quick fix (#4697)

CHANGELOG.md

@@ -55,6 +55,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed docs typo ([#4659](https://github.com/PyTorchLightning/pytorch-lightning/pull/4659), [#4670](https://github.com/PyTorchLightning/pytorch-lightning/pull/4670))
 - Fixed notebooks typo ([#4657](https://github.com/PyTorchLightning/pytorch-lightning/pull/4657))
 - Allowing decorate model init with saving `hparams` inside ([#4662](https://github.com/PyTorchLightning/pytorch-lightning/pull/4662))
+- Fixed `split_idx` set by `LoggerConnector` in `on_trainer_init` to `Trainer`  ([#4697](https://github.com/PyTorchLightning/pytorch-lightning/pull/4697))
 
 
 

pytorch_lightning/trainer/connectors/logger_connector.py

@@ -12,17 +12,19 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
+from collections import ChainMap
+from copy import deepcopy
+from pprint import pprint
+from typing import Iterable
+
 import torch
+
 from pytorch_lightning.core import memory
-from pytorch_lightning.loggers import TensorBoardLogger, LoggerCollection
-from pytorch_lightning.utilities import flatten_dict
-from pytorch_lightning.utilities.model_utils import is_overridden
 from pytorch_lightning.core.step_result import EvalResult, Result
+from pytorch_lightning.loggers import LoggerCollection, TensorBoardLogger
+from pytorch_lightning.utilities import flatten_dict
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
-from pprint import pprint
-from typing import Iterable
-from copy import deepcopy
-from collections import ChainMap
+from pytorch_lightning.utilities.model_utils import is_overridden
 
 
 class LoggerConnector:
@@ -42,6 +44,18 @@ def on_trainer_init(self, logger, flush_logs_every_n_steps, log_every_n_steps):
         self.trainer.flush_logs_every_n_steps = flush_logs_every_n_steps
         self.trainer.log_every_n_steps = log_every_n_steps
 
+        self.trainer.split_idx = None
+
+    @property
+    def should_flush_logs(self):
+        should_flush = (self.trainer.global_step + 1) % self.trainer.flush_logs_every_n_steps == 0
+        return should_flush or self.trainer.should_stop
+
+    @property
+    def should_update_logs(self):
+        should_log_every_n_steps = (self.trainer.global_step + 1) % self.trainer.log_every_n_steps == 0
+        return should_log_every_n_steps or self.trainer.should_stop
+
     def configure_logger(self, logger):
         if logger is True:
             version = os.environ.get('PL_EXP_VERSION', self.trainer.slurm_job_id)