Removing logging exception through update run metadata

llmfoundry/callbacks/curriculum_learning_callback.py

@@ -13,7 +13,7 @@
 
 from composer import DataSpec
 from composer.core import State, Time, TimeUnit, ensure_time
-from composer.loggers import Logger, MosaicMLLogger
+from composer.loggers import Logger
 from streaming import StreamingDataset
 from streaming.base.util import clean_stale_shared_memory
 from torch.utils.data import DataLoader
@@ -23,7 +23,6 @@
     BaseContextualError,
     TrainDataLoaderLocation,
 )
-from llmfoundry.utils.mosaicml_logger_utils import no_override_excepthook
 
 log = logging.getLogger(__name__)
 
@@ -238,13 +237,7 @@ def _build_train_loader(
                 self.device_train_batch_size,
             )
         except BaseContextualError as e:
-            for destination in logger.destinations:
-                if (
-                    isinstance(destination, MosaicMLLogger) and
-                    no_override_excepthook()
-                ):
-                    e.location = TrainDataLoaderLocation
-                    destination.log_exception(e)
+            e.location = TrainDataLoaderLocation
             raise e
 
     def _validate_dataloader(self, train_loader: Any):

llmfoundry/callbacks/run_timeout_callback.py

@@ -8,18 +8,12 @@
 from typing import Optional
 
 from composer import Callback, Logger, State
-from composer.loggers import MosaicMLLogger
-
-from llmfoundry.utils.exceptions import RunTimeoutError
-from llmfoundry.utils.mosaicml_logger_utils import no_override_excepthook
 
 log = logging.getLogger(__name__)
 
 
-def _timeout(timeout: int, mosaicml_logger: Optional[MosaicMLLogger] = None):
+def _timeout(timeout: int):
     log.error(f'Timeout after {timeout} seconds of inactivity after fit_end.',)
-    if mosaicml_logger is not None and no_override_excepthook():
-        mosaicml_logger.log_exception(RunTimeoutError(timeout=timeout))
     os.kill(os.getpid(), signal.SIGINT)
 
 
@@ -30,14 +24,8 @@ def __init__(
         timeout: int = 1800,
     ):
         self.timeout = timeout
-        self.mosaicml_logger: Optional[MosaicMLLogger] = None
         self.timer: Optional[threading.Timer] = None
 
-    def init(self, state: State, logger: Logger):
-        for callback in state.callbacks:
-            if isinstance(callback, MosaicMLLogger):
-                self.mosaicml_logger = callback
-
     def _reset(self):
         if self.timer is not None:
             self.timer.cancel()
@@ -48,7 +36,7 @@ def _timeout(self):
         self.timer = threading.Timer(
             self.timeout,
             _timeout,
-            [self.timeout, self.mosaicml_logger],
+            [self.timeout],
         )
         self.timer.daemon = True
         self.timer.start()

llmfoundry/utils/__init__.py

@@ -46,7 +46,6 @@
     log_eval_analytics,
     log_train_analytics,
     maybe_create_mosaicml_logger,
-    no_override_excepthook,
 )
 from llmfoundry.utils.prompt_files import load_prompts, load_prompts_from_file
 from llmfoundry.utils.registry_utils import (
@@ -98,7 +97,6 @@
     'download_from_hf_hub',
     'download_from_oras',
     'maybe_create_mosaicml_logger',
-    'no_override_excepthook',
     'find_mosaicml_logger',
     'log_eval_analytics',
     'log_train_analytics',

llmfoundry/utils/mosaicml_logger_utils.py

@@ -37,17 +37,6 @@ def maybe_create_mosaicml_logger() -> Optional[MosaicMLLogger]:
         return MosaicMLLogger()
 
 
-def no_override_excepthook() -> bool:
-    """Returns True if the excepthook flag is off.
-
-    This means we are not automatically catching exceptions for MosaicMl runs.
-    """
-    return os.environ.get(
-        'OVERRIDE_EXCEPTHOOK',
-        'false',
-    ).lower() != 'true'
-
-
 def find_mosaicml_logger(
     loggers: List[LoggerDestination],
 ) -> Optional[MosaicMLLogger]:

scripts/data_prep/convert_delta_to_json.py

@@ -34,10 +34,6 @@
 from pyspark.sql.dataframe import DataFrame as SparkDataFrame
 from pyspark.sql.types import Row
 
-from llmfoundry.utils import (
-    maybe_create_mosaicml_logger,
-    no_override_excepthook,
-)
 from llmfoundry.utils.exceptions import (
     ClusterDoesNotExistError,
     FailedToConnectToDatabricksError,
@@ -667,18 +663,10 @@ def fetch_DT(args: Namespace) -> None:
         'The name of the combined final jsonl that combines all partitioned jsonl',
     )
     args = parser.parse_args()
-    mosaicml_logger = maybe_create_mosaicml_logger()
-
-    try:
-        w = WorkspaceClient()
-        args.DATABRICKS_HOST = w.config.host
-        args.DATABRICKS_TOKEN = w.config.token
-
-        tik = time.time()
-        fetch_DT(args)
-        log.info(f'Elapsed time {time.time() - tik}')
+    w = WorkspaceClient()
+    args.DATABRICKS_HOST = w.config.host
+    args.DATABRICKS_TOKEN = w.config.token
 
-    except Exception as e:
-        if mosaicml_logger is not None and no_override_excepthook():
-            mosaicml_logger.log_exception(e)
-        raise e
+    tik = time.time()
+    fetch_DT(args)
+    log.info(f'Elapsed time {time.time() - tik}')

scripts/data_prep/convert_text_to_mds.py

@@ -24,10 +24,6 @@
 from transformers import AutoTokenizer, PreTrainedTokenizerBase
 
 from llmfoundry.data.data import AbstractConcatTokensDataset
-from llmfoundry.utils import (
-    maybe_create_mosaicml_logger,
-    no_override_excepthook,
-)
 from llmfoundry.utils.data_prep_utils import (
     DownloadingIterable,
     download_file,
@@ -608,25 +604,17 @@ def _configure_logging(logging_level: str):
 if __name__ == '__main__':
     args = parse_args()
     _configure_logging(args.logging_level)
-
-    mosaicml_logger = maybe_create_mosaicml_logger()
-
-    try:
-        convert_text_to_mds(
-            tokenizer_name=args.tokenizer,
-            output_folder=args.output_folder,
-            input_folder=args.input_folder,
-            concat_tokens=args.concat_tokens,
-            eos_text=args.eos_text,
-            bos_text=args.bos_text,
-            no_wrap=args.no_wrap,
-            compression=args.compression,
-            processes=args.processes,
-            reprocess=args.reprocess,
-            trust_remote_code=args.trust_remote_code,
-            args_str=_args_str(args),
-        )
-    except Exception as e:
-        if mosaicml_logger is not None and no_override_excepthook():
-            mosaicml_logger.log_exception(e)
-        raise e
+    convert_text_to_mds(
+        tokenizer_name=args.tokenizer,
+        output_folder=args.output_folder,
+        input_folder=args.input_folder,
+        concat_tokens=args.concat_tokens,
+        eos_text=args.eos_text,
+        bos_text=args.bos_text,
+        no_wrap=args.no_wrap,
+        compression=args.compression,
+        processes=args.processes,
+        reprocess=args.reprocess,
+        trust_remote_code=args.trust_remote_code,
+        args_str=_args_str(args),
+    )

scripts/train/train.py

@@ -56,7 +56,6 @@
     EvalDataLoaderLocation,
     TrainDataLoaderLocation,
 )
-from llmfoundry.utils.mosaicml_logger_utils import no_override_excepthook
 from llmfoundry.utils.registry_utils import import_file
 
 log = logging.getLogger(__name__)
@@ -398,8 +397,6 @@ def main(cfg: DictConfig) -> Trainer:
         )
     except BaseContextualError as e:
         e.location = TrainDataLoaderLocation
-        if mosaicml_logger is not None and no_override_excepthook():
-            mosaicml_logger.log_exception(e)
         raise e
 
     if mosaicml_logger is not None:
@@ -431,8 +428,6 @@ def main(cfg: DictConfig) -> Trainer:
                 callbacks.append(eval_gauntlet_callback)
         except BaseContextualError as e:
             e.location = EvalDataLoaderLocation
-            if mosaicml_logger is not None and no_override_excepthook():
-                mosaicml_logger.log_exception(e)
             raise e
 
     if mosaicml_logger is not None:
@@ -481,8 +476,6 @@ def main(cfg: DictConfig) -> Trainer:
             )
     except BaseContextualError as e:
         e.location = EvalDataLoaderLocation
-        if mosaicml_logger is not None and no_override_excepthook():
-            mosaicml_logger.log_exception(e)
         raise e
 
     compile_config = train_cfg.compile_config