diff --git a/onnxruntime/test/providers/cpu/model_tests.cc b/onnxruntime/test/providers/cpu/model_tests.cc index 449bb77cf1a9b..21f860387f59b 100644 --- a/onnxruntime/test/providers/cpu/model_tests.cc +++ b/onnxruntime/test/providers/cpu/model_tests.cc @@ -125,13 +125,11 @@ TEST_P(ModelTest, Run) { return; } -#ifndef ENABLE_TRAINING if (model_info->HasDomain(ONNX_NAMESPACE::AI_ONNX_TRAINING_DOMAIN) || model_info->HasDomain(ONNX_NAMESPACE::AI_ONNX_PREVIEW_TRAINING_DOMAIN)) { - SkipTest("It has training domain"); + SkipTest("it has the training domain. No pipeline should need to run these tests."); return; } -#endif std::set broken_tests = { {"slice_neg_steps", "Type parameter (Tind) bound to different types (tensor(int64) and tensor(int32) in node ()."}, @@ -254,38 +252,9 @@ TEST_P(ModelTest, Run) { {"softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight", "type error", {"opset12"}}, {"softmax_cross_entropy_mean_weight", "type error", {"opset12"}}, {"softmax_cross_entropy_mean_no_weight_ignore_index_4d", "type error", {"opset12"}}, - // models from model zoo - {"BERT-Squad-int8", "failed in training", {"opset12"}}, - {"DenseNet-121-12-int8", "failed in training", {"opset12"}}, - {"EfficientNet-Lite4-int8", "failed in training", {"opset11"}}, - {"EfficientNet-Lite4-qdq", "failed in training", {"opset11"}}, - {"Faster R-CNN R-50-FPN-int8", "failed in training", {"opset12"}}, - {"Inception-1-int8", "failed in training", {"opset12"}}, - {"MobileNet v2-1.0-int8", "failed in traning", {"opset12"}}, - {"MobileNet v2-1.0-qdq", "failed in training", {"opset12"}}, - {"ResNet50-qdq", "failed in training", {"opset12"}}, - {"ResNet50_int8", "failed in training", {"opset12"}}, - {"ResNet50-int8", "failed in training", {"opset12"}}, - {"ShuffleNet-v2-int8", "failed in training", {"opset12"}}, - {"SSD-int8", "failed in training", {"opset12"}}, - {"VGG 16-int8", "failed in training", {"opset12"}}, - {"YOLOv3-12-int8", "failed in training", {"opset12"}}, #endif {"mask_rcnn_keras", "this model currently has an invalid contrib op version set to 10", {}}}; -#ifdef ENABLE_TRAINING_CORE - // They only failed in orttraining-iinux-gpu-ci-pipelie with TRT8.5 - if (provider_name == "cpu") { - broken_tests.insert({"ShuffleNet-v2-qdq", "failed in orttraining-linux-gpu, TRT8.5 with V100, but it's a cpu test?", {"opset12"}}); - } - if (provider_name == "cuda") { - broken_tests.insert({"GoogleNet-qdq", "failed in orttraining-linux-gpu, TRT8.5 with V100.", {"opset12"}}); - broken_tests.insert({"ShuffleNet-v2-qdq", "failed in orttraining-linux-gpu, TRT8.5 with V100.", {"opset12"}}); - broken_tests.insert({"Inception-1-qdq", "failed in orttraining-linux-gpu, TRT8.5 with V100.", {"opset12"}}); - broken_tests.insert({"SqueezeNet 1.0-qdq", "failed in orttraining-linux-gpu, TRT8.5 with V100.", {"opset13"}}); - } -#endif - // Some EPs may fail to pass some specific testcases. // For example TenosrRT EP may fail on FLOAT16 related testcases if GPU doesn't support float16. // Instead of list all these testcases, we can use following keyword set to filter out testcases wchich contain