feat: ROCm 7.2 and MIGraphX support (#26178)

machine-learning/Dockerfile

@@ -22,48 +22,7 @@ FROM builder-cpu AS builder-rknn
 
 # Warning: 25GiB+ disk space required to pull this image
 # TODO: find a way to reduce the image size
-FROM rocm/dev-ubuntu-24.04:6.4.4-complete@sha256:31418ac10a3769a71eaef330c07280d1d999d7074621339b8f93c484c35f6078 AS builder-rocm
-
-# renovate: datasource=github-releases depName=Microsoft/onnxruntime
-ARG ONNXRUNTIME_VERSION="v1.22.1"
-WORKDIR /code
-
-RUN apt-get update && apt-get install -y --no-install-recommends wget git
-RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.31.9/cmake-3.31.9-linux-x86_64.sh && \
-    chmod +x cmake-3.31.9-linux-x86_64.sh && \
-    mkdir -p /code/cmake-3.31.9-linux-x86_64 && \
-    ./cmake-3.31.9-linux-x86_64.sh --skip-license --prefix=/code/cmake-3.31.9-linux-x86_64 && \
-    rm cmake-3.31.9-linux-x86_64.sh
-
-RUN git clone --single-branch --branch "${ONNXRUNTIME_VERSION}" --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime
-WORKDIR /code/onnxruntime
-# Fix for multi-threading based on comments in https://github.com/microsoft/onnxruntime/pull/19567
-# TODO: find a way to fix this without disabling algo caching
-COPY ./patches/* /tmp/
-RUN git apply /tmp/*.patch
-
-RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh
-
-ENV PATH=/opt/rocm-venv/bin:/code/cmake-3.31.9-linux-x86_64/bin:${PATH}
-ENV CCACHE_DIR="/ccache"
-# Note: the `parallel` setting uses a substantial amount of RAM
-RUN --mount=type=cache,target=/ccache \
-    ./build.sh \
-    --allow_running_as_root \
-    --config Release \
-    --build_wheel \
-    --update \
-    --build \
-    --parallel 48 \
-    --cmake_extra_defines \
-    ONNXRUNTIME_VERSION="${ONNXRUNTIME_VERSION}" \
-    CMAKE_HIP_ARCHITECTURES="gfx900;gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201" \
-    --skip_tests \
-    --use_rocm \
-    --rocm_home=/opt/rocm \
-    --use_cache \
-    --compile_no_warning_as_error
-RUN mv /code/onnxruntime/build/Linux/Release/dist/*.whl /opt/
+FROM rocm/dev-ubuntu-24.04:7.2-complete@sha256:86e11093b4a7ec2a79b1b6701d10e840a6994f21c7e05929b51eb9be361c683a AS builder-rocm
 
 FROM builder-${DEVICE} AS builder
 
@@ -79,9 +38,6 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     --mount=type=bind,source=uv.lock,target=uv.lock \
     --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
     uv sync --frozen --extra ${DEVICE} --no-dev --no-editable --no-install-project --compile-bytecode --no-progress --active --link-mode copy
-RUN if [ "$DEVICE" = "rocm" ]; then \
-    uv pip install /opt/onnxruntime_rocm-*.whl; \
-    fi
 
 FROM python:3.11-slim-bookworm@sha256:04cd27899595a99dfe77709d96f08876bf2ee99139ee2f0fe9ac948005034e5b AS prod-cpu
 
@@ -120,7 +76,11 @@ COPY --from=builder-cuda /usr/local/bin/python3 /usr/local/bin/python3
 COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11
 COPY --from=builder-cuda /usr/local/lib/libpython3.11.so /usr/local/lib/libpython3.11.so
 
-FROM rocm/dev-ubuntu-24.04:6.4.4-complete@sha256:31418ac10a3769a71eaef330c07280d1d999d7074621339b8f93c484c35f6078 AS prod-rocm
+FROM rocm/dev-ubuntu-24.04:7.2-complete@sha256:86e11093b4a7ec2a79b1b6701d10e840a6994f21c7e05929b51eb9be361c683a AS prod-rocm
+
+RUN apt-get update && apt-get install --no-install-recommends -yqq migraphx miopen-hip && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
 
