regression v 1.0.0.003

data analysis/analysis/analysis.py

@@ -619,10 +619,12 @@ class Regression:
     #   this module is cuda-optimized and vectorized (except for one small part)
     # setup:
 
-    __version__ = "1.0.0.002"
+    __version__ = "1.0.0.003"
 
     # changelog should be viewed using print(analysis.regression.__changelog__)
     __changelog__ = """
+    1.0.0.003:
+        - bug fixes
     1.0.0.002:
         -Added more parameters to log, exponential, polynomial
         -Added SigmoidalRegKernelArthur, because Arthur apparently needs
@@ -653,12 +655,13 @@ class Regression:
         'CustomTrain'
     ]
 
+    global device
+
     device = "cuda:0" if torch.torch.cuda.is_available() else "cpu"
 
     #todo: document completely
 
     def set_device(self, new_device):
-        global device
         device=new_device
 
     class LinearRegKernel():
@@ -777,7 +780,7 @@ class Regression:
             long_bias=self.bias.repeat([1,mtx.size()[1]])
             return torch.matmul(self.weights,new_mtx)+long_bias
 
-    def SGDTrain(kernel, data, ground, loss=torch.nn.MSELoss(), iterations=1000, learning_rate=.1, return_losses=False):
+    def SGDTrain(self, kernel, data, ground, loss=torch.nn.MSELoss(), iterations=1000, learning_rate=.1, return_losses=False):
         optim=torch.optim.SGD(kernel.parameters, lr=learning_rate)
         data_cuda=data.to(device)
         ground_cuda=ground.to(device)