Deprecate get_state and remove deprecations

commit-id:5d87db4b

composer/callbacks/mlperf.py

@@ -263,22 +263,8 @@ def _get_dataloader_stats(self, dataloader: Iterable):
             if isinstance(dataloader.dataset, IterableDataset):
                 num_samples *= dist.get_world_size()
             return (dataloader.batch_size, num_samples)
-        try:
-            # attempt to import ffcv and test if its an ffcv loader.
-            import ffcv  # type: ignore
-
-            warnings.warn(DeprecationWarning('ffcv is deprecated and will be removed in v0.18'))
-
-            if isinstance(dataloader, ffcv.loader.Loader):
-                # Use the cached attribute ffcv.init_traversal_order to compute number of samples
-                return (
-                    dataloader.batch_size,  # type: ignore
-                    len(dataloader.next_traversal_order()) * dist.get_world_size()  # type: ignore
-                )
-        except ImportError:
-            pass
-
-        raise TypeError(f'torch dataloader or ffcv dataloader required (and ffcv installed)')
+
+        raise TypeError(f'torch dataloader required')
 
     def fit_start(self, state: State, logger: Logger) -> None:
         if _global_rank_zero():

composer/core/state.py

@@ -733,7 +733,8 @@ def fsdp_sharded_state_dict_enabled(self):
 
     @property
     def fsdp_elastic_sharded_enabled(self):
-        warnings.warn('state.fsdp_elastic_sharded_enabled is deprecated and will be removed v0.21.0')
+        warnings.warn('state.fsdp_elastic_sharded_enabled is deprecated and will be removed v0.21.0',
+                      DeprecationWarning)
         return self.fsdp_sharded_state_dict_enabled
 
     @property

composer/core/time.py

@@ -19,6 +19,7 @@
 
 import datetime
 import re
+import warnings
 from typing import Any, Dict, Generic, Optional, TypeVar, Union, cast
 
 from composer.core.serializable import Serializable
@@ -532,21 +533,8 @@ def get_state(self) -> Dict[str, Union[Time[int], datetime.timedelta]]:
         Returns:
             Dict[str, Union[Time[int], datetime.timedelta]]: All values of the timestamp object.
         """
-        return {
-            'iteration': self.iteration,
-            'epoch': self.epoch,
-            'batch': self.batch,
-            'sample': self.sample,
-            'token': self.token,
-            'epoch_in_iteration': self.epoch_in_iteration,
-            'batch_in_epoch': self.batch_in_epoch,
-            'sample_in_epoch': self.sample_in_epoch,
-            'token_in_epoch': self.token_in_epoch,
-            'total_wct': self.total_wct,
-            'iteration_wct': self.iteration_wct,
-            'epoch_wct': self.epoch_wct,
-            'batch_wct': self.batch_wct,
-        }
+        warnings.warn('core.time.Timestamp.get_state is deprecated and will be removed v0.21.0', DeprecationWarning)
+        return self.state_dict()
 
     def load_state_dict(self, state: Dict[str, Any]) -> None:
         self._epoch = Time(state['epoch'], TimeUnit.EPOCH)

composer/loggers/in_memory_logger.py

@@ -14,7 +14,6 @@
 import numpy as np
 from torch import Tensor
 
-from composer.core.time import Time
 from composer.loggers.logger import Logger
 from composer.loggers.logger_destination import LoggerDestination
 from composer.utils.import_helpers import MissingConditionalImportError
@@ -157,8 +156,8 @@ def get_timeseries(self, metric: str) -> Dict[str, Any]:
             timestamp, metric_value = datapoint
             timeseries.setdefault(metric, []).append(metric_value)
             # Iterate through time units and add them all!
-            for field, time in timestamp.get_state().items():
-                time_value = time.value if isinstance(time, Time) else time.total_seconds()
+            for field, time in timestamp.state_dict().items():
+                time_value = time if isinstance(time, int) else time.total_seconds()
                 timeseries.setdefault(field, []).append(time_value)
         # Convert to numpy arrays
         for k, v in timeseries.items():