Support MLPer inference rgat reference implementation

script/app-mlperf-inference-mlcommons-python/_cm.yaml

@@ -482,13 +482,12 @@ deps:
   ## RGAT
   - tags: get,ml-model,rgat
     names:
-    - ml-model
     - rgat-model
     enable_if_env:
       CM_MODEL:
       - rgat
     skip_if_env:
-      RGAT_CHECKPOINT_PATH:
+      CM_ML_MODEL_RGAT_CHECKPOINT_PATH:
         - 'on'
 
   ########################################################################
@@ -620,6 +619,9 @@ deps:
     enable_if_env:
       CM_MODEL:
       - rgat
+    skip_if_env:
+      CM_DATASET_IGBH_PATH:
+      - "on"
 
   ########################################################################
   # Install MLPerf inference dependencies
@@ -1224,27 +1226,45 @@ variations:
     group: models
     env:
       CM_MODEL: rgat
+    adr:
+      pytorch:
+        version: 2.1.0
     deps:
       - tags: get,generic-python-lib,_package.colorama
       - tags: get,generic-python-lib,_package.tqdm
       - tags: get,generic-python-lib,_package.requests
       - tags: get,generic-python-lib,_package.torchdata
-      - tags: get,generic-python-lib,_package.torch-geometric
-      - tags: get,generic-python-lib,_package.torch-scatter
-      - tags: get,generic-python-lib,_package.torch-sparse
+        version: 0.7.0
+      - tags: get,generic-python-lib,_package.torchvision
+        version: 0.16.0
       - tags: get,generic-python-lib,_package.pybind11
       - tags: get,generic-python-lib,_package.PyYAML
+      - tags: get,generic-python-lib,_package.numpy
+        version: 1.26.4
       - tags: get,generic-python-lib,_package.pydantic 
       - tags: get,generic-python-lib,_package.igb,_url.git+https://github.com/IllinoisGraphBenchmark/IGB-Datasets.git
-      - tags: get,generic-python-lib,_package.dgl,_find_links_url.https://data.dgl.ai/wheels/torch-2.1/repo.html
-        enable_if_env:
-          CM_MLPERF_DEVICE:
-          - cpu
+
+  rgat,cuda:
+    deps:
       - tags: get,generic-python-lib,_package.dgl,_find_links_url.https://data.dgl.ai/wheels/torch-2.1/cu121/repo.html
-        enable_if_env:
-          CM_MLPERF_DEVICE:
-          - gpu
-
+      - tags: get,generic-python-lib,_package.torch-scatter
+      - tags: get,generic-python-lib,_package.torch-sparse
+      - tags: get,generic-python-lib,_package.torch-geometric
+        env:
+          CM_GENERIC_PYTHON_PIP_EXTRA_FIND_LINKS_URL: "https://data.pyg.org/whl/torch-<<<CM_TORCH_VERSION>>>.html"
+
+  rgat,cpu:
+    deps:
+      - tags: get,generic-python-lib,_package.torch-geometric
+        env:
+          CM_GENERIC_PYTHON_PIP_EXTRA_FIND_LINKS_URL: "https://data.pyg.org/whl/torch-<<<CM_TORCH_VERSION>>>+cpu.html"
+      - tags: get,generic-python-lib,_package.torch-scatter
+        env:
+          CM_GENERIC_PYTHON_PIP_EXTRA_FIND_LINKS_URL: "https://data.pyg.org/whl/torch-<<<CM_TORCH_VERSION>>>+cpu.html"
+      - tags: get,generic-python-lib,_package.torch-sparse
+        env:
+          CM_GENERIC_PYTHON_PIP_EXTRA_FIND_LINKS_URL: "https://data.pyg.org/whl/torch-<<<CM_TORCH_VERSION>>>+cpu.html"
+      - tags: get,generic-python-lib,_package.dgl,_find_links_url.https://data.dgl.ai/wheels/torch-2.1/repo.html
 
   # Target devices
   cpu:

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

@@ -115,10 +115,12 @@ def preprocess(i):
     scenario_extra_options = ''
 
     NUM_THREADS = env['CM_NUM_THREADS']
-    if int(NUM_THREADS) > 2 and env['CM_MLPERF_DEVICE'] == "gpu":
+    if int(
+            NUM_THREADS) > 2 and env['CM_MLPERF_DEVICE'] == "gpu" and env['CM_MODEL'] != "rgat":
         NUM_THREADS = "2"  # Don't use more than 2 threads when run on GPU
 
-    if env['CM_MODEL'] in ['resnet50', 'retinanet', 'stable-diffusion-xl']:
+    if env['CM_MODEL'] in ['resnet50', 'retinanet',
+                           'stable-diffusion-xl', 'rgat']:
         scenario_extra_options += " --threads " + NUM_THREADS
 
     ml_model_name = env['CM_MODEL']
@@ -485,15 +487,16 @@ def get_run_cmd_reference(
         # have to add the condition for running in debug mode or real run mode
         cmd = env['CM_PYTHON_BIN_WITH_PATH'] + " main.py " \
             " --scenario " + env['CM_MLPERF_LOADGEN_SCENARIO'] + \
-            " --dataset-path " + env['CM_IGBH_DATASET_PATH'] + \
-            " --device " + device.replace("cuda", "cuda:0") + \
+            " --dataset-path " + env['CM_DATASET_IGBH_PATH'] + \
+            " --device " + device.replace("cuda", "gpu") + \
             env['CM_MLPERF_LOADGEN_EXTRA_OPTIONS'] + \
             scenario_extra_options + mode_extra_options + \
             " --output " + env['CM_MLPERF_OUTPUT_DIR'] + \
             ' --dtype ' + dtype_rgat + \
-            " --model-path " + env['RGAT_CHECKPOINT_PATH'] + \
-            " --mlperf_conf " + \
-            os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "mlperf.conf")
+            " --model-path " + env['CM_ML_MODEL_RGAT_CHECKPOINT_PATH']
+
+        if env.get('CM_ACTIVATE_RGAT_IN_MEMORY', '') == "yes":
+            cmd += " --in-memory "
 
     if env.get('CM_NETWORK_LOADGEN', '') in ["lon", "sut"]:
         cmd = cmd + " " + "--network " + env['CM_NETWORK_LOADGEN']

script/app-mlperf-inference/_cm.yaml

@@ -767,6 +767,20 @@ variations:
     env:
       CM_MODEL:
         rgat
+    posthook_deps:
+    - enable_if_env:
+        CM_MLPERF_LOADGEN_MODE:
+        - accuracy
+        - all
+        CM_MLPERF_ACCURACY_RESULTS_DIR:
+        - 'on'
+      skip_if_env:
+        CM_MLPERF_IMPLEMENTATION:
+        - nvidia
+      names:
+      - mlperf-accuracy-script
+      - 3d-unet-accuracy-script
+      tags: run,accuracy,mlperf,_igbh
 
   sdxl:
     group:
@@ -1645,6 +1659,25 @@ variations:
       CM_ENV_NVMITTEN_DOCKER_WHEEL_PATH: '/opt/nvmitten-0.1.3b0-cp38-cp38-linux_x86_64.whl'
       CM_MLPERF_INFERENCE_VERSION: '4.1'
 
+  r5.0-dev_default:
+    group:
+      reproducibility
+    add_deps_recursive:
+      nvidia-inference-common-code:
+        version: r4.1
+        tags: _mlcommons
+      nvidia-inference-server:
+        version: r4.1
+        tags: _mlcommons
+      intel-harness:
+        tags: _v4.1
+    default_env:
+      CM_SKIP_SYS_UTILS: 'yes'
+      CM_REGENERATE_MEASURE_FILES: 'yes'
+    env:
+      CM_ENV_NVMITTEN_DOCKER_WHEEL_PATH: '/opt/nvmitten-0.1.3b0-cp38-cp38-linux_x86_64.whl'
+
+
 invalid_variation_combinations:
   -
     - retinanet
@@ -1768,6 +1801,8 @@ docker:
    - "${{ CM_NVIDIA_LLAMA_DATASET_FILE_PATH }}:${{ CM_NVIDIA_LLAMA_DATASET_FILE_PATH }}"
    - "${{ SDXL_CHECKPOINT_PATH }}:${{ SDXL_CHECKPOINT_PATH }}"
    - "${{ CM_DATASET_KITS19_PREPROCESSED_PATH }}:${{ CM_DATASET_KITS19_PREPROCESSED_PATH }}"
+   - "${{ CM_DATASET_IGBH_PATH }}:${{ CM_DATASET_IGBH_PATH }}"
+   - "${{ CM_ML_MODEL_RGAT_CHECKPOINT_PATH }}:${{ CM_ML_MODEL_RGAT_CHECKPOINT_PATH }}"
   skip_run_cmd: 'no'
   shm_size: '32gb'
   interactive: True

script/get-cudnn/_cm.yaml

@@ -19,6 +19,7 @@ default_env:
 
 deps:
 - tags: detect,os
+- tags: detect,sudo
 - names:
   - cuda
   skip_if_env:

script/get-dataset-mlperf-inference-igbh/_cm.yaml

@@ -11,7 +11,8 @@ tags:
 - inference
 uid: 824e61316c074253
 new_env_keys:
-  - CM_IGBH_DATASET_PATH
+  - CM_DATASET_IGBH_PATH
+  - CM_DATASET_IGBH_SIZE
 input_mapping:
   out_path: CM_IGBH_DATASET_OUT_PATH
 deps:
@@ -21,6 +22,9 @@ deps:
   - tags: get,python
     names:
       - get-python
+  - tags: get,generic-python-lib,_package.igb,_url.git+https://github.com/anandhu-eng/IGB-Datasets.git
+  - tags: get,generic-python-lib,_package.colorama
+  - tags: get,generic-python-lib,_package.tqdm
 prehook_deps:
   #paper  
   - env:
@@ -359,13 +363,13 @@ variations:
     default: true
     group: dataset-type
     env:
-      CM_IGBH_DATASET_TYPE: debug
-      CM_IGBH_DATASET_SIZE: tiny
+      CM_DATASET_IGBH_TYPE: debug
+      CM_DATASET_IGBH_SIZE: tiny
   full:
     group: dataset-type
     env:
-      CM_IGBH_DATASET_TYPE: full
-      CM_IGBH_DATASET_SIZE: full
+      CM_DATASET_IGBH_TYPE: debug
+      CM_DATASET_IGBH_SIZE: tiny
   glt:
     env:
       CM_IGBH_GRAPH_COMPRESS: yes

script/get-dataset-mlperf-inference-igbh/customize.py

@@ -27,18 +27,18 @@ def preprocess(i):
     x_sep = " && "
 
     # download the model
-    if env['CM_IGBH_DATASET_TYPE'] == "debug":
+    if env['CM_DATASET_IGBH_TYPE'] == "debug":
         run_cmd += x_sep + env['CM_PYTHON_BIN_WITH_PATH'] + \
             f" tools/download_igbh_test.py --target-path {download_loc} "
 
     # split seeds
     run_cmd += x_sep + \
-        f"{env['CM_PYTHON_BIN_WITH_PATH']} tools/split_seeds.py --path {download_loc} --dataset_size {env['CM_IGBH_DATASET_SIZE']}"
+        f"{env['CM_PYTHON_BIN_WITH_PATH']} tools/split_seeds.py --path {download_loc} --dataset_size {env['CM_DATASET_IGBH_SIZE']}"
 
     # compress graph(for glt implementation)
     if env.get('CM_IGBH_GRAPH_COMPRESS', '') == "yes":
         run_cmd += x_sep + \
-            f"{env['CM_PYTHON_BIN_WITH_PATH']} tools/compress_graph.py --path {download_loc} --dataset_size {env['CM_IGBH_DATASET_SIZE']} --layout {env['CM_IGBH_GRAPH_COMPRESS_LAYOUT']}"
+            f"{env['CM_PYTHON_BIN_WITH_PATH']} tools/compress_graph.py --path {download_loc} --dataset_size {env['CM_DATASET_IGBH_SIZE']} --layout {env['CM_IGBH_GRAPH_COMPRESS_LAYOUT']}"
 
     env['CM_RUN_CMD'] = run_cmd
 
@@ -49,10 +49,10 @@ def postprocess(i):
 
     env = i['env']
 
-    env['CM_IGBH_DATASET_PATH'] = env.get(
+    env['CM_DATASET_IGBH_PATH'] = env.get(
         'CM_IGBH_DATASET_OUT_PATH', os.getcwd())
 
     print(
-        f"Path to the IGBH dataset: {os.path.join(env['CM_IGBH_DATASET_PATH'], env['CM_IGBH_DATASET_SIZE'])}")
+        f"Path to the IGBH dataset: {os.path.join(env['CM_DATASET_IGBH_PATH'], env['CM_DATASET_IGBH_SIZE'])}")
 
     return {'return': 0}

script/get-ml-model-rgat/_cm.yaml

@@ -12,7 +12,7 @@ input_mapping:
   to: CM_DOWNLOAD_PATH
 new_env_keys:
 - CM_ML_MODEL_*
-- RGAT_CHECKPOINT_PATH
+- CM_ML_MODEL_RGAT_CHECKPOINT_PATH
 prehook_deps:
 - enable_if_env:
     CM_DOWNLOAD_TOOL:

script/get-ml-model-rgat/customize.py

@@ -19,12 +19,12 @@ def postprocess(i):
 
     env = i['env']
 
-    if env.get('RGAT_CHECKPOINT_PATH', '') == '':
-        env['RGAT_CHECKPOINT_PATH'] = os.path.join(
+    if env.get('CM_ML_MODEL_RGAT_CHECKPOINT_PATH', '') == '':
+        env['CM_ML_MODEL_RGAT_CHECKPOINT_PATH'] = os.path.join(
             env['CM_ML_MODEL_PATH'], "RGAT.pt")
     elif env.get('CM_ML_MODEL_PATH', '') == '':
-        env['CM_ML_MODEL_PATH'] = env['RGAT_CHECKPOINT_PATH']
+        env['CM_ML_MODEL_PATH'] = env['CM_ML_MODEL_RGAT_CHECKPOINT_PATH']
 
-    env['CM_GET_DEPENDENT_CACHED_PATH'] = env['RGAT_CHECKPOINT_PATH']
+    env['CM_GET_DEPENDENT_CACHED_PATH'] = env['CM_ML_MODEL_RGAT_CHECKPOINT_PATH']
 
     return {'return': 0}

script/get-mlperf-inference-src/_cm.yaml

@@ -166,6 +166,12 @@ versions:
     env:
       CM_MLPERF_LAST_RELEASE: v3.1
       CM_TMP_GIT_CHECKOUT: ''
+  r4.0:
+    env:
+      CM_MLPERF_LAST_RELEASE: v4.0
+  r4.1:
+    env:
+      CM_MLPERF_LAST_RELEASE: v4.1
   tvm:
     env:
       CM_MLPERF_LAST_RELEASE: v3.1

script/get-mlperf-inference-src/customize.py

@@ -54,7 +54,7 @@ def preprocess(i):
             env["CM_GIT_URL"] = "https://github.com/mlcommons/inference"
 
     if env.get("CM_MLPERF_LAST_RELEASE", '') == '':
-        env["CM_MLPERF_LAST_RELEASE"] = "v4.1"
+        env["CM_MLPERF_LAST_RELEASE"] = "v5.0"
 
     if 'CM_GIT_DEPTH' not in env:
         env['CM_GIT_DEPTH'] = ''

script/process-mlperf-accuracy/_cm.yaml

@@ -261,3 +261,7 @@ variations:
     env:
       CM_DATASET: terabyte
     group: dataset
+  igbh:
+    env:
+      CM_DATASET: igbh
+    group: dataset

script/process-mlperf-accuracy/customize.py

@@ -171,6 +171,16 @@ def preprocess(i):
                 " --dtype " + env.get('CM_ACCURACY_DTYPE',
                                       "float32") + " > '" + out_file + "'"
 
