fix: reference first element for first dropout

Signed-off-by: Saurav Maheshkar <[email protected]>

monai/networks/nets/vnet.py

@@ -133,7 +133,7 @@ def __init__(
         out_channels: int,
         nconvs: int,
         act: tuple[str, dict] | str,
-        dropout_prob: tuple[float, float] | None = [None, 0.5],
+        dropout_prob: tuple[float | None, float] = [None, 0.5],  # noqa: B006
         dropout_dim: int = 3,
     ):
         super().__init__()
@@ -144,14 +144,14 @@ def __init__(
 
         self.up_conv = conv_trans_type(in_channels, out_channels // 2, kernel_size=2, stride=2)
         self.bn1 = norm_type(out_channels // 2)
-        self.dropout = dropout_type(dropout_prob[0]) if dropout_prob is not None else None
+        self.dropout = dropout_type(dropout_prob[0]) if dropout_prob[0] is not None else None
         self.dropout2 = dropout_type(dropout_prob[1])
         self.act_function1 = get_acti_layer(act, out_channels // 2)
         self.act_function2 = get_acti_layer(act, out_channels)
         self.ops = _make_nconv(spatial_dims, out_channels, nconvs, act)
 
     def forward(self, x, skipx):
-        if self.dropout is not None:
+        if self.dropout[0] is not None:
             out = self.dropout(x)
         else:
             out = x
@@ -225,7 +225,7 @@ def __init__(
         out_channels: int = 1,
         act: tuple[str, dict] | str = ("elu", {"inplace": True}),
         dropout_prob_down: float = 0.5,
-        dropout_prob_up: tuple[float, float] = [0.5, 0.5],
+        dropout_prob_up: tuple[float, float] = [0.5, 0.5],  # noqa: B006
         dropout_dim: int = 3,
         bias: bool = False,
     ):