Updated output config file to be same as config file (#267)

* Updated output config file to be same as config file

* Remove yaml from imports since it is not used anymore

* Edited to copy config-lock using shutil

- Removed write_config_to_output_dir() function
- Uses shutil to write to the output dir
- Edited so that config-lock.yaml is copies after output_dir is created

* Modified to copy config.yaml to output dir in rest of the templates

* Satisfy lint

---------

Co-authored-by: vfdev <[email protected]>

Author: theory-in-progress

src/templates/template-text-classification/main.py

@@ -1,9 +1,9 @@
 import os
 from pprint import pformat
+from shutil import copy
 from typing import Any, cast
 
 import ignite.distributed as idist
-import yaml
 from data import setup_data
 from ignite.engine import Events
 from ignite.handlers import LRScheduler, PiecewiseLinear
@@ -27,8 +27,10 @@ def run(local_rank: int, config: Any):
     rank = idist.get_rank()
     manual_seed(config.seed + rank)
 
-    # create output folder
+    # create output folder and copy config file to output dir
     config.output_dir = setup_output_dir(config, rank)
+    if rank == 0:
+        copy(config.config, f"{config.output_dir}/config-lock.yaml")
 
     # donwload datasets and create dataloaders
     dataloader_train, dataloader_eval = setup_data(config)
@@ -79,7 +81,6 @@ def run(local_rank: int, config: Any):
     # print training configurations
     logger = setup_logging(config)
     logger.info("Configuration: \n%s", pformat(vars(config)))
-    (config.output_dir / "config-lock.yaml").write_text(yaml.dump(config))
     trainer.logger = evaluator.logger = logger
 
     if isinstance(lr_scheduler, PyTorchLRScheduler):

src/templates/template-vision-classification/main.py

@@ -1,8 +1,8 @@
 from pprint import pformat
+from shutil import copy
 from typing import Any
 
 import ignite.distributed as idist
-import yaml
 from data import setup_data
 from ignite.engine import Events
 from ignite.handlers import PiecewiseLinear
@@ -19,8 +19,10 @@ def run(local_rank: int, config: Any):
     rank = idist.get_rank()
     manual_seed(config.seed + rank)
 
-    # create output folder
+    # create output folder and copy config file to output dir
     config.output_dir = setup_output_dir(config, rank)
+    if rank == 0:
+        copy(config.config, f"{config.output_dir}/config-lock.yaml")
 
     # donwload datasets and create dataloaders
     dataloader_train, dataloader_eval = setup_data(config)
@@ -60,7 +62,6 @@ def run(local_rank: int, config: Any):
     # print training configurations
     logger = setup_logging(config)
     logger.info("Configuration: \n%s", pformat(vars(config)))
-    (config.output_dir / "config-lock.yaml").write_text(yaml.dump(config))
     trainer.logger = evaluator.logger = logger
 
     trainer.add_event_handler(Events.ITERATION_COMPLETED, lr_scheduler)

src/templates/template-vision-dcgan/main.py

@@ -1,10 +1,10 @@
 from pprint import pformat
+from shutil import copy
 from typing import Any
 
 import ignite.distributed as idist
 import torch
 import torchvision.utils as vutils
-import yaml
 from data import setup_data
 from ignite.engine import Events
 from ignite.utils import manual_seed
@@ -22,8 +22,10 @@ def run(local_rank: int, config: Any):
     rank = idist.get_rank()
     manual_seed(config.seed + rank)
 
-    # create output folder
+    # create output folder and copy config file to output dir
     config.output_dir = setup_output_dir(config, rank)
+    if rank == 0:
+        copy(config.config, f"{config.output_dir}/config-lock.yaml")
 
     # donwload datasets and create dataloaders
     dataloader_train, dataloader_eval, num_channels = setup_data(config)
@@ -77,7 +79,6 @@ def run(local_rank: int, config: Any):
     # print training configurations
     logger = setup_logging(config)
     logger.info("Configuration: \n%s", pformat(vars(config)))
-    (config.output_dir / "config-lock.yaml").write_text(yaml.dump(config))
     trainer.logger = evaluator.logger = logger
 
     # setup ignite handlers

src/templates/template-vision-segmentation/main.py

@@ -1,9 +1,9 @@
 from functools import partial
 from pprint import pformat
+from shutil import copy
 from typing import Any, cast
 
 import ignite.distributed as idist
-import yaml
 from data import denormalize, setup_data
 from ignite.engine import Events
 from ignite.handlers import LRScheduler
@@ -27,8 +27,10 @@ def run(local_rank: int, config: Any):
     rank = idist.get_rank()
     manual_seed(config.seed + rank)
 
-    # create output folder
+    # create output folder and copy config file to output dir
     config.output_dir = setup_output_dir(config, rank)
+    if rank == 0:
+        copy(config.config, f"{config.output_dir}/config-lock.yaml")
 
     # donwload datasets and create dataloaders
     dataloader_train, dataloader_eval = setup_data(config)
@@ -73,7 +75,6 @@ def run(local_rank: int, config: Any):
     # print training configurations
     logger = setup_logging(config)
     logger.info("Configuration: \n%s", pformat(vars(config)))
-    (config.output_dir / "config-lock.yaml").write_text(yaml.dump(config))
     trainer.logger = evaluator.logger = logger
 
     if isinstance(lr_scheduler, PyTorchLRScheduler):