fix doc of ops.misc.MLP (#7041)

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

torchvision/ops/misc.py

@@ -266,8 +266,8 @@ class MLP(torch.nn.Sequential):
     Args:
         in_channels (int): Number of channels of the input
         hidden_channels (List[int]): List of the hidden channel dimensions
-        norm_layer (Callable[..., torch.nn.Module], optional): Norm layer that will be stacked on top of the convolution layer. If ``None`` this layer wont be used. Default: ``None``
-        activation_layer (Callable[..., torch.nn.Module], optional): Activation function which will be stacked on top of the normalization layer (if not None), otherwise on top of the conv layer. If ``None`` this layer wont be used. Default: ``torch.nn.ReLU``
+        norm_layer (Callable[..., torch.nn.Module], optional): Norm layer that will be stacked on top of the linear layer. If ``None`` this layer wont be used. Default: ``None``
+        activation_layer (Callable[..., torch.nn.Module], optional): Activation function which will be stacked on top of the normalization layer (if not None), otherwise on top of the linear layer. If ``None`` this layer wont be used. Default: ``torch.nn.ReLU``
         inplace (bool): Parameter for the activation layer, which can optionally do the operation in-place. Default ``True``
         bias (bool): Whether to use bias in the linear layer. Default ``True``
         dropout (float): The probability for the dropout layer. Default: 0.0