 FROM prod-cpu AS prod-armnn
 

machine-learning/immich_ml/config.py

@@ -79,6 +79,7 @@ class Settings(BaseSettings):
     preload: PreloadModelData | None = None
     max_batch_size: MaxBatchSize | None = None
     openvino_precision: ModelPrecision = ModelPrecision.FP32
+    rocm_precision: ModelPrecision = ModelPrecision.FP32
 
     @property
     def device_id(self) -> str:

machine-learning/immich_ml/models/constants.py

@@ -90,7 +90,7 @@ _PADDLE_MODELS = {
 
 SUPPORTED_PROVIDERS = [
     "CUDAExecutionProvider",
-    "ROCMExecutionProvider",
+    "MIGraphXExecutionProvider",
     "OpenVINOExecutionProvider",
     "CoreMLExecutionProvider",
     "CPUExecutionProvider",

machine-learning/immich_ml/sessions/ort.py

@@ -8,7 +8,7 @@ import onnxruntime as ort
 from numpy.typing import NDArray
 
 from immich_ml.models.constants import SUPPORTED_PROVIDERS
-from immich_ml.schemas import SessionNode
+from immich_ml.schemas import ModelPrecision, SessionNode
 
 from ..config import log, settings
 
@@ -90,8 +90,17 @@ class OrtSession:
             match provider:
                 case "CPUExecutionProvider":
                     options = {"arena_extend_strategy": "kSameAsRequested"}
-                case "CUDAExecutionProvider" | "ROCMExecutionProvider":
+                case "CUDAExecutionProvider":
                     options = {"arena_extend_strategy": "kSameAsRequested", "device_id": settings.device_id}
+                case "MIGraphXExecutionProvider":
+                    migraphx_dir = self.model_path.parent / "migraphx"
+                    # MIGraphX does not create the underlying folder and will crash if it does not exist
+                    migraphx_dir.mkdir(parents=True, exist_ok=True)
+                    options = {
+                        "device_id": settings.device_id,
+                        "migraphx_model_cache_dir": migraphx_dir.as_posix(),
+                        "migraphx_fp16_enable": "1" if settings.rocm_precision == ModelPrecision.FP16 else "0",
+                    }
                 case "OpenVINOExecutionProvider":
                     openvino_dir = self.model_path.parent / "openvino"
                     device = f"GPU.{settings.device_id}"

