deduplicate code for get_group_qparams_symmetric

Summary:
This just removes the implementation, we can have follow up PRs to remove the call all together
after we have replaced all implementation with the new blockwise quant code

Test Plan:
CI

Reviewers:

Subscribers:

Tasks:

Tags:

torchao/quantization/quant_primitives.py

@@ -729,25 +729,38 @@ def get_group_qparams_symmetric(w, n_bit=4, groupsize=128, precision=torch.float
     assert w.shape[-1] % groupsize == 0
     assert w.dim() == 2
 
-    to_quant = w.reshape(-1, groupsize)
-    assert torch.isnan(to_quant).sum() == 0
-
-    max_val = to_quant.amax(dim=1, keepdim=True)
-    min_val = to_quant.amin(dim=1, keepdim=True)
-    min_val_neg = torch.min(min_val, torch.zeros_like(min_val))
-    max_val_pos = torch.max(max_val, torch.zeros_like(max_val))
-
-    max_val_abs = torch.max(-min_val_neg, max_val_pos)
-    max_int = 2 ** (n_bit - 1) - 1
-    min_int = -(2 ** (n_bit - 1))
-
-    scales = max_val_abs / (float(max_int - min_int) / 2)
-    scales = torch.max(scales, torch.full_like(scales, torch.finfo(torch.float32).eps))
-    # TODO: make sure abs(scales) is not too small?
-    zeros = torch.full_like(scales, 0)
-    return scales.to(precision).reshape(w.shape[0], -1), zeros.to(precision).reshape(
-        w.shape[0], -1
-    )
+    block_size = (w.shape[0], groupsize)
+    mapping_type = MappingType.SYMMETRIC
+    eps = torch.finfo(torch.float32).eps
+    if TORCH_VERSION_AFTER_2_3:
+        bit_to_dtype = {
+            1: torch.uint1,
+            2: torch.uint2,
+            3: torch.uint3,
+            4: torch.uint4,
+            5: torch.uint5,
+            6: torch.uint6,
+            7: torch.uint7,
+            8: torch.uint8,
+        }
+        assert n_bit in ranges, f"unsupported bit: {n_bit}"
+        target_dtype = bit_to_dtype[n_bit]
+        return choose_qparams_affine(w, mapping_type, block_size, target_dtype=target_dtype, eps=eps, scale_dtype=precision, zero_point_dtype=precision)
+    else:
+        ranges = {
+            1: (0, 2**1-1),
+            2: (0, 2**2-1),
+            3: (0, 2**3-1),
+            4: (0, 2**4-1),
+            5: (0, 2**5-1),
+            6: (0, 2**6-1),
+            7: (0, 2**7-1),
+            8: (0, 2**8-1),
+        }
+        assert n_bit in ranges, f"unsupported bit: {n_bit}"
+        quant_min, quant_max = ranges[n_bit]
+        # using uint8 to simulate uint4
+        return choose_qparams_affine(w, mapping_type, block_size, target_dtype=torch.uint8, quant_min=0, quant_max=15, eps=eps, scale_dtype=precision, zero_point_dtype=precision)
 
 
 if TORCH_VERSION_AFTER_2_3: