cleanup sequential sequence module

performer_pytorch/reversible.py

@@ -123,22 +123,17 @@ def backward(ctx, dy):
             y, dy = block.backward_pass(y, dy, **kwargs)
         return dy, None, None
 
-
 class SequentialSequence(nn.Module):
-    def __init__(self, layers, args_route = {}, layer_dropout = 0.):
+    def __init__(self, layers, args_route = {}):
         super().__init__()
         assert all(len(route) == len(layers) for route in args_route.values()), 'each argument route map must have the same depth as the number of sequential layers'
         self.layers = layers
         self.args_route = args_route
-        self.layer_dropout = layer_dropout
 
     def forward(self, x, **kwargs):
         args = route_args(self.args_route, kwargs, len(self.layers))
         layers_and_args = list(zip(self.layers, args))
 
-        if self.training and self.layer_dropout > 0:
-            layers_and_args = layer_drop(layers_and_args, self.layer_dropout)
-
         for (f, g), (f_args, g_args) in layers_and_args:
             x = x + f(x, **f_args)
             x = x + g(x, **g_args)

setup.py

@@ -3,7 +3,7 @@
 setup(
   name = 'performer-pytorch',
   packages = find_packages(exclude=['examples']),
-  version = '0.7.0',
+  version = '0.7.1',
   license='MIT',
   description = 'Performer - Pytorch',
   author = 'Phil Wang',