Bump version to 0.18.0.dev (#1717)

llmfoundry/_version.py

@@ -3,4 +3,4 @@
 
 """The LLM Foundry Version."""
 
-__version__ = '0.17.0.dev0'
+__version__ = '0.18.0.dev0'

llmfoundry/models/mpt/modeling_mpt.py

@@ -79,8 +79,6 @@
 from llmfoundry.models.layers.norm import LPLayerNorm  # type: ignore
 # isort: on
 
-from llmfoundry.utils.warnings import VersionedDeprecationWarning
-
 log = logging.getLogger(__name__)
 
 CROSS_ENTROPY_IGNORE_INDEX = -100
@@ -1348,7 +1346,6 @@ def compute_loss_from_logits(
     shift_labels: bool,
     labels: torch.Tensor,
     loss_fn: nn.Module,
-    sample_weighing_factor: Optional[torch.Tensor] = None,
 ) -> torch.Tensor:
     targets = get_targets(labels) if shift_labels else labels
 
@@ -1361,18 +1358,6 @@ def compute_loss_from_logits(
         loss = losses.sum()
     else:
         loss = losses.sum() / (targets != loss_fn.ignore_index).sum()
-        if sample_weighing_factor is not None:
-            warnings.warn(
-                VersionedDeprecationWarning(
-                    message='sample_weighing_factor has been deprecated!',
-                    remove_version='0.17.0',
-                ),
-            )
-            if sample_weighing_factor.shape[0] > 1:
-                raise ValueError(
-                    'Sample weighing factor is not supported when batch["sample_weighing_factor"].shape[0] > 1.',
-                )
-            loss = loss * sample_weighing_factor[0].item()
 
     return loss
 
@@ -1481,7 +1466,6 @@ def loss(self, outputs: CausalLMOutputWithPast,
             self.shift_labels,
             batch['labels'],
             self.loss_fn,
-            batch.get('sample_weighing_factor', None),
         )
 
         if self.config.ffn_config['ffn_type'] in ffns_with_megablocks: