chore(beep boop 🤖): Bump uv.lock (main, mcore-dev) (2026-04-13)

.dev.commit

@@ -1 +1 @@
-c72c4599012297cfbd1d57e006b544478b6bbf78
+c0c4fdc45e9f0f8047e29f2cb8669613169752c3

src/megatron/bridge/training/initialize.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import datetime
+import inspect
 import os
 import time
 import warnings
@@ -676,14 +677,20 @@ def _initialize_distributed(
         if parallel_state.model_parallel_is_initialized():
             print("model parallel is already initialized")
         else:
+            # Guard for main/dev branch submodule compat: hybrid_context_parallel was added in the dev branch.
+            # TODO: remove guard once the addition lands in main and Bridge pins the new main commit.
+            _init_mp_params = set(inspect.signature(parallel_state.initialize_model_parallel).parameters)
+            _optional_kwargs = {}
+            if "hybrid_context_parallel" in _init_mp_params:
+                _optional_kwargs["hybrid_context_parallel"] = model_config.hybrid_context_parallel
+
             parallel_state.initialize_model_parallel(
                 tensor_model_parallel_size=model_config.tensor_model_parallel_size,
                 pipeline_model_parallel_size=model_config.pipeline_model_parallel_size,
                 virtual_pipeline_model_parallel_size=model_config.virtual_pipeline_model_parallel_size,
                 pipeline_model_parallel_comm_backend=model_config.pipeline_model_parallel_comm_backend,
                 context_parallel_size=model_config.context_parallel_size,
                 hierarchical_context_parallel_sizes=model_config.hierarchical_context_parallel_sizes,
-                hybrid_context_parallel=model_config.hybrid_context_parallel,
                 expert_model_parallel_size=model_config.expert_model_parallel_size,
                 num_distributed_optimizer_instances=num_distributed_optimizer_instances,
                 expert_tensor_parallel_size=model_config.expert_tensor_parallel_size,
@@ -696,6 +703,7 @@ def _initialize_distributed(
                 use_sharp=dist_config.use_sharp,
                 high_priority_stream_groups=dist_config.high_priority_stream_groups,
                 sharp_enabled_group=dist_config.sharp_enabled_group,
+                **_optional_kwargs,
             )
             if get_rank_safe() == 0:
                 print(

src/megatron/bridge/training/state.py

@@ -20,20 +20,23 @@
 from typing import Any, Optional
 
 import torch
-from megatron.core.energy_monitor import EnergyMonitor
 from megatron.core.timers import Timers
 from megatron.core.utils import StragglerDetector
 from torch.distributed.checkpoint.stateful import Stateful
 from torch.utils.tensorboard.writer import SummaryWriter
 
 
-# TODO: Remove try/except once `get_async_strategy` lands in mcore dev.
-#       The function was added to mcore main but has not yet been merged into dev.
+# TODO: Remove try/except guards once these land in mcore dev.
 try:
     from megatron.core.dist_checkpointing.strategies.torch import get_async_strategy
 except ImportError:
     get_async_strategy = None  # type: ignore[assignment]
 
+try:
+    from megatron.core.energy_monitor import EnergyMonitor
+except ImportError:
+    EnergyMonitor = None  # type: ignore[assignment]
+
 from megatron.bridge.training.config import ConfigContainer
 from megatron.bridge.training.nvrx_straggler import NVRxStragglerDetectionManager
 from megatron.bridge.training.tokenizers.tokenizer import build_tokenizer
@@ -144,7 +147,7 @@ def __init__(self) -> None:
         self._async_calls_queue: Optional[Any] = None
         self._nvrx_straggler_manager: Optional[NVRxStragglerDetectionManager] = None
         self._nvrx_straggler_created: bool = False
-        self._energy_monitor: Optional[EnergyMonitor] = None
+        self._energy_monitor: Optional[Any] = None
         self._energy_monitor_created: bool = False
 
     @property
@@ -440,13 +443,14 @@ def nvrx_straggler_manager(self) -> Optional[NVRxStragglerDetectionManager]:
         return self._nvrx_straggler_manager
 
     @property
-    def energy_monitor(self) -> Optional[EnergyMonitor]:
+    def energy_monitor(self) -> Optional[Any]:
         """The EnergyMonitor instance for tracking energy consumption."""
         if (
             not self._energy_monitor_created
             and self._energy_monitor is None
             and self.cfg is not None
             and self.cfg.logger.log_energy
+            and EnergyMonitor is not None
         ):
             self._energy_monitor = EnergyMonitor()
             self._energy_monitor_created = True