build: format codebase imports using ruff linter (#1028)

# What does this PR do?

- Configured ruff linter to automatically fix import sorting issues.
- Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are
applied.
- Enabled the 'I' selection to focus on import-related linting rules.
- Ran the linter, and formatted all codebase imports accordingly.
- Removed the black dep from the "dev" group since we use ruff

Signed-off-by: Sébastien Han <seb@redhat.com>

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)

Signed-off-by: Sébastien Han <seb@redhat.com>

llama_stack/providers/inline/post_training/torchtune/common/utils.py

@@ -15,10 +15,8 @@ from typing import Any, Callable, Dict
 import torch
 from llama_models.datatypes import Model
 from llama_models.sku_list import resolve_model
-
 from pydantic import BaseModel
 from torchtune.data._messages import InputOutputToMessages, ShareGPTToMessages
-
 from torchtune.models.llama3 import llama3_tokenizer
 from torchtune.models.llama3._tokenizer import Llama3Tokenizer
 from torchtune.models.llama3_1 import lora_llama3_1_8b

llama_stack/providers/inline/post_training/torchtune/datasets/sft.py

@@ -13,7 +13,6 @@
 from typing import Any, Dict, List, Mapping
 
 import numpy as np
-
 from torch.utils.data import Dataset
 from torchtune.data._common import CROSS_ENTROPY_IGNORE_IDX
 from torchtune.data._messages import validate_messages

llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py

@@ -18,9 +18,9 @@ from llama_models.sku_list import resolve_model
 from torch import nn
 from torch.optim import Optimizer
 from torch.utils.data import DataLoader, DistributedSampler
-from torchtune import modules, training, utils as torchtune_utils
+from torchtune import modules, training
+from torchtune import utils as torchtune_utils
 from torchtune.data import padded_collate_sft
-
 from torchtune.modules.loss import CEWithChunkedOutputLoss
 from torchtune.modules.peft import (
     get_adapter_params,
@@ -44,14 +44,11 @@ from llama_stack.apis.post_training import (
     OptimizerConfig,
     TrainingConfig,
 )
-
 from llama_stack.distribution.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
-
 from llama_stack.distribution.utils.model_utils import model_local_dir
 from llama_stack.providers.inline.post_training.common.validator import (
     validate_input_dataset_schema,
 )
-
 from llama_stack.providers.inline.post_training.torchtune.common import utils
 from llama_stack.providers.inline.post_training.torchtune.common.checkpointer import (
     TorchtuneCheckpointer,