7 @@ compatibility and system requirements.
: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
:doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>`,N/A,N/A,0.7.0
`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:,,
@@ -241,6 +241,9 @@ Expand for full historical view of:
.. [#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.
.. [#stanford-megatron-lm_compat] Stanford Megatron-LM is only supported on ROCm 6.3.0.
.. [#dgl_compat] DGL is only supported on ROCm 6.4.0.
.. [#megablocks_compat] Megablocks is only supported on ROCm 6.3.0.
.. [#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.

View File

@@ -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``

View File

@@ -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

View File

@@ -0,0 +1,93 @@
:orphan:
.. meta::
:description: Megablocks compatibility
:keywords: GPU, megablocks, compatibility
.. version-set:: rocm_version latest
********************************************************************************
Megablocks compatibility
********************************************************************************
Megablocks is a light-weight library for mixture-of-experts (MoE) training.
The core of the system is efficient "dropless-MoE" and standard MoE layers.
Megablocks is integrated with `https://github.com/stanford-futuredata/Megatron-LM <https://github.com/stanford-futuredata/Megatron-LM>`_,
where data and pipeline parallel training of MoEs is supported.
* ROCm support for Megablocks is hosted in the official `https://github.com/ROCm/megablocks <https://github.com/ROCm/megablocks>`_ 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 <megablocks-docker-compat>` with ROCm, PyTorch, and Megablocks preinstalled.
* See the :doc:`ROCm Megablocks installation guide <rocm-install-on-linux:install/3rd-party/megablocks-install>` to install and get started.
.. note::
Megablocks 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 summarizes the Megablocks features supported by ROCm.
* Distributed Pre-training
* Activation Checkpointing and Recomputation
* Distributed Optimizer
* Mixture-of-Experts
* dropless-Mixture-of-Experts
.. _megablocks-recommendations:
Use cases and recommendations
================================================================================
The `ROCm Megablocks blog posts <https://rocm.blogs.amd.com/artificial-intelligence/megablocks/README.html>`_
guide how to leverage the ROCm platform for pre-training using the Megablocks framework.
It features how to pre-process datasets and how to begin pre-training on AMD GPUs through:
* Single-GPU pre-training
* Multi-GPU pre-training
.. _megablocks-docker-compat:
Docker image compatibility
================================================================================
.. |docker-icon| raw:: html
<i class="fab fa-docker"></i>
AMD validates and publishes `ROCm Megablocks images <https://hub.docker.com/r/rocm/megablocks/tags>`_
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
- ROCm
- Megablocks
- PyTorch
- Ubuntu
- Python
* - .. raw:: html
<a href="https://hub.docker.com/layers/rocm/megablocks/megablocks-0.7.0_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-372ff89b96599019b8f5f9db469c84add2529b713456781fa62eb9a148659ab4"><i class="fab fa-docker fa-lg"></i> rocm/megablocks</a>
- `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
- `0.7.0 <https://github.com/databricks/megablocks/releases/tag/v0.7.0>`_
- `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/>`_

View File

@@ -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
================================================================================

View File

@@ -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>`__

View File

@@ -16,56 +16,25 @@ verl offers a scalable, open-source fine-tuning solution optimized for AMD Insti
* 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.
* See the :doc:`ROCm verl installation guide <rocm-install-on-linux:install/3rd-party/verl-install>` to install and 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>`_
The benefits of verl in large-scale reinforcement learning 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-supported_features:
Supported features
===============================================================================
The following table shows verl and ROCm support for GPU-accelerated modules.
The following table shows verl on ROCm support for GPU-accelerated modules.
.. list-table::
:header-rows: 1
@@ -77,9 +46,41 @@ The following table shows verl and ROCm support for GPU-accelerated modules.
* - ``FSDP``
- Training engine
- 0.3.0.post0
- 6.2
- 6.2.0
* - ``vllm``
- Inference engine
- 0.3.0.post0
- 6.2
- 6.2.0
.. _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/tags>`_
with ROCm backends on Docker Hub. The following Docker image tags and associated inventories represent the available verl versions from the official Docker Hub.
.. list-table::
:header-rows: 1
* - Docker image
- ROCm
- verl
- Ubuntu
- 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>
- `6.2.0 <https://repo.radeon.com/rocm/apt/6.2/>`_
- `0.3.0post0 <https://github.com/volcengine/verl/releases/tag/v0.3.0.post0>`_
- 20.04
- `2.5.0 <https://github.com/ROCm/pytorch/tree/release/2.5>`_
- `3.9.19 <https://www.python.org/downloads/release/python-3919/>`_
- `0.6.3 <https://github.com/vllm-project/vllm/releases/tag/v0.6.3>`_

View File

@@ -96,6 +96,10 @@ 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/verl-compatibility", "os": ["linux"]},
{"file": "compatibility/ml-compatibility/stanford-megatron-lm-compatibility", "os": ["linux"]},
{"file": "compatibility/ml-compatibility/dgl-compatibility", "os": ["linux"]},
{"file": "compatibility/ml-compatibility/megablocks-compatibility", "os": ["linux"]},
{"file": "how-to/deep-learning-rocm", "os": ["linux"]},
{"file": "how-to/rocm-for-ai/index", "os": ["linux"]},

View File

@@ -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

View File

@@ -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

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@@ -20,6 +20,7 @@ features for these ROCm-enabled deep learning frameworks.
* :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>`
* :doc:`Megablocks compatibility <../compatibility/ml-compatibility/megablocks-compatibility>`
This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
@@ -35,6 +36,7 @@ See the installation instructions to get started.
* :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>`
* :doc:`Megablocks for ROCm <rocm-install-on-linux:install/3rd-party/megablocks-install>`
.. note::

View File

@@ -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>`__

View File

@@ -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`.

View File

@@ -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.

View File

@@ -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`.

View File

@@ -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>`

View File

@@ -24,12 +24,13 @@ If youre new to ROCm, refer to the :doc:`ROCm quick start install guide for L
If youre 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 +60,12 @@ images with the framework pre-installed.
* :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/jax-install>`
* :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
Next steps
==========

View File

@@ -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>`_.

View File

@@ -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
=================

View File

@@ -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

View File

@@ -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>`_
-

View File

@@ -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

View File

@@ -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

View File

@@ -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