fix: Fixed the API for torch.std and torch.std_mean

ivy/functional/frontends/torch/reduction_ops.py

@@ -335,16 +335,18 @@ def quantile(input, q, dim=None, keepdim=False, *, interpolation="linear", out=N
 @numpy_to_torch_style_args
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"2.2 and below": ("float16", "bool", "integer")}, "torch")
-def std(input, dim=None, unbiased=True, keepdim=False, *, out=None):
-    return ivy.std(input, axis=dim, correction=int(unbiased), keepdims=keepdim, out=out)
+def std(input, dim=None, *, correction=1, keepdim=False, out=None):
+    return ivy.std(
+        input, axis=dim, correction=int(correction), keepdims=keepdim, out=out
+    )
 
 
 @numpy_to_torch_style_args
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"2.2 and below": ("bfloat16",)}, "torch")
-def std_mean(input, dim, unbiased, keepdim=False, *, out=None):
+def std_mean(input, dim, *, correction=1, keepdim=False, out=None):
     temp_std = ivy.std(
-        input, axis=dim, correction=int(unbiased), keepdims=keepdim, out=out
+        input, axis=dim, correction=int(correction), keepdims=keepdim, out=out
     )
     temp_mean = ivy.mean(input, axis=dim, keepdims=keepdim, out=out)
     return temp_std, temp_mean