feat(ml): rocm (#16613)

* feat(ml): introduce support of onnxruntime-rocm for AMD GPU

* try mutex for algo cache

use OrtMutex

* bump versions, run on mich

use 3.12

use 1.19.2

* acquire lock before any changes can be made

guard algo benchmark results

mark mutex as mutable

re-add /bin/sh (?)

use 3.10

use 6.1.2

* use composite cache key

1.19.2

fix variable name

fix variable reference

aaaaaaaaaaaaaaaaaaaa

* bump deps

* disable algo caching

* fix gha

* try ubuntu runner

* actually fix the gha

* update patch

* skip mimalloc preload for rocm

* increase build threads

* increase timeout for rocm

* Revert "increase timeout for rocm"

This reverts commit 2c4452f5d132198ed381a7b262b4a5cab5114b5f.

* attempt migraphx

* set migraphx_home

* Revert "set migraphx_home"

This reverts commit c121d3e48754b3bce100636f8d666deec58a44b7.

* Revert "attempt migraphx"

This reverts commit 521f9fb72dbe506dc6cb8faeb6494817d87265c6.

* migraphx, take two

* bump rocm

* allow cpu

* try only targeting migraphx

* skip tests

* migraph ❌

* known issues

* target gfx900 and gfx1102

* mention `HSA_USE_SVM`

* update lock

* set device id for rocm

---------

Co-authored-by: Mehdi GHESH <mehdi.ghesh@hotmail.fr>

docker/docker-compose.yml

@@ -33,12 +33,12 @@ services:
 
   immich-machine-learning:
     container_name: immich_machine_learning
-    # For hardware acceleration, add one of -[armnn, cuda, openvino, rknn] to the image tag.
+    # For hardware acceleration, add one of -[armnn, cuda, rocm, openvino, rknn] to the image tag.
     # Example tag: ${IMMICH_VERSION:-release}-cuda
     image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
     # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
     #   file: hwaccel.ml.yml
-    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl, rknn] for accelerated inference - use the `-wsl` version for WSL2 where applicable
+    #   service: cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference - use the `-wsl` version for WSL2 where applicable
     volumes:
       - model-cache:/cache
     env_file: