mirror of
https://github.com/saymrwulf/onnxruntime.git
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Add onnx single node test data to tests (#12822)
1. add node test data to current model tests 2. support opset version to filter tests. 3. remove old filter based on onnx version. To avoid confusion, ONLY support opset version filter in onnxruntime_test_all 4. support read onnx test data from absolute path on Windows.
This commit is contained in:
Yi Zhang
GitHub
parent
a5d70d8609
commit
8356e3b9b0
10 changed files with 95 additions and 96 deletions
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@ -343,7 +343,7 @@ class OnnxTestCase : public ITestCase {
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const std::string& GetNodeName() const override { return model_info_->GetNodeName(); }
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const PATH_CHAR_TYPE* GetModelUrl() const override { return model_info_->GetModelUrl(); }
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const std::string& GetTestCaseName() const override { return test_case_name_; }
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std::string GetTestCaseVersion() const override { return model_info_->GetModelVersion(); }
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std::string GetTestCaseVersion() const override { return model_info_->GetNominalOpsetVersion(); }
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void LoadTestData(size_t id, onnxruntime::test::HeapBuffer& b, std::unordered_map<std::string, Ort::Value>&,
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bool is_input) const override;
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@ -66,7 +66,7 @@ class TestModelInfo {
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virtual int GetOutputCount() const = 0;
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virtual const std::string& GetInputName(size_t i) const = 0;
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virtual const std::string& GetOutputName(size_t i) const = 0;
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virtual std::string GetModelVersion() const { return ""; }
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virtual std::string GetNominalOpsetVersion() const { return ""; }
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virtual ~TestModelInfo() = default;
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#if !defined(ORT_MINIMAL_BUILD)
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@ -58,15 +58,13 @@ void OnnxModelInfo::InitOnnxModelInfo(_In_ const PATH_CHAR_TYPE* model_url) { /
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const std::string model_url_string = ToUTF8String(model_url);
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re2::StringPiece text(model_url_string);
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re2::StringPiece submatch;
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re2::RE2 regex("onnx[0-9a-z]{3}", re2::RE2::Options()); //e.g. onnx141, onnx150, onnxtip
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if (!regex.ok()) {
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ORT_THROW("Failed to parse regex: onnx[0-9a-z]{3}");
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}
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bool match = regex.Match(text, 0, text.length(), re2_anchor, &submatch, 1);
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re2::RE2 regex_op("opset[0-9a-z]{1,2}", re2::RE2::Options()); // e.g. opset14, opset15
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bool match = regex_op.Match(text, 0, text.length(), re2_anchor, &submatch, 1);
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if (match) {
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onnx_commit_tag_.assign(submatch.data(), submatch.length());
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onnx_nominal_opset_vesion_.assign(submatch.data(), submatch.length());
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} else {
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onnx_commit_tag_ = TestModelInfo::unknown_version;
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onnx_nominal_opset_vesion_ = TestModelInfo::unknown_version;
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}
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}
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for (const auto& opset : model_pb.opset_import()) {
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@ -102,9 +100,6 @@ void OnnxModelInfo::InitOrtModelInfo(_In_ const PATH_CHAR_TYPE* model_url) {
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std::ifstream bytes_stream(model_location, std::ifstream::in | std::ifstream::binary);
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bytes_stream.read(reinterpret_cast<char*>(bytes.data()), num_bytes);
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// TODO use ort format version here?
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onnx_commit_tag_ = TestModelInfo::unknown_version;
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// TODO, verify it is a valid ort format
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// TODO, version matches the ORT version
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const auto* fbs_session = fbs::GetInferenceSession(bytes.data());
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@ -8,7 +8,8 @@
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class OnnxModelInfo : public TestModelInfo {
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private:
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std::string node_name_;
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std::string onnx_commit_tag_;
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// Due to performance, the opset version is get from directory name, so it's nominal
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std::string onnx_nominal_opset_vesion_;
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std::vector<ONNX_NAMESPACE::ValueInfoProto> input_value_info_;
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std::vector<ONNX_NAMESPACE::ValueInfoProto> output_value_info_;
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std::unordered_map<std::string, int64_t> domain_to_version_;
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@ -32,7 +33,7 @@ class OnnxModelInfo : public TestModelInfo {
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}
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const PATH_CHAR_TYPE* GetModelUrl() const override { return model_url_.c_str(); }
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std::string GetModelVersion() const override { return onnx_commit_tag_; }
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std::string GetNominalOpsetVersion() const override { return onnx_nominal_opset_vesion_; }
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const std::string& GetNodeName() const override { return node_name_; }
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@ -65,12 +65,12 @@ namespace {
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struct BrokenTest {
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std::string test_name_;
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std::string reason_;
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std::set<std::string> broken_versions_ = {}; // apply to all versions if empty
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std::set<std::string> broken_opset_versions_ = {}; // apply to all versions if empty
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BrokenTest(std::string name, std::string reason) : test_name_(std::move(name)), reason_(std::move(reason)) {
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}
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BrokenTest(std::string name, std::string reason, const std::initializer_list<std::string>& versions)
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: test_name_(std::move(name)), reason_(std::move(reason)), broken_versions_(versions) {
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BrokenTest(std::string name, std::string reason, const std::initializer_list<std::string>& opversions)
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: test_name_(std::move(name)), reason_(std::move(reason)), broken_opset_versions_(opversions) {
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}
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bool operator<(const struct BrokenTest& test) const {
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@ -123,7 +123,6 @@ TEST_P(ModelTest, Run) {
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return;
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}
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#endif
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// TODO: filter model based on opset
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std::set<BrokenTest> broken_tests = {
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{"slice_neg_steps",
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"Type parameter (Tind) bound to different types (tensor(int64) and tensor(int32) in node ()."},
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@ -133,9 +132,9 @@ TEST_P(ModelTest, Run) {
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{"cast_FLOAT_to_BFLOAT16", "expect uint16 got bfloat16"},
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{"mnist", "Input data isn't in valid range"},
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{"BERT_Squad", "test data bug"},
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{"constantofshape_float_ones", "test data bug", {"onnx141", "onnx150"}},
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{"constantofshape_int_zeros", "test data bug", {"onnx141", "onnx150"}},
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{"cast_STRING_to_FLOAT", "Linux CI has old ONNX python package with bad test data", {"onnx141"}},
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{"constantofshape_float_ones", "test data bug", {"opset9", "opset10"}},
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{"constantofshape_int_zeros", "test data bug", {"opset9", "opset10"}},
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{"cast_STRING_to_FLOAT", "Linux CI has old ONNX python package with bad test data", {"opset9", "opset10"}},
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// Numpy float to string has unexpected rounding for some results given numpy default precision is meant to be 8.
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// "e.g. 0.296140194 -> '0.2961402' not '0.29614019'. ORT produces the latter with precision set to 8,
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// which doesn't match the expected output that was generated with numpy.
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@ -143,7 +142,7 @@ TEST_P(ModelTest, Run) {
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{"tf_nasnet_large", "disable temporarily"},
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{"tf_nasnet_mobile", "disable temporarily"},
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{"tf_pnasnet_large", "disable temporarily"},
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{"shrink", "test case is wrong", {"onnx141"}},
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{"shrink", "test case is wrong", {"opset9"}},
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{"maxpool_with_argmax_2d_precomputed_strides", "ShapeInferenceError"},
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{"tf_inception_v2", "result mismatch"},
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{"tf_resnet_v1_50", "result mismatch when Conv BN Fusion is applied"},
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@ -181,7 +180,7 @@ TEST_P(ModelTest, Run) {
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{"castlike_FLOAT_to_BFLOAT16_expanded", "type error", {}},
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{"castlike_FLOAT_to_STRING", "type error", {}},
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{"castlike_FLOAT_to_STRING_expanded", "type error", {}},
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{"convtranspose_autopad_same", "Test data has been corrected in ONNX 1.10.", {"onnx180", "onnx181", "onnx190"}},
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{"convtranspose_autopad_same", "Test data has been corrected in ONNX 1.10.", {"opset13", "opset14"}},
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{"gru_batchwise", "type error", {}},
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{"lstm_batchwise", "type error", {}},
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{"optional_get_element", "type error", {}},
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@ -195,6 +194,7 @@ TEST_P(ModelTest, Run) {
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{"shape_start_1_end_negative_1", "type error", {}},
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{"shape_start_negative_1", "type error", {}},
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{"simple_rnn_batchwise", "type error", {}},
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{"mod_float_mixed_sign_example", "fmod attribute must be true for floating point types", {}},
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#ifdef ENABLE_TRAINING
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{"adagrad", "not a registered function/op", {}}, // Op not registered.
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{"adagrad_multiple", "not a registered function/op", {}}, // Op not registered.
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@ -205,46 +205,46 @@ TEST_P(ModelTest, Run) {
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{"momentum", "not a registered function/op", {}}, // Op not registered.
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{"momentum_multiple", "not a registered function/op", {}}, // Op not registered.
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{"nesterov_momentum", "not a registered function/op", {}}, // Op not registered.
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index_log_prob",
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"type error",
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{"onnx170"}},
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{"softmax_cross_entropy_mean_weight_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_3d", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_4d_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_4d", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index", "type error", {"onnx170"}},
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{"opset12"}},
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{"softmax_cross_entropy_mean_weight_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_3d", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_4d_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_4d", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_log_prob",
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"type error",
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{"onnx170"}},
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{"softmax_cross_entropy_mean_3d_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_none_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_3d", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_3d_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_3d_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_none_weights_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_sum_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight_ignore_index", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_3d", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index", "type error", {"onnx170"}},
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{"softmax_cross_entropy_sum", "type error", {"onnx170"}},
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{"opset12"}},
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{"softmax_cross_entropy_mean_3d_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_none_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_3d", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index_3d_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_3d_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_none_weights_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_sum_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight_ignore_index", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_3d", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index", "type error", {"opset12"}},
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{"softmax_cross_entropy_sum", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_log_prob",
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"type error",
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{"onnx170"}},
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{"softmax_cross_entropy_none_weights", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_4d_log_prob", "type error", {"onnx170"}},
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{"softmax_cross_entropy_none", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index", "type error", {"onnx170"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_weight", "type error", {"onnx170"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_4d", "type error", {"onnx170"}},
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{"opset12"}},
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{"softmax_cross_entropy_none_weights", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_4d_log_prob", "type error", {"opset12"}},
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{"softmax_cross_entropy_none", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index", "type error", {"opset12"}},
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{"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_weight", "type error", {"opset12"}},
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{"softmax_cross_entropy_mean_no_weight_ignore_index_4d", "type error", {"opset12"}},
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#endif
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{"mask_rcnn_keras", "this model currently has an invalid contrib op version set to 10", {}}};
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@ -593,10 +593,10 @@ TEST_P(ModelTest, Run) {
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{
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BrokenTest t = {ToUTF8String(test_case_name), ""};
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auto iter = broken_tests.find(t);
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auto model_version = model_info->GetModelVersion();
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if (iter != broken_tests.end() &&
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(model_version == TestModelInfo::unknown_version || iter->broken_versions_.empty() ||
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iter->broken_versions_.find(model_version) != iter->broken_versions_.end())) {
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auto opset_version = model_info->GetNominalOpsetVersion();
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if (iter != broken_tests.end() &&
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(opset_version == TestModelInfo::unknown_version || iter->broken_opset_versions_.empty() ||
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iter->broken_opset_versions_.find(opset_version) != iter->broken_opset_versions_.end() )) {
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SkipTest();
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return;
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}
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@ -1055,9 +1055,14 @@ TEST_P(ModelTest, Run) {
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#endif
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// TENSORRT/OpenVino has too many test failures in the single node tests
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#if !defined(_WIN32) && !defined(USE_OPENVINO)
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paths.push_back("/data/onnx");
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#if !defined(USE_OPENVINO)
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#if !defined(_WIN32)
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paths.push_back(ORT_TSTR("/data/onnx"));
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#else
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paths.push_back(ORT_TSTR("c:\\local\\data\\onnx"));
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#endif
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#endif
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while (!paths.empty()) {
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std::basic_string<ORTCHAR_T> node_data_root_path = paths.back();
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paths.pop_back();
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@ -1074,7 +1079,6 @@ TEST_P(ModelTest, Run) {
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std::basic_string<PATH_CHAR_TYPE> filename_str = filename;
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if (!HasExtensionOf(filename_str, ORT_TSTR("onnx")))
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return true;
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std::basic_string<PATH_CHAR_TYPE> test_case_name = my_dir_name;
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if (test_case_name.compare(0, 5, ORT_TSTR("test_")) == 0)
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test_case_name = test_case_name.substr(5);
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@ -1125,8 +1129,8 @@ auto ExpandModelName = [](const ::testing::TestParamInfo<ModelTest::ParamType>&
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std::replace(name.begin(), name.end(), '\\', '_');
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// Note: test name only accepts '_' and alphanumeric
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// remove '.' and '-'
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char chars[] = ".-";
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// remove '.', '-', ':'
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char chars[] = ".-:";
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for (unsigned int i = 0; i < strlen(chars); ++i) {
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name.erase(std::remove(name.begin(), name.end(), chars[i]), name.end());
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}
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@ -2694,8 +2694,7 @@ def main():
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if args.test:
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if args.enable_onnx_tests:
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source_onnx_model_dir = "C:\\local\\models" if is_windows() else "/data/models"
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dest_model_dir_name = "models"
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setup_test_data(source_onnx_model_dir, dest_model_dir_name, build_dir, configs)
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setup_test_data(source_onnx_model_dir, "models", build_dir, configs)
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run_onnxruntime_tests(args, source_dir, ctest_path, build_dir, configs)
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@ -23,7 +23,7 @@ resources:
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repositories:
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- repository: onnxruntime-inference-examples # The name used to reference this repository in the checkout step
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type: github
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endpoint: ort-examples
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endpoint: ort-examples
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name: microsoft/onnxruntime-inference-examples
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- repository: manylinux
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type: Github
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@ -287,7 +287,7 @@ jobs:
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set -e -x
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cd $(Build.SourcesDirectory)
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mv manylinux onnxruntime
|
||||
ls
|
||||
ls
|
||||
|
||||
- template: templates/with-container-registry-steps.yml
|
||||
parameters:
|
||||
|
|
@ -352,7 +352,7 @@ jobs:
|
|||
script: |
|
||||
docker run --gpus all -e CC=/opt/rh/devtoolset-10/root/usr/bin/cc -e CXX=/opt/rh/devtoolset-10/root/usr/bin/c++ -e CFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all" -e CXXFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all" -e NVIDIA_VISIBLE_DEVICES=all --rm --volume $(Build.SourcesDirectory):/src_dir \
|
||||
--volume $(Build.ArtifactStagingDirectory):/artifact_src -e NIGHTLY_BUILD onnxruntimecuda116xtrt84build \
|
||||
/src_dir/onnxruntime-inference-examples/c_cxx/squeezenet/run_capi_application.sh -o /src_dir/onnxruntime -p /artifact_src/onnxruntime-linux-x64-gpu-$(OnnxRuntimeVersion).tgz -w /src_dir/onnxruntime-inference-examples/c_cxx/squeezenet
|
||||
/src_dir/onnxruntime-inference-examples/c_cxx/squeezenet/run_capi_application.sh -o /src_dir/onnxruntime -p /artifact_src/onnxruntime-linux-x64-gpu-$(OnnxRuntimeVersion).tgz -w /src_dir/onnxruntime-inference-examples/c_cxx/squeezenet
|
||||
workingDirectory: '$(Build.ArtifactStagingDirectory)'
|
||||
|
||||
- task: PublishPipelineArtifact@1
|
||||
|
|
@ -433,8 +433,8 @@ jobs:
|
|||
displayName: 'Test C API application for GPU package'
|
||||
inputs:
|
||||
filename: $(Build.SourcesDirectory)\onnxruntime-inference-examples\c_cxx\squeezenet\run_capi_application.bat
|
||||
arguments: $(Build.SourcesDirectory)\onnxruntime $(Build.ArtifactStagingDirectory)\onnxruntime-win-x64-gpu-$(OnnxRuntimeVersion).zip $(Build.SourcesDirectory)\onnxruntime-inference-examples\c_cxx\squeezenet
|
||||
workingFolder: '$(Build.ArtifactStagingDirectory)'
|
||||
arguments: $(Build.SourcesDirectory)\onnxruntime $(Build.ArtifactStagingDirectory)\onnxruntime-win-x64-gpu-$(OnnxRuntimeVersion).zip $(Build.SourcesDirectory)\onnxruntime-inference-examples\c_cxx\squeezenet
|
||||
workingFolder: '$(Build.ArtifactStagingDirectory)'
|
||||
|
||||
- task: PublishPipelineArtifact@0
|
||||
displayName: 'Publish Pipeline Combined GPU Package Artifact'
|
||||
|
|
@ -518,17 +518,17 @@ jobs:
|
|||
script: |
|
||||
dotnet workload install android ios macos
|
||||
workingDirectory: '$(Build.SourcesDirectory)\csharp'
|
||||
|
||||
|
||||
- task: PowerShell@2
|
||||
displayName: Build .NET 6 targets using dotnet
|
||||
inputs:
|
||||
targetType: 'inline'
|
||||
# we don't specify 'Any CPU' as the platform here because if we do it gets added to the output path
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\Any CPU\RelWithDebInfo\net6.0-ios\
|
||||
# which is inconsistent with the msbuild output path for the pre-.net6 targets
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\Any CPU\RelWithDebInfo\net6.0-ios\
|
||||
# which is inconsistent with the msbuild output path for the pre-.net6 targets
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\RelWithDebInfo\monoandroid11.0
|
||||
# and makes it harder to do the packing
|
||||
#
|
||||
#
|
||||
# 'Any CPU' is the default (first 'mixed' platform specified in the csproj) so this should be fine.
|
||||
script: |
|
||||
dotnet build .\src\Microsoft.ML.OnnxRuntime\Microsoft.ML.OnnxRuntime.csproj -p:SelectedTargets=Net6 -p:Configuration=RelWithDebInfo -p:OnnxRuntimeBuildDirectory="$(Build.BinariesDirectory)" -p:OrtPackageId="Microsoft.ML.OnnxRuntime.Gpu" -p:IsReleaseBuild=${{ parameters.IsReleaseBuild }}
|
||||
|
|
@ -855,4 +855,4 @@ jobs:
|
|||
artifactName: 'drop-signed-nuget-dml'
|
||||
targetPath: '$(Build.ArtifactStagingDirectory)'
|
||||
|
||||
- template: templates/publish-nuget.yml
|
||||
- template: templates/publish-nuget.yml
|
||||
|
|
|
|||
|
|
@ -22,9 +22,9 @@ jobs:
|
|||
|
||||
steps:
|
||||
- task: UsePythonVersion@0
|
||||
inputs:
|
||||
versionSpec: '3.7'
|
||||
addToPath: true
|
||||
inputs:
|
||||
versionSpec: '3.7'
|
||||
addToPath: true
|
||||
architecture: x64
|
||||
|
||||
- task: NuGetToolInstaller@0
|
||||
|
|
@ -45,7 +45,7 @@ jobs:
|
|||
filename: 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvarsall.bat'
|
||||
arguments: 'amd64'
|
||||
modifyEnvironment: true
|
||||
|
||||
|
||||
- task: DownloadPipelineArtifact@0
|
||||
displayName: 'Download Pipeline Artifact'
|
||||
inputs:
|
||||
|
|
|
|||
|
|
@ -71,9 +71,9 @@ jobs:
|
|||
versionSpec: '16.x'
|
||||
|
||||
- task: UsePythonVersion@0
|
||||
inputs:
|
||||
versionSpec: '3.7'
|
||||
addToPath: true
|
||||
inputs:
|
||||
versionSpec: '3.7'
|
||||
addToPath: true
|
||||
architecture: ${{ parameters.BuildArch }}
|
||||
|
||||
- task: BatchScript@1
|
||||
|
|
@ -94,10 +94,10 @@ jobs:
|
|||
$Env:CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=OFF -DProtobuf_USE_STATIC_LIBS=ON -DONNX_USE_LITE_PROTO=ON -DCMAKE_TOOLCHAIN_FILE=C:/vcpkg/scripts/buildsystems/vcpkg.cmake -DVCPKG_TARGET_TRIPLET=${{ parameters.BuildArch }}-windows-static"
|
||||
python setup.py bdist_wheel
|
||||
python -m pip uninstall -y onnx -qq
|
||||
Get-ChildItem -Path dist/*.whl | foreach {pip --disable-pip-version-check install --upgrade $_.fullname}
|
||||
Get-ChildItem -Path dist/*.whl | foreach {pip --disable-pip-version-check install --upgrade $_.fullname}
|
||||
workingDirectory: '$(Build.SourcesDirectory)\cmake\external\onnx'
|
||||
displayName: 'Install ONNX'
|
||||
|
||||
|
||||
- task: PythonScript@0
|
||||
displayName: 'Generate cmake config'
|
||||
inputs:
|
||||
|
|
@ -160,7 +160,7 @@ jobs:
|
|||
workingDirectory: '$(Build.BinariesDirectory)'
|
||||
displayName: 'Create models link'
|
||||
|
||||
- ${{ if in(parameters['sln_platform'], 'Win32', 'x64') }}:
|
||||
- ${{ if in(parameters['sln_platform'], 'Win32', 'x64') }}:
|
||||
- ${{ if eq(parameters.BuildCSharp, true) }}:
|
||||
- task: DotNetCoreCLI@2
|
||||
displayName: 'Test C#'
|
||||
|
|
|
|||
|
|
@ -40,7 +40,7 @@ parameters:
|
|||
|
||||
jobs:
|
||||
- template: c-api-linux-cpu.yml
|
||||
parameters:
|
||||
parameters:
|
||||
AdditionalBuildFlags: ${{ parameters.AdditionalBuildFlags }}
|
||||
BaseImage: 'centos:7'
|
||||
OnnxruntimeArch: 'x64'
|
||||
|
|
@ -50,7 +50,7 @@ jobs:
|
|||
PoolName: 'Linux-CPU'
|
||||
|
||||
- template: c-api-linux-cpu.yml
|
||||
parameters:
|
||||
parameters:
|
||||
AdditionalBuildFlags: ${{ parameters.AdditionalBuildFlags }}
|
||||
BaseImage: 'arm64v8/centos:7'
|
||||
OnnxruntimeArch: 'aarch64'
|
||||
|
|
@ -431,17 +431,17 @@ jobs:
|
|||
script: |
|
||||
dotnet workload install android ios macos
|
||||
workingDirectory: '$(Build.SourcesDirectory)\csharp'
|
||||
|
||||
- task: PowerShell@2
|
||||
|
||||
- task: PowerShell@2
|
||||
displayName: Build Microsoft.ML.OnnxRuntime .NET 6 targets using dotnet
|
||||
inputs:
|
||||
targetType: 'inline'
|
||||
# we don't specify 'Any CPU' as the platform here because if we do it gets added to the output path
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\Any CPU\RelWithDebInfo\net6.0-ios\
|
||||
# which is inconsistent with the msbuild output path for the pre-.net6 targets
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\Any CPU\RelWithDebInfo\net6.0-ios\
|
||||
# which is inconsistent with the msbuild output path for the pre-.net6 targets
|
||||
# e.g. csharp\src\Microsoft.ML.OnnxRuntime\bin\RelWithDebInfo\monoandroid11.0
|
||||
# and makes it harder to do the packing
|
||||
#
|
||||
#
|
||||
# 'Any CPU' is the default (first 'mixed' platform specified in the csproj) so this should be fine.
|
||||
script: |
|
||||
dotnet build .\src\Microsoft.ML.OnnxRuntime\Microsoft.ML.OnnxRuntime.csproj -p:SelectedTargets=Net6 -p:Configuration=RelWithDebInfo -p:OnnxRuntimeBuildDirectory="$(Build.BinariesDirectory)" -p:OrtPackageId=$(OrtPackageId) -p:IsReleaseBuild=${{ parameters.IsReleaseBuild }}
|
||||
|
|
@ -583,7 +583,7 @@ jobs:
|
|||
git checkout -- js/**
|
||||
git checkout -- .gitattributes
|
||||
workingDirectory: '$(Build.SourcesDirectory)'
|
||||
displayName: 'Testing: force EOL to lf on windows for /js/**'
|
||||
displayName: 'Testing: force EOL to lf on windows for /js/**'
|
||||
|
||||
- task: DownloadPipelineArtifact@0
|
||||
displayName: 'Download Pipeline Artifact - NuGet (Win x64)'
|
||||
|
|
|
|||
Loading…
Reference in a new issue