Update on "[docs][ao] Add missing documentation for torch.quantized_b…

…atch_norm"

Summary:
Op is exposed via torch.quantized_batch_norm to the end user without any existing documentation

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CI
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Differential Revision: [D30316431](https://our.internmc.facebook.com/intern/diff/D30316431)

[ghstack-poisoned]

torch/_torch_docs.py

@@ -11237,10 +11237,10 @@ def merge_dicts(*dicts):
 
 Arguments:
     input (Tensor): quantized tensor
-    weight (Tensor): tensor that corresponds to the gamma, size C
-    bias (Tensor):  tensor that corresponds to the beta, size C
-    mean (Tensor): mean value in batch normalization, size C
-    var (Tensor): variance value, size C
+    weight (Tensor): float tensor that corresponds to the gamma, size C
+    bias (Tensor):  float tensor that corresponds to the beta, size C
+    mean (Tensor): float mean value in batch normalization, size C
+    var (Tensor): float tensor for variance, size C
     eps (float): a value added to the denominator for numerical stability.
     output_scale (float): output quantized tensor scale
     output_zero_point (int): output quantized tensor zero_point