Merge branch 'master' into zixuan/sdxl

.azure-pipelines/model-test-3x.yml

@@ -112,7 +112,7 @@ stages:
             displayName: "Publish report"
           - script: |
               if [ $(is_perf_reg) == 'true' ]; then
-                echo "[Performance Regression] Some model performance regression occurred, please check artifacts and reports."
+                echo "Some benchmark regression occurred or the reference data need to be updated, please check artifacts and reports."
                 exit 1
               fi
-            displayName: "Specify performance regression"
+            displayName: "Specify regression"

.azure-pipelines/model-test.yml

@@ -40,33 +40,20 @@ parameters:
     displayName: Run ONNX models?
     type: boolean
     default: true
-  - name: MXNet_Model
-    displayName: Run MXNet models?
-    type: boolean
-    default: false
 
   - name: TensorFlowModelList
     type: object
     default:
       - resnet50v1.5
       - ssd_resnet50_v1
-#      - ssd_mobilenet_v1_ckpt
-#      - inception_v1
-#      - darknet19
-#      - resnet-101
   - name: PyTorchModelList
     type: object
     default:
-#      - resnet18
       - resnet18_fx
   - name: ONNXModelList
     type: object
     default:
       - resnet50-v1-12
-  - name: MXNetModelList
-    type: object
-    default:
-      - resnet50v1
 
 stages:
   - stage: TensorFlowModels
@@ -114,21 +101,6 @@ stages:
                   modelName: ${{ model }}
                   framework: "onnxrt"
 
-  - stage: MXNetModels
-    displayName: Run MXNet Model
-    pool: MODEL_PERF_TEST
-    dependsOn: []
-    condition: and(succeeded(), eq('${{ parameters.MXNet_Model }}', 'true'))
-    jobs:
-      - ${{ each model in parameters.MXNetModelList }}:
-          - job:
-            displayName: ${{ model }}
-            steps:
-              - template: template/model-template.yml
-                parameters:
-                  modelName: ${{ model }}
-                  framework: "mxnet"
-
   - stage: GenerateLogs
     displayName: Generate Report
     pool:
@@ -191,7 +163,7 @@ stages:
             displayName: "Publish report"
           - script: |
               if [ $(is_perf_reg) == 'true' ]; then
-                echo "[Performance Regression] Some model performance regression occurred, please check artifacts and reports."
+                echo "Some benchmark regression occurred or the reference data need to be updated, please check artifacts and reports."
                 exit 1
               fi
-            displayName: "Specify performance regression"
+            displayName: "Specify regression"

.azure-pipelines/scripts/models/generate_report.sh

@@ -245,13 +245,9 @@ function generate_html_core {
               if((new_result == nan && previous_result == nan) || new_result == "unknown"){
                     printf("<td class=\"col-cell col-cell3\" colspan=2></td>");
               } else{
-                  if(new_result == nan) {
-                        job_status = "fail"
-                        status_png = "background-color:#FFD2D2";
-                        printf("<td style=\"%s\" colspan=2></td>", status_png);
-                  } else{
-                        printf("<td class=\"col-cell col-cell3\" colspan=2></td>");
-                  }
+                    job_status = "fail"
+                    status_png = "background-color:#FFD2D2";
+                    printf("<td style=\"%s\" colspan=2></td>", status_png);
               }
             }
         }

.azure-pipelines/scripts/models/run_pytorch_models_trigger.sh

@@ -72,6 +72,7 @@ FRAMEWORK="pytorch"
 source /neural-compressor/.azure-pipelines/scripts/fwk_version.sh 'latest'
 if [[ "${inc_new_api}" == "3x"* ]]; then
     FRAMEWORK_VERSION="latest"
+    export LD_LIBRARY_PATH=/usr/local/lib/:$LD_LIBRARY_PATH
 else
     FRAMEWORK_VERSION=${pytorch_version}
     TORCH_VISION_VERSION=${torchvision_version}

.azure-pipelines/scripts/ut/3x/run_3x_pt.sh

@@ -5,6 +5,7 @@ echo "${test_case}"
 
 # install requirements
 echo "set up UT env..."
+export LD_LIBRARY_PATH=/usr/local/lib/:$LD_LIBRARY_PATH
 pip install -r /neural-compressor/test/3x/torch/requirements.txt
 pip install pytest-cov
 pip install pytest-html

.azure-pipelines/scripts/ut/run_itrex.sh

@@ -6,6 +6,7 @@ echo "run itrex ut..."
 
 # install inc 3x deps
 pip install -r /neural-compressor/requirements_pt.txt
+export LD_LIBRARY_PATH=/usr/local/lib/:$LD_LIBRARY_PATH
 
 # prepare itrex
 git clone https://github.com/intel/intel-extension-for-transformers.git /intel-extension-for-transformers

.azure-pipelines/ut-itrex.yml

@@ -13,10 +13,6 @@ pr:
       - requirements.txt
       - .azure-pipelines/scripts/ut/run_itrex.sh
       - .azure-pipelines/ut-itrex.yml
-    exclude:
-      - neural_compressor/common
-      - neural_compressor/torch
-      - neural_compressor/tensorflow
 
 pool: MODEL_PERF_TEST
 

docs/source/faq.md

@@ -17,3 +17,12 @@ ImportError: libGL.so.1: cannot open shared object file: No such file or directo
 #### Issue 4:  
 Conda package *neural-compressor-full* (this binary is only available from v1.13 to v2.1.1) dependency conflict may pending on conda installation for a long time.   
 **Solution:** run *conda install sqlalchemy=1.4.27 alembic=1.7.7 -c conda-forge* before install *neural-compressor-full*. 
+#### Issue 5: 
+If you run 3X torch extension API inside a docker container, then you may encounter the following error:  
+```shell
+ValueError: No threading layer could be loaded.
+HINT:
+Intel TBB is required, try:
+$ conda/pip install tbb
+```
+**Solution:** It's actually already installed by `requirements_pt.txt`, so just need to set up with `export LD_LIBRARY_PATH=/usr/local/lib/:$LD_LIBRARY_PATH`.