fix: torch frontend max/min to support dim and keepdim as arg or kwarg (

ivy-llc#28469)

ivy/functional/frontends/torch/reduction_ops.py

@@ -100,11 +100,25 @@ def logsumexp(input, dim, keepdim=False, *, out=None):
 
 @numpy_to_torch_style_args
 @to_ivy_arrays_and_back
+@with_unsupported_dtypes(
+    {"2.2 and below": ("complex64", "complex128")},
+    "torch",
+)
 def max(*input, dim=None, keepdim=False, out=None):
     if len(input) == 1:
         input = input[0]
     elif len(input) == 2:
-        return torch_frontend.maximum(*input)
+        input_0 = input[0]
+        input_1 = input[1]
+        if ivy.is_array(input_1):
+            return torch_frontend.maximum(*input)
+        else:
+            input = input_0
+            dim = input_1
+    else:
+        input = input[0]
+        dim = input[1]
+        keepdim = input[2]
     if dim is None:
         return ivy.max(input, axis=dim, keepdims=keepdim, out=out)
     elif out is not None:
@@ -173,7 +187,17 @@ def min(*input, dim=None, keepdim=False, out=None):
     if len(input) == 1:
         input = input[0]
     elif len(input) == 2:
-        return torch_frontend.minimum(*input)
+        input_0 = input[0]
+        input_1 = input[1]
+        if ivy.is_array(input_1):
+            return torch_frontend.minimum(*input)
+        else:
+            input = input_0
+            dim = input_1
+    else:
+        input = input[0]
+        dim = input[1]
+        keepdim = input[2]
     if dim is None:
         return ivy.min(input, axis=dim, keepdims=keepdim, out=out)
     elif out is not None: