merge conflict #11

Author: Sebastien M. Popoff

complexPyTorch/complexFunctions.py

@@ -40,6 +40,12 @@ def complex_normalize(input):
 def complex_relu(input):
     return relu(input.real).type(torch.complex64)+1j*relu(input.imag).type(torch.complex64)
 
+<<<<<<< HEAD
+=======
+def complex_relu(input):
+    return relu(input.real).type(torch.complex64)+1j*relu(input.imag).type(torch.complex64)
+
+>>>>>>> octaveguinebretiere-master
 def complex_sigmoid(input):
     return sigmoid(input.real).type(torch.complex64)+1j*sigmoid(input.imag).type(torch.complex64)
 

complexPyTorch/complexLayers.py

@@ -13,8 +13,21 @@
 from torch.nn import Module, Parameter, init
 from torch.nn import Conv2d, Linear, BatchNorm1d, BatchNorm2d
 from torch.nn import ConvTranspose2d
+<<<<<<< HEAD:complexPyTorch/complexLayers.py
 from .complexFunctions import complex_relu, complex_max_pool2d, complex_avg_pool2d
 from .complexFunctions import complex_dropout, complex_dropout2d
+=======
+from complexFunctions import ( 
+    complex_relu,
+    complex_tanh,
+    complex_sigmoid,
+    complex_max_pool2d,
+    complex_avg_pool2d,
+    complex_dropout,
+    complex_dropout2d,
+    complex_opposite,
+)
+>>>>>>> d00e50c5d93386dd85b363a39c24cf783b7914aa:complexLayers.py
 
 def apply_complex(fr, fi, input, dtype = torch.complex64):
     return (fr(input.real)-fi(input.imag)).type(dtype) \