Call NoneType object! #539

Author: Hananel-Hazan

bindsnet/datasets/spoken_mnist.py

@@ -250,7 +250,7 @@ def process_data(
             # Fast Fourier Transform and Power Spectrum
             NFFT = 512
             mag_frames = np.absolute(np.fft.rfft(frames, NFFT))  # Magnitude of the FFT
-            pow_frames = (1.0 / NFFT) * (mag_frames ** 2)  # Power Spectrum
+            pow_frames = (1.0 / NFFT) * (mag_frames**2)  # Power Spectrum
 
             # Log filter banks
             nfilt = 40

bindsnet/network/nodes.py

@@ -1212,8 +1212,8 @@ def __init__(
             self.r = torch.rand(n)
             self.a = 0.02 * torch.ones(n)
             self.b = 0.2 * torch.ones(n)
-            self.c = -65.0 + 15 * (self.r ** 2)
-            self.d = 8 - 6 * (self.r ** 2)
+            self.c = -65.0 + 15 * (self.r**2)
+            self.d = 8 - 6 * (self.r**2)
             self.S = 0.5 * torch.rand(n, n)
             self.excitatory = torch.ones(n).byte()
 
@@ -1282,8 +1282,8 @@ def forward(self, x: torch.Tensor) -> None:
             )
 
         # Apply v and u updates.
-        self.v += self.dt * 0.5 * (0.04 * self.v ** 2 + 5 * self.v + 140 - self.u + x)
-        self.v += self.dt * 0.5 * (0.04 * self.v ** 2 + 5 * self.v + 140 - self.u + x)
+        self.v += self.dt * 0.5 * (0.04 * self.v**2 + 5 * self.v + 140 - self.u + x)
+        self.v += self.dt * 0.5 * (0.04 * self.v**2 + 5 * self.v + 140 - self.u + x)
         self.u += self.dt * self.a * (self.b * self.v - self.u)
 
         # Voltage clipping to lower bound.
@@ -1518,7 +1518,7 @@ def set_batch_size(self, batch_size) -> None:
 
     def AlphaKernel(self, dt):
         t = torch.arange(0, self.res_window_size, dt)
-        kernelVec = (1 / (self.tau ** 2)) * t * torch.exp(-t / self.tau)
+        kernelVec = (1 / (self.tau**2)) * t * torch.exp(-t / self.tau)
         return torch.flip(kernelVec, [0])
 
     def AlphaKernelSLAYER(self, dt):

examples/mnist/conv3d_MNIST.py

@@ -94,7 +94,7 @@
     kernel_size=kernel_size,
     stride=stride,
     update_rule=PostPre,
-    norm=0.4 * kernel_size ** 3,
+    norm=0.4 * kernel_size**3,
     nu=[1e-4, 1e-2],
     wmax=1.0,
 )

examples/mnist/conv_mnist.py

@@ -98,7 +98,7 @@
     kernel_size=kernel_size,
     stride=stride,
     update_rule=PostPre,
-    norm=0.4 * kernel_size ** 2,
+    norm=0.4 * kernel_size**2,
     nu=[1e-4, 1e-2],
     wmax=1.0,
 )

examples/tensorboard/tensorboard.py

@@ -87,7 +87,7 @@
     kernel_size=kernel_size,
     stride=stride,
     update_rule=PostPre,
-    norm=0.4 * kernel_size ** 2,
+    norm=0.4 * kernel_size**2,
     nu=[1e-4, 1e-2],
     wmax=1.0,
 )