swap operations

Author: dsikka

src/compressed_tensors/quantization/lifecycle/forward.py

@@ -380,7 +380,7 @@ def _quantize(
 ) -> torch.Tensor:
 
     if global_scale:
-        scale = scale.to(global_scale.dtype) * global_scale
+        scale = scale.to(global_scale.dtype) / global_scale
 
     scaled = x / scale
     if zero_point is not None:
@@ -409,7 +409,7 @@ def _dequantize(
 ) -> torch.Tensor:
 
     if global_scale:
-        scale = scale.to(global_scale.dtype) * global_scale
+        scale = scale.to(global_scale.dtype) / global_scale
 
     dequant_value = x_q.to(scale.dtype)
 

src/compressed_tensors/quantization/utils/helpers.py

@@ -87,17 +87,14 @@ def calculate_qparams(
             and quantization_args.type == QuantizationType.FLOAT
         ):
             assert global_scale is not None
-            breakpoint()
-            scales = max_val_pos / FP4_E2M1_DATA.max  # Not needed
-            scales = scales / global_scale
-            scales = scales.to(FP8_E4M3_DATA.dtype)  # .to(torch.float32)
-
+            scales = global_scale * (max_val_pos / FP4_E2M1_DATA.max)  # Not needed
+            # scales = scales / global_scale
+            scales = scales.to(FP8_E4M3_DATA.dtype)
         else:
             # Divide over bit range over max value?
-            scales = max_val_pos / (float(bit_range) / 2)
+            scales = max_val_pos / (float(bit_radnge) / 2)
 
         # TODO: clamp not implemented for FP8 '
-        breakpoint()
         # scales = torch.clamp(scales, min=torch.finfo(torch.float32).eps)
         zero_points = torch.zeros(scales.shape, device=device, dtype=min_vals.dtype)
     else: