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feat: ROCm 7.2 and MIGraphX support (#26178)
This commit is contained in:
Kishor Prins
GitHub
parent
177d1c9a30
commit
dd9046508d
@ -50,6 +50,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
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- The GPU must be supported by ROCm. If it isn't officially supported, you can attempt to use the `HSA_OVERRIDE_GFX_VERSION` environmental variable: `HSA_OVERRIDE_GFX_VERSION=<a supported version, e.g. 10.3.0>`. If this doesn't work, you might need to also set `HSA_USE_SVM=0`.
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- The ROCm image is quite large and requires at least 35GiB of free disk space. However, pulling later updates to the service through Docker will generally only amount to a few hundred megabytes as the rest will be cached.
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- This backend is new and may experience some issues. For example, GPU power consumption can be higher than usual after running inference, even if the machine learning service is idle. In this case, it will only go back to normal after being idle for 5 minutes (configurable with the [MACHINE_LEARNING_MODEL_TTL](/install/environment-variables) setting).
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- MIGraphX is a new backend for AMD cards, which compiles models at runtime. As such, the first few inferences will be slow.
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#### OpenVINO
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@ -22,48 +22,7 @@ FROM builder-cpu AS builder-rknn
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# Warning: 25GiB+ disk space required to pull this image
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# TODO: find a way to reduce the image size
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FROM rocm/dev-ubuntu-24.04:6.4.4-complete@sha256:31418ac10a3769a71eaef330c07280d1d999d7074621339b8f93c484c35f6078 AS builder-rocm
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# renovate: datasource=github-releases depName=Microsoft/onnxruntime
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ARG ONNXRUNTIME_VERSION="v1.22.1"
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WORKDIR /code
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RUN apt-get update && apt-get install -y --no-install-recommends wget git
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RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.31.9/cmake-3.31.9-linux-x86_64.sh && \
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chmod +x cmake-3.31.9-linux-x86_64.sh && \
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mkdir -p /code/cmake-3.31.9-linux-x86_64 && \
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./cmake-3.31.9-linux-x86_64.sh --skip-license --prefix=/code/cmake-3.31.9-linux-x86_64 && \
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rm cmake-3.31.9-linux-x86_64.sh
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RUN git clone --single-branch --branch "${ONNXRUNTIME_VERSION}" --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime
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WORKDIR /code/onnxruntime
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# Fix for multi-threading based on comments in https://github.com/microsoft/onnxruntime/pull/19567
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# TODO: find a way to fix this without disabling algo caching
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COPY ./patches/* /tmp/
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RUN git apply /tmp/*.patch
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RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh
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ENV PATH=/opt/rocm-venv/bin:/code/cmake-3.31.9-linux-x86_64/bin:${PATH}
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ENV CCACHE_DIR="/ccache"
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# Note: the `parallel` setting uses a substantial amount of RAM
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RUN --mount=type=cache,target=/ccache \
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./build.sh \
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--allow_running_as_root \
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--config Release \
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--build_wheel \
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--update \
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--build \
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--parallel 48 \
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--cmake_extra_defines \
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ONNXRUNTIME_VERSION="${ONNXRUNTIME_VERSION}" \
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CMAKE_HIP_ARCHITECTURES="gfx900;gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201" \
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--skip_tests \
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--use_rocm \
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--rocm_home=/opt/rocm \
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--use_cache \
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--compile_no_warning_as_error
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RUN mv /code/onnxruntime/build/Linux/Release/dist/*.whl /opt/
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FROM rocm/dev-ubuntu-24.04:7.2-complete@sha256:86e11093b4a7ec2a79b1b6701d10e840a6994f21c7e05929b51eb9be361c683a AS builder-rocm
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FROM builder-${DEVICE} AS builder
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@ -79,9 +38,6 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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--mount=type=bind,source=uv.lock,target=uv.lock \
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--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
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uv sync --frozen --extra ${DEVICE} --no-dev --no-editable --no-install-project --compile-bytecode --no-progress --active --link-mode copy
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RUN if [ "$DEVICE" = "rocm" ]; then \
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uv pip install /opt/onnxruntime_rocm-*.whl; \
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fi
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FROM python:3.11-slim-bookworm@sha256:04cd27899595a99dfe77709d96f08876bf2ee99139ee2f0fe9ac948005034e5b AS prod-cpu
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@ -120,7 +76,11 @@ COPY --from=builder-cuda /usr/local/bin/python3 /usr/local/bin/python3
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COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11
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COPY --from=builder-cuda /usr/local/lib/libpython3.11.so /usr/local/lib/libpython3.11.so
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FROM rocm/dev-ubuntu-24.04:6.4.4-complete@sha256:31418ac10a3769a71eaef330c07280d1d999d7074621339b8f93c484c35f6078 AS prod-rocm
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FROM rocm/dev-ubuntu-24.04:7.2-complete@sha256:86e11093b4a7ec2a79b1b6701d10e840a6994f21c7e05929b51eb9be361c683a AS prod-rocm
