Update model.py

Author: qubvel

segmentation_models_pytorch/manet/model.py

@@ -6,11 +6,11 @@
 
 
 class MAnet(SegmentationModel):
-    """MAnet_ :  Multi-scale Attention Net.
-       The MA-Net can capture rich contextual dependencies based on the attention mechanism, using two blocks:
-       Position-wise Attention Block (PAB, which captures the spatial dependencies between pixels in a global view)
-       and Multi-scale Fusion Attention Block (MFAB, which  captures the channel dependencies between any feature map by
-       multi-scale semantic feature fusion)
+    """MAnet_ :  Multi-scale Attention Net. The MA-Net can capture rich contextual dependencies based on the attention mechanism, 
+    using two blocks:
+     - Position-wise Attention Block (PAB), which captures the spatial dependencies between pixels in a global view
+     - Multi-scale Fusion Attention Block (MFAB), which  captures the channel dependencies between any feature map by
+       multi-scale semantic feature fusion
 
     Args:
         encoder_name: Name of the classification model that will be used as an encoder (a.k.a backbone)
@@ -52,7 +52,7 @@ def __init__(
         self,
         encoder_name: str = "resnet34",
         encoder_depth: int = 5,
-        encoder_weights: str = "imagenet",
+        encoder_weights: Optional[str] = "imagenet",
         decoder_use_batchnorm: bool = True,
         decoder_channels: List[int] = (256, 128, 64, 32, 16),
         decoder_pab_channels: int = 64,