Refactor configs (ashleve#306)

configs/logger/comet.yaml

@@ -3,5 +3,5 @@
 comet:
   _target_: pytorch_lightning.loggers.comet.CometLogger
   api_key: ${oc.env:COMET_API_TOKEN} # api key is loaded from environment variable
-  project_name: "template-tests"
+  project_name: "lightning-hydra-template"
   experiment_name: ${name}

configs/logger/neptune.yaml

@@ -3,7 +3,7 @@
 neptune:
   _target_: pytorch_lightning.loggers.neptune.NeptuneLogger
   api_key: ${oc.env:NEPTUNE_API_TOKEN} # api key is loaded from environment variable
-  project_name: your_name/template-tests
+  project_name: your_name/lightning-hydra-template
   close_after_fit: True
   offline_mode: False
   experiment_name: ${name}

configs/logger/wandb.yaml

@@ -2,14 +2,14 @@
 
 wandb:
   _target_: pytorch_lightning.loggers.wandb.WandbLogger
-  project: "template-tests"
-  # name: ${name}
-  save_dir: "."
-  offline: False # set True to store all logs only locally
+  project: "lightning-hydra-template"
+  # name: ${name} # name of the run (normally generated by wandb)
+  # entity: "" # set to name of your wandb team
   id: null # pass correct id to resume experiment!
-  # entity: ""  # set to name of your wandb team
-  log_model: False
-  prefix: ""
-  job_type: "train"
+  save_dir: "."
+  offline: False
+  anonymous: null
+  log_model: False # upload lightning checkpoints
+  job_type: ""
   group: ""
   tags: []

configs/trainer/default.yaml

@@ -2,5 +2,5 @@ _target_: pytorch_lightning.Trainer
 
 gpus: 0
 
-min_epochs: 1
+min_epochs: 1 # prevents early stopping
 max_epochs: 10

setup.cfg

@@ -1,9 +1,3 @@
-[isort]
-line_length = 99
-profile = black
-filter_files = True
-
-
 [flake8]
 max_line_length = 99
 show_source = True