fix: torch frontend max pooling to support optional batch dim (ivy-ll…

…c#28490)

ivy/functional/frontends/torch/nn/functional/pooling_functions.py

@@ -237,7 +237,13 @@ def max_pool1d(
         stride = kernel_size
     if not isinstance(padding, int):
         padding = [(pad, pad) for pad in padding]
-    return ivy.max_pool1d(
+    if input.ndim == 2:
+        without_batch_dim = True
+        input = ivy.expand_dims(input, axis=0)
+    else:
+        without_batch_dim = False
+
+    ret = ivy.max_pool1d(
         input,
         kernel_size,
         stride,
@@ -246,6 +252,9 @@ def max_pool1d(
         dilation=dilation,
         ceil_mode=ceil_mode,
     )
+    if without_batch_dim:
+        ret = ret[0]
+    return ret
 
 
 @with_unsupported_dtypes({"2.2 and below": ("float16",)}, "torch")
@@ -263,7 +272,13 @@ def max_pool2d(
         stride = kernel_size
     if not isinstance(padding, int):
         padding = [(pad, pad) for pad in padding]
-    return ivy.max_pool2d(
+    if input.ndim == 3:
+        without_batch_dim = True
+        input = ivy.expand_dims(input, axis=0)
+    else:
+        without_batch_dim = False
+
+    ret = ivy.max_pool2d(
         input,
         kernel_size,
         stride,
@@ -272,6 +287,9 @@ def max_pool2d(
         dilation=dilation,
         ceil_mode=ceil_mode,
     )
+    if without_batch_dim:
+        ret = ret[0]
+    return ret
 
 
 @with_unsupported_dtypes({"2.2 and below": ("float16",)}, "torch")
@@ -306,5 +324,4 @@ def max_pool3d(
     )
     if without_batch_dim:
         ret = ret[0]
-
     return ret