Fixes for Sdxl MLPerf inference

.github/workflows/test-nvidia-mlperf-implementation.yml

@@ -2,7 +2,7 @@ name: MLPerf Inference Nvidia implementations
 
 on:
   schedule:
-    - cron: "31 2 * * *" #to be adjusted
+    - cron: "29 20 * * *" #to be adjusted
 
 jobs:
   build_nvidia:
@@ -21,5 +21,5 @@ jobs:
           source gh_action/bin/activate
           export CM_REPOS=$HOME/GH_CM
           pip install --upgrade cm4mlops
-          cm run script --tags=run-mlperf,inference,_all-scenarios,_submission,_full,_r4.1-dev --execution_mode=valid --gpu_name=rtx_4090 --model=${{ matrix.model }} --submitter="MLCommons" --hw_name=RTX4090x2  --implementation=nvidia    --backend=tensorrt    --category=datacenter,edge --division=closed  --docker_dt=yes --docker_it=no --docker_cm_repo=gateoverflow@cm4mlops --adr.compiler.tags=gcc --device=cuda --use_dataset_from_host=yes --results_dir=$HOME/gh_action_results --submission_dir=$HOME/gh_action_submissions --clean  --docker --quiet
+          cm run script --tags=run-mlperf,inference,_all-scenarios,_submission,_full,_r4.1-dev --preprocess_submission=yes --execution_mode=valid --gpu_name=rtx_4090 --pull_changes=yes --model=${{ matrix.model }} --submitter="MLCommons" --hw_name=RTX4090x2  --implementation=nvidia    --backend=tensorrt    --category=datacenter,edge --division=closed  --docker_dt=yes --docker_it=no --docker_cm_repo=gateoverflow@cm4mlops --adr.compiler.tags=gcc --device=cuda --use_dataset_from_host=yes --results_dir=$HOME/gh_action_results --submission_dir=$HOME/gh_action_submissions --clean  --docker --quiet
           cm run script --tags=push,github,mlperf,inference,submission --repo_url=https://github.com/gateoverflow/mlperf_inference_unofficial_submissions_v5.0 --repo_branch=main --commit_message="Results from GH action on NVIDIA_RTX4090x2" --quiet --submission_dir=$HOME/gh_action_submissions --hw_name=RTX4090x2

.github/workflows/test-scc24-sdxl.yaml

@@ -2,7 +2,7 @@ name: MLPerf inference SDXL (SCC)
 
 on:
   schedule:
-    - cron: "5 2 * * *"
+    - cron: "20 14 * * *"
 
 jobs:
   build_reference:

script/app-mlperf-inference-mlcommons-python/customize.py

@@ -290,6 +290,10 @@ def get_run_cmd_reference(os_info, env, scenario_extra_options, mode_extra_optio
 
     elif "stable-diffusion-xl" in env['CM_MODEL']:
         env['RUN_DIR'] = os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "text_to_image")
+        if env.get('+PYTHONPATH', '') == '':
+            env['+PYTHONPATH'] = []
+        env['+PYTHONPATH'].append(os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools", "fid"))
+
         backend = env['CM_MLPERF_BACKEND']
         device = env['CM_MLPERF_DEVICE'] if env['CM_MLPERF_DEVICE'] not in [ "gpu", "rocm" ] else "cuda"
         max_batchsize = env.get('CM_MLPERF_LOADGEN_MAX_BATCHSIZE', '1')

script/process-mlperf-accuracy/customize.py

@@ -92,7 +92,7 @@ def preprocess(i):
 
 
         elif dataset == "coco2014":
-            env['+PYTHONPATH'] = [ os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools") ]
+            env['+PYTHONPATH'] = [ os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools") , os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools", "fid") ]
             extra_options = ""
 
             if env.get('CM_SDXL_STATISTICS_FILE_PATH', '') != '':

script/run-mlperf-inference-app/customize.py

@@ -203,6 +203,7 @@ def preprocess(i):
         inp = {}
         if str(docker_dt).lower() in ["yes", "true", "1"]:
             env['CM_DOCKER_REUSE_EXISTING_CONTAINER'] = 'no' # turning it off for the first run and after that we turn it on
+            env['CM_DOCKER_DETACHED_MODE'] = 'yes'
 
         if env.get('CM_DOCKER_IMAGE_NAME', '') != '':
             docker_extra_input['docker_image_name'] = env['CM_DOCKER_IMAGE_NAME']

tests/script/test_docker.py

@@ -12,7 +12,8 @@
                'image_name':'cm-script-app-image-classification-onnx-py',
                'env': {
                  'CM_DOCKER_RUN_SCRIPT_TAGS': 'app,image-classification,onnx,python',
-                 'CM_MLOPS_REPO': 'ctuning@mlcommons-ck', 
+                 'CM_MLOPS_REPO': 'mlcommons@cm4mlops',
+                 'CM_MLOPS_REPO_BRANCH': 'mlperf-inference',
                  'CM_DOCKER_IMAGE_BASE': 'ubuntu:22.04'
                }, 
                'quiet': 'yes'