machine-learning/patches/0001-disable-rocm-conv-algo-caching.patch

@@ -1,179 +0,0 @@
-commit 16839b58d9b3c3162a67ce5d776b36d4d24e801f
-Author: mertalev <101130780+mertalev@users.noreply.github.com>
-Date:   Wed Mar 5 11:25:38 2025 -0500
-
-    disable algo caching (attributed to @dmnieto in https://github.com/microsoft/onnxruntime/pull/19567)
-
-diff --git a/onnxruntime/core/providers/rocm/nn/conv.cc b/onnxruntime/core/providers/rocm/nn/conv.cc
-index d7f47d07a8..4060a2af52 100644
---- a/onnxruntime/core/providers/rocm/nn/conv.cc
-+++ b/onnxruntime/core/providers/rocm/nn/conv.cc
-@@ -127,7 +127,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
-
-     if (w_dims_changed) {
-       s_.last_w_dims = gsl::make_span(w_dims);
--      s_.cached_benchmark_fwd_results.clear();
-     }
-
-     ORT_RETURN_IF_ERROR(conv_attrs_.ValidateInputShape(X->Shape(), W->Shape(), channels_last, channels_last));
-@@ -277,35 +276,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
-       HIP_CALL_THROW(hipMalloc(&s_.b_zero, malloc_size));
-       HIP_CALL_THROW(hipMemsetAsync(s_.b_zero, 0, malloc_size, Stream(context)));
-     }
--
--    if (!s_.cached_benchmark_fwd_results.contains(x_dims_miopen)) {
--      miopenConvAlgoPerf_t perf;
--      int algo_count = 1;
--      const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
--      static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
--      size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
--                                                                   : AlgoSearchWorkspaceSize;
--      IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
--      MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
--          GetMiopenHandle(context),
--          s_.x_tensor,
--          s_.x_data,
--          s_.w_desc,
--          s_.w_data,
--          s_.conv_desc,
--          s_.y_tensor,
--          s_.y_data,
--          1,            // requestedAlgoCount
--          &algo_count,  // returnedAlgoCount
--          &perf,
--          algo_search_workspace.get(),
--          max_ws_size,
--          false));  // Do not do exhaustive algo search.
--      s_.cached_benchmark_fwd_results.insert(x_dims_miopen, {perf.fwd_algo, perf.memory});
--    }
--    const auto& perf = s_.cached_benchmark_fwd_results.at(x_dims_miopen);
--    s_.fwd_algo = perf.fwd_algo;
--    s_.workspace_bytes = perf.memory;
-   } else {
-     // set Y
-     s_.Y = context->Output(0, TensorShape(s_.y_dims));
-@@ -319,6 +289,31 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
-       s_.y_data = reinterpret_cast<HipT*>(s_.Y->MutableData<T>());
-     }
-   }
-+
-+  miopenConvAlgoPerf_t perf;
-+  int algo_count = 1;
-+  const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
-+  static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
-+  size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
-+                                                                : AlgoSearchWorkspaceSize;
-+  IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
-+  MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
-+      GetMiopenHandle(context),
-+      s_.x_tensor,
-+      s_.x_data,
-+      s_.w_desc,
-+      s_.w_data,
-+      s_.conv_desc,
-+      s_.y_tensor,
-+      s_.y_data,
-+      1,            // requestedAlgoCount
-+      &algo_count,  // returnedAlgoCount
-+      &perf,
-+      algo_search_workspace.get(),
-+      max_ws_size,
-+      false));  // Do not do exhaustive algo search.
-+  s_.fwd_algo = perf.fwd_algo;
-+  s_.workspace_bytes = perf.memory;
-   return Status::OK();
- }
-
-diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
-index bc9846203e..d54218f258 100644
---- a/onnxruntime/core/providers/rocm/nn/conv.h
-+++ b/onnxruntime/core/providers/rocm/nn/conv.h
-@@ -108,9 +108,6 @@ class lru_unordered_map {
-   list_type lru_list_;
- };
-
--// cached miopen descriptors
--constexpr size_t MAX_CACHED_ALGO_PERF_RESULTS = 10000;
--
- template <typename AlgoPerfType>
- struct MiopenConvState {
-   // if x/w dims changed, update algo and miopenTensors
-@@ -148,9 +145,6 @@ struct MiopenConvState {
-     decltype(AlgoPerfType().memory) memory;
-   };
-
--  lru_unordered_map<TensorShapeVector, PerfFwdResultParams, vector_hash> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
--  lru_unordered_map<TensorShapeVector, PerfBwdResultParams, vector_hash> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
--
-   // Some properties needed to support asymmetric padded Conv nodes
-   bool post_slicing_required;
-   TensorShapeVector slice_starts;
-diff --git a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
-index 7447113fdf..a662e35b2e 100644
---- a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
-+++ b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
-@@ -76,7 +76,6 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
-
-       if (w_dims_changed) {
-         s_.last_w_dims = gsl::make_span(w_dims);
--        s_.cached_benchmark_bwd_results.clear();
-       }
-
-       ConvTransposeAttributes::Prepare p;
-@@ -126,35 +125,29 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
-       }
-
-       y_data = reinterpret_cast<HipT*>(p.Y->MutableData<T>());
--
--      if (!s_.cached_benchmark_bwd_results.contains(x_dims)) {
--        IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
--
--        miopenConvAlgoPerf_t perf;
--        int algo_count = 1;
--        MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
--            GetMiopenHandle(context),
--            s_.x_tensor,
--            x_data,
--            s_.w_desc,
--            w_data,
--            s_.conv_desc,
--            s_.y_tensor,
--            y_data,
--            1,
--            &algo_count,
--            &perf,
--            algo_search_workspace.get(),
--            AlgoSearchWorkspaceSize,
--            false));
--        s_.cached_benchmark_bwd_results.insert(x_dims, {perf.bwd_data_algo, perf.memory});
--      }
--
--      const auto& perf = s_.cached_benchmark_bwd_results.at(x_dims);
--      s_.bwd_data_algo = perf.bwd_data_algo;
--      s_.workspace_bytes = perf.memory;
-     }
-
-+    IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
-+    miopenConvAlgoPerf_t perf;
-+    int algo_count = 1;
-+    MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
-+        GetMiopenHandle(context),
-+        s_.x_tensor,
-+        x_data,
-+        s_.w_desc,
-+        w_data,
-+        s_.conv_desc,
-+        s_.y_tensor,
-+        y_data,
-+        1,
-+        &algo_count,
-+        &perf,
-+        algo_search_workspace.get(),
-+        AlgoSearchWorkspaceSize,
-+        false));
-+    s_.bwd_data_algo = perf.bwd_data_algo;
-+    s_.workspace_bytes = perf.memory;
-+
-     // The following block will be executed in case there has been no change in the shapes of the
-     // input and the filter compared to the previous run
-     if (!y_data) {

