dropout=kwarg

app.py

@@ -210,7 +210,7 @@ def predict_and_analyze(model_name, num_channels, dim, input_channel, image):
         
         
         config = EfficientNetConfig(
-                                    hparams.dropout,
+                                    dropout=hparams.dropout,
                                     num_channels=hparams.num_channels,
                                     num_classes=hparams.num_classes,
                                     size=hparams.size,

model_utils/efficientnet_config.py

@@ -247,7 +247,7 @@ class EfficientNetConfig(PretrainedConfig):
     def __init__(
         self,
         # inverted_residual_setting: Sequence[Union[MBConvConfig, FusedMBConvConfig]],
-        dropout: float,
+        dropout: float=0.25,
         num_channels: int = 61,
         stochastic_depth_prob: float = 0.2,
         num_classes: int = 2,
@@ -272,7 +272,7 @@ class EfficientNetConfig(PretrainedConfig):
         
         
         self.model = EfficientNet(
-                                    dropout,
+                                    dropout=dropout,
                                     num_channels=num_channels,
                                     num_classes=num_classes,
                                     size=size,
@@ -409,7 +409,7 @@ class EfficientNet(nn.Module):
     def __init__(
         self,
         # inverted_residual_setting: Sequence[Union[MBConvConfig, FusedMBConvConfig]],
-        dropout: float,
+        dropout: float=0.25,
         num_channels: int = 61,
         stochastic_depth_prob: float = 0.2,
         num_classes: int = 2,