Add parallelism optional keys

mlperf_logging/compliance_checker/mlp_compliance.py

@@ -217,6 +217,13 @@ def configured_checks(self, loglines, config_file):
             if 'REQ' not in v:
                 continue
 
+            if v['REQ'] == 'OPTIONAL':
+                if len(reported_values[k]) == 0:
+                    # self.put_warning(f"OPTIONAL key '{k}' not reported", 
+                    #                  key=k)
+                    continue
+
+
             if v['REQ']=='EXACTLY_ONE':
                 if len(reported_values[k]) !=1:
                     if reported_values[k] and all_same(reported_values[k]):

mlperf_logging/compliance_checker/training_6.0.0/common.yaml

@@ -144,3 +144,33 @@
     REQ:   EXACTLY_ONE
     CHECK: " v['value'] != '' "
 
+# Optional parallelism keys
+- KEY:
+    NAME:  tensor_parallelism
+    REQ:   OPTIONAL
+    CHECK: " is_integer(v['value']) "
+
+- KEY:
+    NAME:  pipeline_parallelism
+    REQ:   OPTIONAL
+    CHECK: " is_integer(v['value']) "
+
+- KEY:
+    NAME:  context_parallelism
+    REQ:   OPTIONAL
+    CHECK: " is_integer(v['value']) "
+
+- KEY:
+    NAME:  expert_parallelism
+    REQ:   OPTIONAL
+    CHECK: " is_integer(v['value']) "
+
+- KEY:
+    NAME:  micro_batch_size
+    REQ:   OPTIONAL
+    CHECK: " is_integer(v['value']) "
+
+- KEY:
+    NAME:  config_filename
+    REQ:   OPTIONAL
+

mlperf_logging/mllog/constants.py

@@ -196,3 +196,12 @@
 POWER_READING = "power_reading"
 CONVERTION_EFF = "conversion_eff"
 INTERCONNECT_POWER_EST = "interconnect_power_est"
+
+# Parallelism constants
+TENSOR_PARALLELISM = "tensor_parallelism"
+PIPELINE_PARALLELISM = "pipeline_parallelism"
+CONTEXT_PARALLELISM = "context_parallelism"
+EXPERT_PARALLELISM = "expert_parallelism"
+MICRO_BATCH_SIZE = "micro_batch_size"
+
+CONFIG_FILENAME = "config_filename"

mlperf_logging/mllog/examples/parallelism.py

@@ -0,0 +1,53 @@
+# Copyright 2019 MLBenchmark Group. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+import os
+
+from mlperf_logging import mllog
+
+
+def parallelism_example():
+  """Example usage of mllog with parallelism and config keys"""
+
+  mllogger = mllog.get_mllogger()
+
+  mllog.config(
+      filename="parallelism_example.log",
+      default_namespace="worker1",
+      default_stack_offset=1,
+      default_clear_line=False,
+      root_dir=os.path.normpath(
+          os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "..")))
+
+  mllogger.start(key=mllog.constants.RUN_START)
+
+  # Log the model config file used for this run
+  mllogger.event(key=mllog.constants.CONFIG_FILENAME, value="llama31_405b_config.yaml")
+
+  # Log parallelism strategy
+  mllogger.event(key=mllog.constants.TENSOR_PARALLELISM, value=8)
+  mllogger.event(key=mllog.constants.PIPELINE_PARALLELISM, value=4)
+  mllogger.event(key=mllog.constants.CONTEXT_PARALLELISM, value=2)
+  mllogger.event(key=mllog.constants.EXPERT_PARALLELISM, value=1)
+
+  # Log micro batch size alongside global batch size
+  mllogger.event(key=mllog.constants.GLOBAL_BATCH_SIZE, value=2048)
+  mllogger.event(key=mllog.constants.MICRO_BATCH_SIZE, value=1)
+
+  mllogger.end(key=mllog.constants.RUN_STOP, metadata={mllog.constants.STATUS: mllog.constants.SUCCESS})
+
+
+if __name__ == "__main__":
+  parallelism_example()