初始化项目，由ModelHub XC社区提供模型

Model: ayh015/myLightningOPD
Source: Original Platform

slime/utils/train_metric_utils.py

@@ -0,0 +1,51 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import logging
+from argparse import Namespace
+from collections.abc import Callable
+from copy import deepcopy
+
+from slime.utils import tracking_utils
+from slime.utils.metric_utils import compute_rollout_step
+from slime.utils.timer import Timer
+
+logger = logging.getLogger(__name__)
+
+
+def log_perf_data_raw(
+    rollout_id: int, args: Namespace, is_primary_rank: bool, compute_total_fwd_flops: Callable
+) -> None:
+    timer_instance = Timer()
+    log_dict_raw = deepcopy(timer_instance.log_dict())
+    timer_instance.reset()
+
+    if not is_primary_rank:
+        return
+
+    log_dict = {f"perf/{key}_time": val for key, val in log_dict_raw.items()}
+
+    if ("perf/actor_train_time" in log_dict) and (compute_total_fwd_flops is not None):
+        total_fwd_flops = compute_total_fwd_flops(seq_lens=timer_instance.seq_lens)
+
+        if "perf/log_probs_time" in log_dict:
+            log_dict["perf/log_probs_tflops"] = total_fwd_flops / log_dict["perf/log_probs_time"]
+
+        if "perf/ref_log_probs_time" in log_dict:
+            log_dict["perf/ref_log_probs_tflops"] = total_fwd_flops / log_dict["perf/ref_log_probs_time"]
+
+        if log_dict["perf/actor_train_time"] > 0:
+            log_dict["perf/actor_train_tflops"] = 3 * total_fwd_flops / log_dict["perf/actor_train_time"]
+            log_dict["perf/actor_train_tok_per_s"] = sum(timer_instance.seq_lens) / log_dict["perf/actor_train_time"]
+
+    if "perf/train_wait_time" in log_dict and "perf/train_time" in log_dict:
+        total_time = log_dict["perf/train_wait_time"] + log_dict["perf/train_time"]
+        if total_time > 0:
+            log_dict["perf/step_time"] = total_time
+            log_dict["perf/wait_time_ratio"] = log_dict["perf/train_wait_time"] / total_time
+
+    logger.info(f"perf {rollout_id}: {log_dict}")
+
+    step = compute_rollout_step(args, rollout_id)
+    log_dict["rollout/step"] = step
+    tracking_utils.log(args, log_dict, step_key="rollout/step")