Remove yaml extension from hydra defaults lists (#584)

configs/callbacks/default.yaml

@@ -1,8 +1,8 @@
 defaults:
-  - model_checkpoint.yaml
-  - early_stopping.yaml
-  - model_summary.yaml
-  - rich_progress_bar.yaml
+  - model_checkpoint
+  - early_stopping
+  - model_summary
+  - rich_progress_bar
   - _self_
 
 model_checkpoint:

configs/debug/fdr.yaml

@@ -3,7 +3,7 @@
 # runs 1 train, 1 validation and 1 test step
 
 defaults:
-  - default.yaml
+  - default
 
 trainer:
   fast_dev_run: true

configs/debug/limit.yaml

@@ -3,7 +3,7 @@
 # uses only 1% of the training data and 5% of validation/test data
 
 defaults:
-  - default.yaml
+  - default
 
 trainer:
   max_epochs: 3

configs/debug/overfit.yaml

@@ -3,7 +3,7 @@
 # overfits to 3 batches
 
 defaults:
-  - default.yaml
+  - default
 
 trainer:
   max_epochs: 20

configs/debug/profiler.yaml

@@ -3,7 +3,7 @@
 # runs with execution time profiling
 
 defaults:
-  - default.yaml
+  - default
 
 trainer:
   max_epochs: 1

configs/eval.yaml

@@ -2,13 +2,13 @@
 
 defaults:
   - _self_
-  - data: mnist.yaml # choose datamodule with `test_dataloader()` for evaluation
-  - model: mnist.yaml
+  - data: mnist # choose datamodule with `test_dataloader()` for evaluation
+  - model: mnist
   - logger: null
-  - trainer: default.yaml
-  - paths: default.yaml
-  - extras: default.yaml
-  - hydra: default.yaml
+  - trainer: default
+  - paths: default
+  - extras: default
+  - hydra: default
 
 task_name: "eval"
 

configs/experiment/example.yaml

@@ -4,10 +4,10 @@
 # python train.py experiment=example
 
 defaults:
-  - override /data: mnist.yaml
-  - override /model: mnist.yaml
-  - override /callbacks: default.yaml
-  - override /trainer: default.yaml
+  - override /data: mnist
+  - override /model: mnist
+  - override /callbacks: default
+  - override /trainer: default
 
 # all parameters below will be merged with parameters from default configurations set above
 # this allows you to overwrite only specified parameters

configs/logger/many_loggers.yaml

@@ -1,9 +1,9 @@
 # train with many loggers at once
 
 defaults:
-  # - comet.yaml
-  - csv.yaml
-  # - mlflow.yaml
-  # - neptune.yaml
-  - tensorboard.yaml
-  - wandb.yaml
+  # - comet
+  - csv
+  # - mlflow
+  # - neptune
+  - tensorboard
+  - wandb

configs/train.yaml

@@ -4,14 +4,14 @@
 # order of defaults determines the order in which configs override each other
 defaults:
   - _self_
-  - data: mnist.yaml
-  - model: mnist.yaml
-  - callbacks: default.yaml
+  - data: mnist
+  - model: mnist
+  - callbacks: default
   - logger: null # set logger here or use command line (e.g. `python train.py logger=tensorboard`)
-  - trainer: default.yaml
-  - paths: default.yaml
-  - extras: default.yaml
-  - hydra: default.yaml
+  - trainer: default
+  - paths: default
+  - extras: default
+  - hydra: default
 
   # experiment configs allow for version control of specific hyperparameters
   # e.g. best hyperparameters for given model and datamodule
@@ -22,7 +22,7 @@ defaults:
 
   # optional local config for machine/user specific settings
   # it's optional since it doesn't need to exist and is excluded from version control
-  - optional local: default.yaml
+  - optional local: default
 
   # debugging config (enable through command line, e.g. `python train.py debug=default)
   - debug: null

configs/trainer/cpu.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default.yaml
+  - default
 
 accelerator: cpu
 devices: 1

configs/trainer/ddp.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default.yaml
+  - default
 
 strategy: ddp
 

configs/trainer/ddp_sim.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default.yaml
+  - default
 
 # simulate DDP on CPU, useful for debugging
 accelerator: cpu

configs/trainer/gpu.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default.yaml
+  - default
 
 accelerator: gpu
 devices: 1

configs/trainer/mps.yaml

@@ -1,5 +1,5 @@
 defaults:
-  - default.yaml
+  - default
 
 accelerator: mps
 devices: 1