[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

unsloth/__init__.py

@@ -208,9 +208,11 @@ elif DEVICE_TYPE == "xpu":
 # Backwards compatibility: some notebooks import `unsloth.is_bf16_supported`.
 # Ensure it exists on all backends (HIP / XPU) and has a stable signature.
 if "is_bf16_supported" not in globals():
+
     def is_bf16_supported(including_emulation = False):
         return SUPPORTS_BFLOAT16
 
+
 # For Gradio HF Spaces?
 # if "SPACE_AUTHOR_NAME" not in os.environ and "SPACE_REPO_NAME" not in os.environ:
 import triton

unsloth/kernels/utils.py

@@ -110,6 +110,7 @@ def calculate_settings(
 HAS_CUDA_STREAM = False
 try:
     import bitsandbytes as bnb
+
     # https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1330/files
     HAS_CUDA_STREAM = Version(bnb.__version__) > Version("0.43.3")
     get_ptr = bnb.functional.get_ptr
@@ -197,8 +198,12 @@ if bnb is not None:
         cgemm_4bit_inference_naive_fp16 = bnb.functional.lib.cgemv_4bit_inference_fp16
         cgemm_4bit_inference_naive_bf16 = bnb.functional.lib.cgemv_4bit_inference_bf16
     else:
-        cgemm_4bit_inference_naive_fp16 = bnb.functional.lib.cgemm_4bit_inference_naive_fp16
-        cgemm_4bit_inference_naive_bf16 = bnb.functional.lib.cgemm_4bit_inference_naive_bf16
+        cgemm_4bit_inference_naive_fp16 = (
+            bnb.functional.lib.cgemm_4bit_inference_naive_fp16
+        )
+        cgemm_4bit_inference_naive_bf16 = (
+            bnb.functional.lib.cgemm_4bit_inference_naive_bf16
+        )
 else:
     cdequantize_blockwise_fp32 = None
     cdequantize_blockwise_fp16_nf4 = None
@@ -207,7 +212,6 @@ else:
     cgemm_4bit_inference_naive_bf16 = None
 
 
-
 torch_device_stream = (
     torch.xpu.current_stream if DEVICE_TYPE == "xpu" else torch.cuda.current_stream
 )

unsloth/models/_utils.py

@@ -1914,7 +1914,10 @@ def patch_fast_lora():
     try:
         import peft.tuners.lora.bnb
     except Exception as e:
-        print("Unsloth: bitsandbytes/peft bnb not available - skipping 4bit LoRA patch.", repr(e))
+        print(
+            "Unsloth: bitsandbytes/peft bnb not available - skipping 4bit LoRA patch.",
+            repr(e),
+        )
         return
 
     peft.tuners.lora.bnb.Linear4bit.forward = fast_lora_forward

unsloth/models/granite.py

@@ -30,6 +30,7 @@ from .llama import (
     LlamaLinearScalingRotaryEmbedding,
 )
 from .mistral import *
+
 try:
     from bitsandbytes.nn import Linear4bit as Bnb_Linear4bit
 except Exception:
@@ -40,9 +41,7 @@ try:
 except Exception:
     Peft_Linear4bit = None
 
-_BNB_LINEAR_TYPES = tuple(
-    t for t in (Bnb_Linear4bit, Peft_Linear4bit) if t is not None
-)
+_BNB_LINEAR_TYPES = tuple(t for t in (Bnb_Linear4bit, Peft_Linear4bit) if t is not None)
 
 try:
     from transformers.models.granite.modeling_granite import (

unsloth/models/llama.py

@@ -3004,7 +3004,11 @@ class FastLlamaModel:
         # PEFT API compatibility: only pass kwargs supported by the installed peft version.
         try:
             import inspect as _inspect
-            if "ensure_weight_tying" not in _inspect.signature(LoraConfig.__init__).parameters:
+
+            if (
+                "ensure_weight_tying"
+                not in _inspect.signature(LoraConfig.__init__).parameters
+            ):
                 arguments.pop("ensure_weight_tying", None)
         except Exception:
             arguments.pop("ensure_weight_tying", None)

unsloth/save.py

@@ -23,6 +23,7 @@ from unsloth_zoo.llama_cpp import (
     check_llama_cpp,
     _download_convert_hf_to_gguf,
 )
+
 try:
     from bitsandbytes.nn import Linear4bit as Bnb_Linear4bit
 except Exception:
@@ -65,7 +66,9 @@ except:
 from pathlib import Path
 from peft import PeftModelForCausalLM, PeftModel
 
-_MERGE_LORA_LINEAR_TYPES = tuple(t for t in (Bnb_Linear4bit, Peft_Linear4bit, Peft_Linear) if t is not None)
+_MERGE_LORA_LINEAR_TYPES = tuple(
+    t for t in (Bnb_Linear4bit, Peft_Linear4bit, Peft_Linear) if t is not None
+)
 
 __all__ = [
     "print_quantization_methods",