machine-learning/patches/0002-install-system-deps.patch

@@ -1,33 +0,0 @@
-diff --git a/dockerfiles/scripts/install_common_deps.sh b/dockerfiles/scripts/install_common_deps.sh
-index bbb672a99e..0dc652fbda 100644
---- a/dockerfiles/scripts/install_common_deps.sh
-+++ b/dockerfiles/scripts/install_common_deps.sh
-@@ -8,16 +8,23 @@ apt-get update && apt-get install -y --no-install-recommends \
-         curl \
-         libcurl4-openssl-dev \
-         libssl-dev \
--        python3-dev
-+        python3-dev \
-+        ccache
- 
- # Dependencies: conda
--wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-4.5.11-Linux-x86_64.sh -O ~/miniconda.sh --no-check-certificate && /bin/bash ~/miniconda.sh -b -p /opt/miniconda
-+wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-py312_25.9.1-1-Linux-x86_64.sh -O ~/miniconda.sh && /bin/bash ~/miniconda.sh -b -p /opt/miniconda
- rm ~/miniconda.sh
- /opt/miniconda/bin/conda clean -ya
- 
--pip install numpy
--pip install packaging
--pip install "wheel>=0.35.1"
-+# Dependencies: venv and packages
-+/opt/miniconda/bin/python3 -m venv /opt/rocm-venv
-+/opt/rocm-venv/bin/pip install --no-cache-dir --upgrade pip
-+/opt/rocm-venv/bin/pip install --no-cache-dir \
-+  "numpy==2.3.4" \
-+  "packaging==25.0" \
-+  "wheel==0.45.1" \
-+  "setuptools==80.9.0"
-+
- rm -rf /opt/miniconda/pkgs
- 
- # Dependencies: cmake

machine-learning/pyproject.toml

@@ -52,7 +52,7 @@ cuda = ["onnxruntime-gpu>=1.23.2,<2"]
 openvino = ["onnxruntime-openvino>=1.23.0,<2"]
 armnn = ["onnxruntime>=1.23.2,<2"]
 rknn = ["onnxruntime>=1.23.2,<2", "rknn-toolkit-lite2>=2.3.0,<3"]
-rocm = []
+rocm = ["onnxruntime-migraphx>=1.23.2,<2"]
 
 [tool.uv]
 compile-bytecode = true

machine-learning/test_main.py

@@ -179,7 +179,7 @@ class TestOrtSession:
     OV_EP = ["OpenVINOExecutionProvider", "CPUExecutionProvider"]
     CUDA_EP_OUT_OF_ORDER = ["CPUExecutionProvider", "CUDAExecutionProvider"]
     TRT_EP = ["TensorrtExecutionProvider", "CUDAExecutionProvider", "CPUExecutionProvider"]
-    ROCM_EP = ["ROCMExecutionProvider", "CPUExecutionProvider"]
+    ROCM_EP = ["MIGraphXExecutionProvider", "CPUExecutionProvider"]
     COREML_EP = ["CoreMLExecutionProvider", "CPUExecutionProvider"]
 
     @pytest.mark.providers(CPU_EP)
@@ -289,12 +289,38 @@ class TestOrtSession:
 
         assert session.provider_options == [{"arena_extend_strategy": "kSameAsRequested", "device_id": "1"}]
 