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RUN apt-get update && apt-get install --no-install-recommends -yqq migraphx miopen-hip && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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FROM prod-cpu AS prod-armnn
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@ -79,6 +79,7 @@ class Settings(BaseSettings):
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preload: PreloadModelData | None = None
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max_batch_size: MaxBatchSize | None = None
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openvino_precision: ModelPrecision = ModelPrecision.FP32
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rocm_precision: ModelPrecision = ModelPrecision.FP32
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@property
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def device_id(self) -> str:
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@ -90,7 +90,7 @@ _PADDLE_MODELS = {
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SUPPORTED_PROVIDERS = [
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"CUDAExecutionProvider",
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"ROCMExecutionProvider",
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"MIGraphXExecutionProvider",
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"OpenVINOExecutionProvider",
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"CoreMLExecutionProvider",
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"CPUExecutionProvider",
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@ -8,7 +8,7 @@ import onnxruntime as ort
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from numpy.typing import NDArray
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from immich_ml.models.constants import SUPPORTED_PROVIDERS
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from immich_ml.schemas import SessionNode
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from immich_ml.schemas import ModelPrecision, SessionNode
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from ..config import log, settings
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@ -90,8 +90,17 @@ class OrtSession:
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match provider:
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case "CPUExecutionProvider":
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options = {"arena_extend_strategy": "kSameAsRequested"}
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case "CUDAExecutionProvider" | "ROCMExecutionProvider":
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case "CUDAExecutionProvider":
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options = {"arena_extend_strategy": "kSameAsRequested", "device_id": settings.device_id}
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case "MIGraphXExecutionProvider":
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migraphx_dir = self.model_path.parent / "migraphx"
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# MIGraphX does not create the underlying folder and will crash if it does not exist
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migraphx_dir.mkdir(parents=True, exist_ok=True)
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options = {
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"device_id": settings.device_id,
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"migraphx_model_cache_dir": migraphx_dir.as_posix(),
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"migraphx_fp16_enable": "1" if settings.rocm_precision == ModelPrecision.FP16 else "0",
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}
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case "OpenVINOExecutionProvider":
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openvino_dir = self.model_path.parent / "openvino"
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device = f"GPU.{settings.device_id}"
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@ -1,179 +0,0 @@
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commit 16839b58d9b3c3162a67ce5d776b36d4d24e801f
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Author: mertalev <101130780+mertalev@users.noreply.github.com>
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Date: Wed Mar 5 11:25:38 2025 -0500
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disable algo caching (attributed to @dmnieto in https://github.com/microsoft/onnxruntime/pull/19567)
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diff --git a/onnxruntime/core/providers/rocm/nn/conv.cc b/onnxruntime/core/providers/rocm/nn/conv.cc
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index d7f47d07a8..4060a2af52 100644
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--- a/onnxruntime/core/providers/rocm/nn/conv.cc
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+++ b/onnxruntime/core/providers/rocm/nn/conv.cc
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@@ -127,7 +127,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
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if (w_dims_changed) {
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s_.last_w_dims = gsl::make_span(w_dims);
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- s_.cached_benchmark_fwd_results.clear();
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}
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ORT_RETURN_IF_ERROR(conv_attrs_.ValidateInputShape(X->Shape(), W->Shape(), channels_last, channels_last));
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@@ -277,35 +276,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
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HIP_CALL_THROW(hipMalloc(&s_.b_zero, malloc_size));
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HIP_CALL_THROW(hipMemsetAsync(s_.b_zero, 0, malloc_size, Stream(context)));
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}
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-
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- if (!s_.cached_benchmark_fwd_results.contains(x_dims_miopen)) {
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- miopenConvAlgoPerf_t perf;
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- int algo_count = 1;
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- const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
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- static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
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- size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
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- : AlgoSearchWorkspaceSize;
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- IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
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- MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
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- GetMiopenHandle(context),
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- s_.x_tensor,
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- s_.x_data,
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- s_.w_desc,
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- s_.w_data,
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- s_.conv_desc,
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- s_.y_tensor,
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- s_.y_data,
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- 1, // requestedAlgoCount
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- &algo_count, // returnedAlgoCount
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- &perf,
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- algo_search_workspace.get(),
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- max_ws_size,
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- false)); // Do not do exhaustive algo search.
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- s_.cached_benchmark_fwd_results.insert(x_dims_miopen, {perf.fwd_algo, perf.memory});
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- }
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- const auto& perf = s_.cached_benchmark_fwd_results.at(x_dims_miopen);
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- s_.fwd_algo = perf.fwd_algo;
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- s_.workspace_bytes = perf.memory;
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} else {
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// set Y
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s_.Y = context->Output(0, TensorShape(s_.y_dims));
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@@ -319,6 +289,31 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
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s_.y_data = reinterpret_cast<HipT*>(s_.Y->MutableData<T>());
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}
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}
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+
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+ miopenConvAlgoPerf_t perf;
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+ int algo_count = 1;
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+ const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
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+ static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
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+ size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
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+ : AlgoSearchWorkspaceSize;
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+ IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
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+ MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
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+ GetMiopenHandle(context),
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+ s_.x_tensor,
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+ s_.x_data,
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+ s_.w_desc,
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+ s_.w_data,
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+ s_.conv_desc,
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+ s_.y_tensor,
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+ s_.y_data,
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+ 1, // requestedAlgoCount
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+ &algo_count, // returnedAlgoCount
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+ &perf,
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+ algo_search_workspace.get(),
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+ max_ws_size,
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+ false)); // Do not do exhaustive algo search.
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+ s_.fwd_algo = perf.fwd_algo;
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+ s_.workspace_bytes = perf.memory;
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return Status::OK();
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}
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diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
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index bc9846203e..d54218f258 100644
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--- a/onnxruntime/core/providers/rocm/nn/conv.h
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+++ b/onnxruntime/core/providers/rocm/nn/conv.h
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@@ -108,9 +108,6 @@ class lru_unordered_map {
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list_type lru_list_;
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};
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-// cached miopen descriptors
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-constexpr size_t MAX_CACHED_ALGO_PERF_RESULTS = 10000;
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-
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template <typename AlgoPerfType>
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struct MiopenConvState {
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// if x/w dims changed, update algo and miopenTensors
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@@ -148,9 +145,6 @@ struct MiopenConvState {
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decltype(AlgoPerfType().memory) memory;
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};
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- lru_unordered_map<TensorShapeVector, PerfFwdResultParams, vector_hash> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
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- lru_unordered_map<TensorShapeVector, PerfBwdResultParams, vector_hash> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
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-
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// Some properties needed to support asymmetric padded Conv nodes
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bool post_slicing_required;
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TensorShapeVector slice_starts;
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diff --git a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
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index 7447113fdf..a662e35b2e 100644
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--- a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
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+++ b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
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@@ -76,7 +76,6 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
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if (w_dims_changed) {
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s_.last_w_dims = gsl::make_span(w_dims);
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- s_.cached_benchmark_bwd_results.clear();
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}
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ConvTransposeAttributes::Prepare p;
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@@ -126,35 +125,29 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
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}
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y_data = reinterpret_cast<HipT*>(p.Y->MutableData<T>());
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-
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- if (!s_.cached_benchmark_bwd_results.contains(x_dims)) {
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- IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
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-
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- miopenConvAlgoPerf_t perf;
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- int algo_count = 1;
