Remove unused function

src/compressed_tensors/quantization/lifecycle/helpers.py

@@ -16,62 +16,15 @@
 Miscelaneous helpers for the quantization lifecycle
 """
 
-from typing import Optional
-
-import torch
 from torch.nn import Module
 
 
 __all__ = [
-    "update_layer_weight_quant_params",
     "enable_quantization",
     "disable_quantization",
 ]
 
 
-def update_layer_weight_quant_params(
-    layer: Module,
-    weight: Optional[torch.Tensor] = None,
-    g_idx: Optional[torch.Tensor] = None,
-    reset_obs: bool = False,
-):
-    """
-    Update quantization parameters on layer
-
-    :param layer: input layer
-    :param weight: weight to update quant params with, defaults to layer weight
-    :param g_idx: optional mapping from column index to group index
-    :param reset_obs: reset the observer before calculating quant params,
-        defaults to False
-    """
-    attached_weight = getattr(layer, "weight", None)
-
-    if weight is None:
-        weight = attached_weight
-    scale = getattr(layer, "weight_scale", None)
-    zero_point = getattr(layer, "weight_zero_point", None)
-    if g_idx is None:
-        g_idx = getattr(layer, "weight_g_idx", None)
-    observer = getattr(layer, "weight_observer", None)
-
-    if weight is None or observer is None or scale is None or zero_point is None:
-        # scale, zp, or observer not calibratable or weight not available
-        return
-
-    if reset_obs:
-        observer.reset()
-
-    if attached_weight is not None:
-        weight = weight.to(attached_weight.dtype)
-
-    updated_scale, updated_zero_point = observer(weight)
-
-    # update scale and zero point
-    device = next(layer.parameters()).device
-    scale.data = updated_scale.to(device)
-    zero_point.data = updated_zero_point.to(device)
-
-
 def enable_quantization(module: Module):
     module.quantization_enabled = True