mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-14 20:48:00 +00:00
Update migraphx to rocm4.2 (#7994)
* update dockerfile for migraphx ep * update to rocm4.2 * code cleanup * fix error related to onnx unit tests
This commit is contained in:
Shucai Xiao
GitHub
parent
5809890ba2
commit
e7d7fa8fa2
3 changed files with 100 additions and 47 deletions
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@ -21,10 +21,15 @@ ENV LANG C.UTF-8
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# Install rocm
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RUN apt-get update && apt-get install -y gnupg2 --no-install-recommends curl && \
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curl -sL http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | apt-key add - && \
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sh -c 'echo deb [arch=amd64] http://repo.radeon.com/rocm/apt/3.7/ xenial main > /etc/apt/sources.list.d/rocm.list'
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sh -c 'echo deb [arch=amd64] http://repo.radeon.com/rocm/apt/4.2/ xenial main > /etc/apt/sources.list.d/rocm.list'
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RUN apt-get update &&\
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apt-get install -y sudo git bash build-essential cmake rocm-dkms libpython3.6-dev python3-pip miopen-hip rocblas half
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apt-get install -y sudo git bash build-essential rocm-dev libpython3.6-dev python3-pip miopen-hip \
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rocblas half aria2
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RUN aria2c -q -d /tmp -o cmake-3.20.3-Linux-x86_64.tar.gz \
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https://github.com/Kitware/CMake/releases/download/v3.20.3/cmake-3.20.3-Linux-x86_64.tar.gz &&\
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tar -zxf /tmp/cmake-3.20.3-Linux-x86_64.tar.gz --strip=1 -C /usr
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# Install rbuild
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RUN pip3 install https://github.com/RadeonOpenCompute/rbuild/archive/master.tar.gz
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@ -34,7 +39,7 @@ ENV PATH /opt/miniconda/bin:/code/cmake-3.20.3-linux-x86_64/bin:${PATH}
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# Install MIGraphX from source
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RUN mkdir -p /migraphx
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RUN cd /migraphx && git clone --depth=1 --branch migraphx_for_ort https://github.com/ROCmSoftwarePlatform/AMDMIGraphX src
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RUN cd /migraphx && rbuild package --cxx /opt/rocm-3.7.0/llvm/bin/clang++ -d /migraphx/deps -B /migraphx/build -S /migraphx/src/ -DPYTHON_EXECUTABLE=/usr/bin/python3
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RUN cd /migraphx && rbuild package --cxx /opt/rocm-4.2.0/llvm/bin/clang++ -d /migraphx/deps -B /migraphx/build -S /migraphx/src/ -DPYTHON_EXECUTABLE=/usr/bin/python3
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RUN dpkg -i /migraphx/build/*.deb
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RUN rm -rf /migraphx
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@ -12,7 +12,6 @@
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#include "core/graph/graph_utils.h"
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#include "core/platform/env.h"
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#include "core/session/onnxruntime_cxx_api.h"
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#include "core/optimizer/reshape_fusion.h"
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#include "migraphx_inc.h"
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#include "migraphx_execution_provider.h"
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#include "hip_allocator.h"
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@ -204,7 +203,8 @@ static bool get_migraphx_type(ONNXTensorElementDataType type,
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return true;
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}
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static bool can_eval_shape_general(const Graph& graph, const Node* node, const logging::Logger& logger)
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static bool can_eval_shape_general(const Graph& graph, const Node* node, const logging::Logger& logger, std::vector<NodeIndex>& input_nodes)
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{
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if (node == nullptr)
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{
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@ -213,6 +213,7 @@ static bool can_eval_shape_general(const Graph& graph, const Node* node, const l
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if (node->OpType() == "Shape")
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{
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input_nodes.push_back(node->Index());
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return true;
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}
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@ -245,7 +246,7 @@ static bool can_eval_shape_general(const Graph& graph, const Node* node, const l
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continue;
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}
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if (can_eval_shape_general(graph, input_node, logger))
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if (can_eval_shape_general(graph, input_node, logger, input_nodes))
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{
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continue;
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}
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@ -253,11 +254,15 @@ static bool can_eval_shape_general(const Graph& graph, const Node* node, const l
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return false;
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}
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input_nodes.push_back(node->Index());
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return true;
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}
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static bool can_eval_node_argument(const Graph& graph, const Node* node, std::vector<std::size_t> indices, const logging::Logger& logger)
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static bool can_eval_node_argument(const Graph& graph, const Node* node, std::vector<std::size_t> indices, const logging::Logger& logger, std::vector<NodeIndex>& input_nodes)
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{
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input_nodes.clear();
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for (auto& arg_index : indices)
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{
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const std::string& input_name = graph_utils::GetNodeInputName(*node, arg_index);
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@ -275,7 +280,7 @@ static bool can_eval_node_argument(const Graph& graph, const Node* node, std::ve
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}
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auto input_node = graph_utils::GetInputNode(*node, arg_index);
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if (!can_eval_shape_general(graph, input_node, logger))
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if (!can_eval_shape_general(graph, input_node, logger, input_nodes))
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{
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return false;
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}
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@ -285,6 +290,7 @@ static bool can_eval_node_argument(const Graph& graph, const Node* node, std::ve
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}
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static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, const Node* node, const logging::Logger& logger) {
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std::vector<NodeIndex> input_nodes;
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const auto& optype = node->OpType();
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// const auto& initializers = graph_viewer.GetAllInitializedTensors();
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if (optype == "ArgMax" or optype == "ArgMin") {
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@ -295,7 +301,7 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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return true;
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}
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} else if (optype == "ConstantOfShape") {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {0}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {0}, logger, input_nodes))
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{
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return true;
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}
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@ -320,7 +326,7 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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}
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} else if (optype == "Expand") {
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// MIGraphX only supports constant shape input values
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return true;
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}
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@ -390,12 +396,12 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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return true;
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}
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} else if (optype == "NonZero") {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {0}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {0}, logger, input_nodes))
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{
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return true;
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}
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} else if (optype == "OneHot") {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return true;
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}
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@ -403,7 +409,7 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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const auto& args = node->InputDefs();
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// if pad size is not constant, migraphx cannot support
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if (args.size() >= 2) {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return true;
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}
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@ -424,7 +430,7 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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// input value only applied to constant mode
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if (mode == "constant") {
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if (args.size() == 3) {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {2}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {2}, logger, input_nodes))
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{
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return true;
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}
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@ -434,14 +440,23 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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auto arg_num = node->InputDefs().size();
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std::vector<std::size_t> vec(arg_num);
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std::iota(vec.begin(), vec.end(), 0);
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, vec, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, vec, logger, input_nodes))
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{
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return true;
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}
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} else if (optype == "Reshape") {
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const auto& args = node->InputDefs();
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if (args.size() == 2) {
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger))
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return false;
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}
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return true;
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}
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} else if (optype == "ReduceSum") {
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const auto& args = node->InputDefs();
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if (args.size() == 2) {
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return false;
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}
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@ -455,7 +470,7 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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std::vector<std::size_t> vec(arg_num);
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std::iota(vec.begin(), vec.end(), 0);
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vec.erase(vec.begin());
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, vec, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, vec, logger, input_nodes))
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{
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return true;
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}
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@ -490,18 +505,36 @@ static bool IsUnsupportedOpMode(const onnxruntime::GraphViewer& graph_viewer, co
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return true;
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}
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}
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const auto& args = node->InputDefs();
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if (args.size() == 2) {
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return false;
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}
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return true;
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}
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} else if (optype == "Tile") {
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger))
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if (!can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return true;
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}
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} else if (optype == "Unsqueeze" or optype == "Squeeze") {
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const auto& args = node->InputDefs();
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if (args.size() == 2) {
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, input_nodes))
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{
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return false;
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}
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return true;
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}
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}
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//Op doesn't fall into known any of unsupported modes.
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return false;
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}
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void SubgraphPostProcessing(const onnxruntime::GraphViewer& graph_viewer, std::vector<std::vector<NodeIndex>>& clusters)
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void SubgraphPostProcessing(const onnxruntime::GraphViewer& graph_viewer, std::vector<std::vector<NodeIndex>>& clusters, const logging::Logger& logger)
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{
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// If the number of nodes in the graph is less than 5, do nothing
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// this is to deal with onnx unit tests
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@ -516,6 +549,28 @@ void SubgraphPostProcessing(const onnxruntime::GraphViewer& graph_viewer, std::v
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std::unordered_set<std::string> op_names = {"AveragePool", "Conv", "Gemm", "LRN", "MatMul", "MaxPool"};
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auto it = std::remove_if(clusters.begin(), clusters.end(), [&](auto git) {
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for (auto index : git)
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{
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auto node = graph_viewer.GetNode(index);
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if (node->OpType() == "Reshape")
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{
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const auto& args = node->InputDefs();
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if (args.size() == 2) {
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std::vector<NodeIndex> node_inputs;
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if (can_eval_node_argument(graph_viewer.GetGraph(), node, {1}, logger, node_inputs))
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{
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return (not std::all_of(node_inputs.begin(), node_inputs.end(), [&](auto index) {
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return std::find(git.begin(), git.end(), index) != git.end();
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}));
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}
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else
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{
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return true;
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}
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}
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}
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}
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// if 6 operators or more
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if (git.size() > 5)
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{
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@ -640,21 +695,19 @@ static std::vector<NodeIndex>
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GetUnsupportedNodeIndices(const GraphViewer& graph_viewer,
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/*out*/ std::unordered_set<std::string>& mgx_required_initializers,
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const logging::Logger& logger) {
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static std::set<std::string> mgx_supported_ops = {"Abs", "Acos", "Acosh", "Add", "ArgMax", "ArgMin",
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"Asin", "Asinh", "Atan", "Atanh", "AveragePool", "BatchNormalization", "Cast", "Ceil", "Clip",
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"Concat", "Constant", "ConstantFill", "ConstantOfShape", "Conv", "Cos", "Cosh",
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"Div", "Dropout", "Elu", "Equal", "Erf", "Exp", "Expand", "Flatten", "Floor", "GRU", "Gather",
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"GatherElements", "Gemm", "GlobalAveragePool", "GlobalMaxPool", "Identity", "ImageScaler",
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"InstanceNormalization", "LRN", "LSTM", "LeakyRelu", "Log", "LogSoftmax", "MatMul", "Max",
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"MaxPool", "Min", "Mul", "Neg", "NonZero", "OneHot", "Pad", "Pow", "PRelu",
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"RNN", "Range", "Reciprocal", "ReduceL1", "ReduceL2", "ReduceLogSum", "ReduceLogSumExp", "ReduceMax",
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"ReduceMean", "ReduceMin", "ReduceProd", "ReduceSum", "ReduceSumSquare", "Relu", "Reshape",
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"Round", "Shape", "Sigmoid", "Sign", "Sin", "Sinh", "Slice", "Softmax", "Split", "Sqrt", "Squeeze",
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"Sub", "Sum", "Tan", "Tanh", "Tile", "Transpose", "Unsqueeze", "Where"};
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static std::set<std::string> mgx_supported_ops = {"Abs", "Acos", "Acosh", "Add", "And", "ArgMax", "ArgMin",
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"Asin", "Asinh", "Atan", "Atanh", "AveragePool", "BatchNormalization", "Cast", "Ceil", "Clip",
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"Concat", "Constant", "ConstantFill", "ConstantOfShape", "Conv", "Cos", "Cosh", "DequantizeLinear",
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"Div", "Dropout", "Elu", "Equal", "Erf", "Exp", "Expand", "Flatten", "Floor", "GRU", "Gather",
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"GatherElements", "Gemm", "GlobalAveragePool", "GlobalMaxPool", "Greater", "Identity", "ImageScaler",
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"InstanceNormalization", "LRN", "LSTM", "LeakyRelu", "Less", "LessOrEqual", "Log", "LogSoftmax",
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"MatMul", "Max", "MaxPool", "Min", "Mul", "Neg", "NonZero", "OneHot", "Or", "Pad", "Pow", "PRelu",
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"QuantizeLinear", "RNN", "Range", "Reciprocal", "ReduceL1", "ReduceL2", "ReduceLogSum", "ReduceLogSumExp",
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"ReduceMax", "ReduceMean", "ReduceMin", "ReduceProd", "ReduceSum", "ReduceSumSquare", "Relu", "Reshape",
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"Round", "Selu", "Shape", "Sigmoid", "Sign", "Sin", "Sinh", "Slice", "Softmax", "Split", "Sqrt", "Squeeze",
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"Sub", "Sum", "Tan", "Tanh", "Tile", "Transpose", "Unsqueeze", "Where", "Xor"};
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std::vector<NodeIndex> unsupported_nodes_idx;
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for (const auto& node_idx : graph_viewer.GetNodesInTopologicalOrder()) {
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// auto node = graph_viewer.GetNode(node_idx);
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// print_node_info(node);
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if (IsNodeSupported(mgx_supported_ops, graph_viewer, node_idx, logger)) {
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// Collect inputs that are initializers
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graph_viewer.GetNode(node_idx)->ForEachDef([&mgx_required_initializers, &graph_viewer](const onnxruntime::NodeArg& node_arg, bool is_input) {
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@ -810,6 +863,7 @@ MIGraphXExecutionProvider::GetCapability(const onnxruntime::GraphViewer& graph_v
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std::unordered_map<std::string, std::size_t> map_dim_param_values;
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onnxruntime::Graph& graph_build = model.MainGraph();
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for (const auto& node : graph_viewer.Nodes()) {
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std::vector<onnxruntime::NodeArg*> inputs, outputs;
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for (auto input : node.InputDefs()) {
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@ -835,6 +889,7 @@ MIGraphXExecutionProvider::GetCapability(const onnxruntime::GraphViewer& graph_v
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model_proto.set_ir_version(ONNX_NAMESPACE::Version::IR_VERSION);
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auto status = graph_build.Resolve();
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std::string onnx_string_buffer;
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model_proto.SerializeToString(&onnx_string_buffer);
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@ -870,18 +925,10 @@ MIGraphXExecutionProvider::GetCapability(const onnxruntime::GraphViewer& graph_v
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AppendNodesToSubGraph(graph_viewer.GetNodesInTopologicalOrder(), inputs, outputs, result);
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} else { // unsupported_nodes_idx.empty()
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// migraphx cannot handle Loop, If, and SoftmaxCrossEntropyLoss for now,
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// so if a model contain any of these operators, fall back to CPU
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std::unordered_set<std::string> vec_ops = {"If", "Loop", "SoftmaxCrossEntropyLoss"};
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if (std::any_of(unsupported_nodes.begin(), unsupported_nodes.end(), [&](auto i) {
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return (vec_ops.count(graph_viewer.GetNode(i)->OpType()) > 0);
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})) {
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return result;
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}
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auto mgx_clusters = GetPartitionedSubgraphs(graph_viewer.GetNodesInTopologicalOrder(), unsupported_nodes);
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// check whether a subgrap should fallback to CPU
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SubgraphPostProcessing(graph_viewer, mgx_clusters);
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SubgraphPostProcessing(graph_viewer, mgx_clusters, *GetLogger());
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for (const auto& this_cluster : mgx_clusters) {
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std::vector<std::string> cluster_inputs, cluster_outputs;
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@ -970,7 +1017,6 @@ Status MIGraphXExecutionProvider::Compile(const std::vector<onnxruntime::Node*>&
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std::vector<NodeComputeInfo>& node_compute_funcs) {
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migraphx::onnx_options options;
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bool no_input_shape = false;
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for (const auto& fused_node : fused_nodes) {
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// map parameter input name to index
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std::unordered_map<std::string, std::size_t> input_name_index;
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@ -77,9 +77,7 @@ def create_backend_test(testname=None):
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if c2.supports_device('MIGRAPHX'):
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current_failing_tests += [
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'^test_constant_pad_cpu', '^test_softmax_axis_1_cpu', '^test_softmax_axis_0_cpu',
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'^test_softmax_default_axis_cpu', '^test_round_cpu', '^test_lrn_default_cpu', '^test_lrn_cpu',
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'^test_logsoftmax_axis_0_cpu', '^test_logsoftmax_axis_1_cpu', '^test_logsoftmax_default_axis_cpu',
|
||||
'^test_constant_pad_cpu', '^test_round_cpu', '^test_lrn_default_cpu', '^test_lrn_cpu',
|
||||
'^test_dynamicquantizelinear_expanded_cpu', '^test_dynamicquantizelinear_max_adjusted_cpu',
|
||||
'^test_dynamicquantizelinear_max_adjusted_expanded_cpu', '^test_dynamicquantizelinear_min_adjusted_cpu',
|
||||
'^test_dynamicquantizelinear_min_adjusted_expanded_cpu',
|
||||
|
|
@ -88,7 +86,11 @@ def create_backend_test(testname=None):
|
|||
'^test_operator_symbolic_override_nested_cpu',
|
||||
'^test_negative_log_likelihood_loss',
|
||||
'^test_softmax_cross_entropy',
|
||||
'^test_greater_equal', '^test_less_equal'
|
||||
'^test_greater_equal',
|
||||
'^test_if_seq_cpu',
|
||||
'^test_loop13_seq_cpu',
|
||||
'^test_sequence_insert_at_back_cpu',
|
||||
'^test_sequence_insert_at_front_cpu'
|
||||
]
|
||||
|
||||
# Skip these tests for a "pure" DML onnxruntime python wheel. We keep these tests enabled for instances where both DML and CUDA
|
||||
|
|
|
|||
Loading…
Reference in a new issue