tidy code based on code review

src/transformers/integrations/integration_utils.py

@@ -1502,10 +1502,7 @@ def setup(self, args, state, model, tokenizer, **kwargs):
                     self._clearml_task = self._clearml.Task.init(
                         project_name=os.getenv("CLEARML_PROJECT", "HuggingFace Transformers"),
                         task_name=os.getenv("CLEARML_TASK", "Trainer"),
-                        auto_connect_frameworks={
-                            "tensorboard": False,
-                            "pytorch": False,
-                        },
+                        auto_connect_frameworks={"tensorboard": False, "pytorch": False},
                         output_uri=True,
                     )
                     self._log_model = os.getenv("CLEARML_LOG_MODEL", "TRUE").upper() in ENV_VARS_TRUE_VALUES.union(
@@ -1515,38 +1512,29 @@ def setup(self, args, state, model, tokenizer, **kwargs):
                     logger.info("ClearML Task has been initialized.")
                 self._initialized = True
 
-            ignore_hparams_config_section = (
-                ClearMLCallback._hparams_section
-                + ClearMLCallback.log_suffix
-                + "/"
-                + ClearMLCallback._ignore_hparams_overrides
-            )
+            suffixed_hparams_section = ClearMLCallback._hparams_section + ClearMLCallback.log_suffix
+            ignore_hparams_config_section = suffixed_hparams_section + "/" + ClearMLCallback._ignore_hparams_overrides
             if self._clearml.Task.running_locally():
-                self._copy_training_args_as_hparams(
-                    args, ClearMLCallback._hparams_section + ClearMLCallback.log_suffix
-                )
+                self._copy_training_args_as_hparams(args, suffixed_hparams_section)
                 self._clearml_task.set_parameter(
                     name=ignore_hparams_config_section,
                     value=True,
                     value_type=bool,
                     description=(
-                        "If True, ignore hyperparameters overrides done in the UI section"
-                        + "when running remotely. Otherwise, the overrides will be used"
+                        "If True, ignore Transformers hyperparameters overrides done in the UI/backend "
+                        + "when running remotely. Otherwise, the overrides will be applied when running remotely"
                     ),
                 )
             elif not self._clearml_task.get_parameter(ignore_hparams_config_section, default=True, cast=True):
-                self._clearml_task.connect(args, ClearMLCallback._hparams_section + ClearMLCallback.log_suffix)
+                self._clearml_task.connect(args, suffixed_hparams_section)
             else:
                 self._copy_training_args_as_hparams(
                     args, ClearMLCallback._hparams_section + ClearMLCallback.log_suffix
                 )
 
             if getattr(model, "config", None) is not None:
                 ignore_model_config_section = (
-                    ClearMLCallback._hparams_section
-                    + ClearMLCallback.log_suffix
-                    + "/"
-                    + ClearMLCallback._ignoge_model_config_overrides
+                    suffixed_hparams_section + "/" + ClearMLCallback._ignoge_model_config_overrides
                 )
                 configuration_object_description = ClearMLCallback._model_config_description.format(
                     ClearMLCallback._model_connect_counter
@@ -1559,8 +1547,8 @@ def setup(self, args, state, model, tokenizer, **kwargs):
                         value=True,
                         value_type=bool,
                         description=(
-                            "If True, ignore model configuration overrides done in the UI section "
-                            + "when running remotely. Otherwise, the overrides will be used"
+                            "If True, ignore Transformers model configuration overrides done in the UI/backend "
+                            + "when running remotely. Otherwise, the overrides will be applied when running remotely"
                         ),
                     )
                     self._clearml_task.set_configuration_object(
@@ -1652,8 +1640,8 @@ def on_save(self, args, state, control, **kwargs):
         if self._log_model and self._clearml_task and state.is_world_process_zero:
             ckpt_dir = f"checkpoint-{state.global_step}"
             artifact_path = os.path.join(args.output_dir, ckpt_dir)
-            logger.info(f"Logging checkpoint artifacts in {ckpt_dir}. This may take time.")
             name = ckpt_dir + ClearMLCallback.log_suffix
+            logger.info(f"Logging checkpoint artifact `{name}`. This may take some time.")
             output_model = self._clearml.OutputModel(task=self._clearml_task, name=name)
             output_model.connect(task=self._clearml_task, name=name)
             output_model.update_weights_package(
@@ -1681,10 +1669,11 @@ def on_save(self, args, state, control, **kwargs):
                 self._checkpoints_saved = self._checkpoints_saved[1:]
 
     def _copy_training_args_as_hparams(self, training_args, prefix):
-        as_dict = {field.name: getattr(training_args, field.name) for field in fields(training_args) if field.init}
-        token_keys = [k for k in as_dict.keys() if k.endswith("_token")]
-        for token_key in token_keys:
-            as_dict.pop(token_key, None)
+        as_dict = {
+            field.name: getattr(training_args, field.name)
+            for field in fields(training_args)
+            if field.init and not field.name.endswith("_token")
+        }
         flat_dict = {str(k): v for k, v in self._clearml.utilities.proxy_object.flatten_dictionary(as_dict).items()}
         self._clearml_task._arguments.copy_from_dict(flat_dict, prefix=prefix)