reactivate 3.8 tests

.github/workflows/ci.yml

@@ -39,7 +39,7 @@ jobs:
         strategy:
             max-parallel: 4
             matrix:
-                python-version: ["3.9", "3.10", "3.11"]
+                python-version: ["3.8", "3.9", "3.10", "3.11"]
         steps:
 
             - uses: actions/checkout@v3

tox.ini

@@ -1,6 +1,6 @@
 [tox]
 minversion = 3.4.0
-envlist = py{310,39,38}
+envlist = py{311,310,39,38}
 isolated_build = True
 skip_missing_interpreters = true
 
@@ -14,6 +14,7 @@ script_launch_mode = subprocess
 
 [gh-actions]
 python =
+    3.8: py38
     3.9: py39
     3.10: py310
     3.11: py311

zeldarose/train_transformer.py

@@ -95,7 +95,8 @@ def emit(self, record):
             if frame is None:
                 warnings.warn(
                     "Catching calls to logging is impossible in stackless environment,"
-                    " logging from external libraries might be lost."
+                    " logging from external libraries might be lost.",
+                    stacklevel=2,
                 )
             else:
                 if self.wrapped_name is not None:
@@ -268,7 +269,7 @@ def on_train_epoch_end(self, trainer: pl.Trainer, pl_module: TrainingModule):
 @click.option(
     "--precision",
     type=click.Choice(["64", "32", "16", "bf16"]),
-    help="The precision of float for traingin",
+    help="The precision of float for training",
 )
 @click.option(
     "--pretrained-model",
@@ -401,7 +402,7 @@ def main(
         total_devices = num_nodes * num_devices
     logger.info(f"Training on a total of {total_devices} devices.")
 
-    tuning_config = TrainConfig.parse_obj(config.get("tuning", dict()))
+    tuning_config = TrainConfig.model_validate(config.get("tuning", dict()))
 
     if tuning_config.max_steps is not None:
         max_steps = tuning_config.max_steps