style

Signed-off-by: Kyle Sayers <[email protected]>

Author: kylesayrs

src/llmcompressor/modifiers/quantization/calibration.py

@@ -198,7 +198,7 @@ def calibrate_activations(module: Module, value: torch.Tensor, base_name: str):
             calculate_qparams = False
         if quantization_args.strategy == QuantizationStrategy.TENSOR_GROUP:
             calculate_gparam = True
-    
+
     # (..., 1, hidden_dim)
     # this reshaping is mostly for the benefit of group quantization
     value = value.unsqueeze(-2)

src/llmcompressor/observers/base.py

@@ -8,9 +8,8 @@
     QuantizationArgs,
     QuantizationStrategy,
 )
-from compressed_tensors.quantization.utils import is_fp4
+from compressed_tensors.quantization.utils import is_fp4, strict_divide
 from compressed_tensors.registry.registry import RegistryMixin
-from compressed_tensors.quantization.utils import strict_divide
 from loguru import logger
 from torch import FloatTensor, IntTensor, Tensor
 
@@ -255,10 +254,7 @@ def get_qparams_along_dim(
         dim = set(dim)
 
         # convert negative dims
-        dim = [
-            d if d >= 0 else observed.ndim + d
-            for d in dim
-        ]
+        dim = [d if d >= 0 else observed.ndim + d for d in dim]
 
         # reduce all dimensions except the the one pass as argument to this function
         reduce_dims = tuple(idx for idx in range(observed.ndim) if idx not in dim)