-    def test_sets_provider_options_for_rocm(self) -> None:
+    def test_sets_provider_options_for_rocm(self, mocker: MockerFixture) -> None:
+        model_path = "/cache/ViT-B-32__openai/textual/model.onnx"
         os.environ["MACHINE_LEARNING_DEVICE_ID"] = "1"
+        mkdir = mocker.patch("immich_ml.sessions.ort.Path.mkdir")
 
-        session = OrtSession("ViT-B-32__openai", providers=["ROCMExecutionProvider"])
+        session = OrtSession(model_path, providers=["MIGraphXExecutionProvider"])
 
-        assert session.provider_options == [{"arena_extend_strategy": "kSameAsRequested", "device_id": "1"}]
+        assert session.provider_options == [
+            {
+                "device_id": "1",
+                "migraphx_model_cache_dir": "/cache/ViT-B-32__openai/textual/migraphx",
+                "migraphx_fp16_enable": "0",
+            }
+        ]
+        mkdir.assert_called_once_with(parents=True, exist_ok=True)
+
+    def test_sets_rocm_to_fp16_if_enabled(self, path: mock.Mock, mocker: MockerFixture) -> None:
+        model_path = "/cache/ViT-B-32__openai/textual/model.onnx"
+        os.environ["MACHINE_LEARNING_DEVICE_ID"] = "1"
+        mocker.patch.object(settings, "rocm_precision", ModelPrecision.FP16)
+        mkdir = mocker.patch("immich_ml.sessions.ort.Path.mkdir")
+
+        session = OrtSession(model_path, providers=["MIGraphXExecutionProvider"])
+
+        assert session.provider_options == [
+            {
+                "device_id": "1",
+                "migraphx_model_cache_dir": "/cache/ViT-B-32__openai/textual/migraphx",
+                "migraphx_fp16_enable": "1",
+            }
+        ]
+        mkdir.assert_called_once_with(parents=True, exist_ok=True)
 
     def test_sets_provider_options_kwarg(self) -> None:
         session = OrtSession(

machine-learning/uv.lock

@@ -960,6 +960,9 @@ rknn = [
     { name = "onnxruntime" },
     { name = "rknn-toolkit-lite2" },
 ]
+rocm = [
+    { name = "onnxruntime-migraphx" },
+]
 
 [package.dev-dependencies]
 dev = [
@@ -1013,6 +1016,7 @@ requires-dist = [
     { name = "onnxruntime", marker = "extra == 'cpu'", specifier = ">=1.23.2,<2" },
     { name = "onnxruntime", marker = "extra == 'rknn'", specifier = ">=1.23.2,<2" },
     { name = "onnxruntime-gpu", marker = "extra == 'cuda'", specifier = ">=1.23.2,<2" },
+    { name = "onnxruntime-migraphx", marker = "extra == 'rocm'", specifier = ">=1.23.2,<2" },
     { name = "onnxruntime-openvino", marker = "extra == 'openvino'", specifier = ">=1.23.0,<2" },
     { name = "opencv-python-headless", specifier = ">=4.7.0.72,<5.0" },
     { name = "orjson", specifier = ">=3.9.5" },
@@ -1429,32 +1433,55 @@ wheels = [
 
 [[package]]
 name = "msgpack"
-version = "1.0.7"
+version = "1.1.2"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/c2/d5/5662032db1571110b5b51647aed4b56dfbd01bfae789fa566a2be1f385d1/msgpack-1.0.7.tar.gz", hash = "sha256:572efc93db7a4d27e404501975ca6d2d9775705c2d922390d878fcf768d92c87", size = 166311, upload-time = "2023-09-28T13:20:36.726Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/4d/f2/bfb55a6236ed8725a96b0aa3acbd0ec17588e6a2c3b62a93eb513ed8783f/msgpack-1.1.2.tar.gz", hash = "sha256:3b60763c1373dd60f398488069bcdc703cd08a711477b5d480eecc9f9626f47e", size = 173581, upload-time = "2025-10-08T09:15:56.596Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f9/b3/309de40dc7406b7f3492332c5ee2b492a593c2a9bb97ea48ebf2f5279999/msgpack-1.0.7-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:576eb384292b139821c41995523654ad82d1916da6a60cff129c715a6223ea84", size = 305096, upload-time = "2023-09-28T13:18:49.678Z" },
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