+        elif dataset == "igbh":
+            if env.get('CM_DATASET_IGBH_SIZE', '') == '':
+                if env.get('CM_MLPERF_SUBMISSION_GENERATION_STYLE',
+                           '') == "full":
+                    env['CM_DATASET_IGBH_SIZE'] = "full"
+                else:
+                    env['CM_DATASET_IGBH_SIZE'] = "tiny"
+            CMD = env['CM_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['CM_MLPERF_INFERENCE_SOURCE'], "graph", "R-GAT", "tools", "accuracy_igbh.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --dataset-path '" + env['CM_DATASET_IGBH_PATH'] + "' --dataset-size '" + env['CM_DATASET_IGBH_SIZE'] + "' > '" + out_file + "'"
+
         else:
             return {'return': 1, 'error': 'Unsupported dataset'}
 

script/run-mlperf-inference-app/_cm.yaml

@@ -360,6 +360,19 @@ variations:
       mlperf-inference-nvidia-scratch-space:
         tags: _version.r4_1
     group: benchmark-version
+
+  r5.0-dev:
+    env:
+      CM_MLPERF_INFERENCE_VERSION: '5.0-dev'
+      CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS: r5.0-dev_default
+    group: benchmark-version
+    adr:
+      get-mlperf-inference-results-dir:
+        tags: _version.r5.0-dev
+      get-mlperf-inference-submission-dir:
+        tags: _version.r5.0-dev
+      mlperf-inference-nvidia-scratch-space:
+        tags: _version.r5.0-dev
 
   short:
     add_deps_recursive:

script/test-cm-core/src/tutorials/test_tutorial_retinanet.py

@@ -30,7 +30,7 @@
                'name': 'mlperf'})
 checks.check_return(r)
 
-r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short,_dashboard', 'adr':
+r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short', 'adr':
                {'python': {'name': 'mlperf', 'version_min': '3.8'}, 'compiler': {'tags': "gcc"}, 'openimages-preprocessed': {'tags': '_50'}}, 'submitter': 'Community',
                'implementation': 'cpp', 'hw_name': 'default', 'model': 'retinanet', 'backend': 'onnxruntime', 'device': 'cpu', 'scenario': 'Offline',
                'test_query_count': '10', 'clean': 'true', 'quiet': 'yes'})

script/test-cm-core/src/tutorials/test_tutorial_tvm_pip_ge.py

@@ -18,7 +18,7 @@
                'device': 'cpu', 'scenario': 'Offline', 'mode': 'accuracy', 'test_query_count': '5', 'clean': 'true', 'quiet': 'yes'})
 checks.check_return(r)
 
-r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short,_dashboard', 'adr':
+r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short', 'adr':
                {'python': {'name': 'mlperf', 'version_min': '3.8'}, 'tvm': {
                    'tags': '_pip-install'}, 'tvm-model': {'tags': '_graph_executor'}},
                'submitter': 'Community', 'implementation': 'python', 'hw_name': 'default', 'model': 'resnet50', 'backend': 'tvm-onnx',

script/test-cm-core/src/tutorials/test_tutorial_tvm_pip_vm.py

@@ -20,7 +20,7 @@
                'mode': 'accuracy', 'test_query_count': '5', 'clean': 'true', 'quiet': 'yes'})
 checks.check_return(r)
 
-r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short,_dashboard', 'adr':
+r = cm.access({'action': 'run', 'automation': 'script', 'tags': 'run,mlperf,inference,generate-run-cmds,_submission,_short', 'adr':
                {'python': {'name': 'mlperf', 'version_min': '3.8'}, 'tvm': {'tags': '_pip-install'}}, 'submitter': 'Community',
                'implementation': 'python', 'hw_name': 'default', 'model': 'resnet50', 'backend': 'tvm-onnx', 'device': 'cpu', 'scenario': 'Offline',
                'test_query_count': '500', 'clean': 'true', 'quiet': 'yes'})