chore: lint

src/axolotl/cli/args.py

@@ -13,7 +13,12 @@ class PreprocessCliArgs:
     debug_num_examples: int = field(default=1)
     prompter: Optional[str] = field(default=None)
     download: Optional[bool] = field(default=True)
-    iterable: Optional[bool] = field(default=None, metadata={"help": "Use IterableDataset for streaming processing of large datasets"})
+    iterable: Optional[bool] = field(
+        default=None,
+        metadata={
+            "help": "Use IterableDataset for streaming processing of large datasets"
+        },
+    )
 
 
 @dataclass

src/axolotl/cli/preprocess.py

@@ -3,7 +3,7 @@
 import logging
 import warnings
 from pathlib import Path
-from typing import Optional, Union
+from typing import Union
 
 import fire
 import transformers

src/axolotl/common/datasets.py

@@ -63,7 +63,11 @@ def load_datasets(
     """
     tokenizer = load_tokenizer(cfg)
     processor = load_processor(cfg, tokenizer=tokenizer) if cfg.processor_type else None
-    preprocess_iterable = hasattr(cli_args, "iterable") and cli_args.iterable is not None and cli_args.iterable
+    preprocess_iterable = (
+        hasattr(cli_args, "iterable")
+        and cli_args.iterable is not None
+        and cli_args.iterable
+    )
 
     train_dataset, eval_dataset, total_num_steps, prompters = prepare_dataset(
         cfg,

src/axolotl/utils/data/sft.py

@@ -3,7 +3,7 @@
 import functools
 import logging
 from pathlib import Path
-from typing import List, Tuple, Union, Optional
+from typing import List, Optional, Tuple, Union
 
 from datasets import (
     Dataset,

tests/e2e/integrations/test_kd.py

@@ -6,8 +6,8 @@ from pathlib import Path
 import pytest
 from e2e.utils import check_tensorboard, require_torch_2_5_1
 
-from axolotl.cli import load_datasets
+from axolotl.cli.args import TrainerCliArgs
-from axolotl.common.cli import TrainerCliArgs
+from axolotl.common.datasets import load_datasets
 from axolotl.train import train
 from axolotl.utils.config import normalize_config, prepare_plugins
 from axolotl.utils.dict import DictDefault
@@ -84,7 +84,7 @@ class TestKnowledgeDistillation:
         cli_args = TrainerCliArgs()
         dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
 
-        train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
+        train(cfg=cfg, dataset_meta=dataset_meta)
         assert (Path(temp_dir) / "model.safetensors").exists()
         check_tensorboard(
             temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high"
@@ -114,7 +114,7 @@ class TestKnowledgeDistillation:
         cli_args = TrainerCliArgs()
         dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
 
-        train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
+        train(cfg=cfg, dataset_meta=dataset_meta)
         assert (Path(temp_dir) / "adapter_model.safetensors").exists()
         check_tensorboard(
             temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high"