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- MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
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- GetMiopenHandle(context),
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- s_.x_tensor,
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- x_data,
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- s_.w_desc,
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- w_data,
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- s_.conv_desc,
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- s_.y_tensor,
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- y_data,
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- 1,
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- &algo_count,
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- &perf,
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- algo_search_workspace.get(),
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- AlgoSearchWorkspaceSize,
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- false));
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- s_.cached_benchmark_bwd_results.insert(x_dims, {perf.bwd_data_algo, perf.memory});
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- }
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-
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- const auto& perf = s_.cached_benchmark_bwd_results.at(x_dims);
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- s_.bwd_data_algo = perf.bwd_data_algo;
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- s_.workspace_bytes = perf.memory;
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}
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+ IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
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+ miopenConvAlgoPerf_t perf;
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+ int algo_count = 1;
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+ MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
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+ GetMiopenHandle(context),
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+ s_.x_tensor,
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+ x_data,
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+ s_.w_desc,
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+ w_data,
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+ s_.conv_desc,
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+ s_.y_tensor,
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+ y_data,
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+ 1,
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+ &algo_count,
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+ &perf,
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+ algo_search_workspace.get(),
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+ AlgoSearchWorkspaceSize,
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+ false));
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+ s_.bwd_data_algo = perf.bwd_data_algo;
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+ s_.workspace_bytes = perf.memory;
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+
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// The following block will be executed in case there has been no change in the shapes of the
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// input and the filter compared to the previous run
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if (!y_data) {
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@ -1,33 +0,0 @@
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diff --git a/dockerfiles/scripts/install_common_deps.sh b/dockerfiles/scripts/install_common_deps.sh
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index bbb672a99e..0dc652fbda 100644
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--- a/dockerfiles/scripts/install_common_deps.sh
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+++ b/dockerfiles/scripts/install_common_deps.sh
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@@ -8,16 +8,23 @@ apt-get update && apt-get install -y --no-install-recommends \
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curl \
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libcurl4-openssl-dev \
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libssl-dev \
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- python3-dev
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+ python3-dev \
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+ ccache
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# Dependencies: conda
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-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
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+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
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rm ~/miniconda.sh
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/opt/miniconda/bin/conda clean -ya
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-pip install numpy
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-pip install packaging
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-pip install "wheel>=0.35.1"
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+# Dependencies: venv and packages
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+/opt/miniconda/bin/python3 -m venv /opt/rocm-venv
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+/opt/rocm-venv/bin/pip install --no-cache-dir --upgrade pip
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+/opt/rocm-venv/bin/pip install --no-cache-dir \
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+ "numpy==2.3.4" \
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+ "packaging==25.0" \
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+ "wheel==0.45.1" \
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+ "setuptools==80.9.0"
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+
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rm -rf /opt/miniconda/pkgs
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# Dependencies: cmake
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@ -52,7 +52,7 @@ cuda = ["onnxruntime-gpu>=1.23.2,<2"]
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openvino = ["onnxruntime-openvino>=1.23.0,<2"]
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armnn = ["onnxruntime>=1.23.2,<2"]
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rknn = ["onnxruntime>=1.23.2,<2", "rknn-toolkit-lite2>=2.3.0,<3"]
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rocm = []
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||||
rocm = ["onnxruntime-migraphx>=1.23.2,<2"]
|
||||
|
||||
[tool.uv]
|
||||
compile-bytecode = true
|
||||
|
||||
@ -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(
|
||||
|
||||
93
machine-learning/uv.lock
generated
93
machine-learning/uv.lock
generated
@ -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"
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source = { registry = "https://pypi.org/simple" }
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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" }
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wheels = [
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Loading…
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Reference in New Issue
Block a user