add complex-cat
This commit is contained in:
parent
60fc4607d0
commit
d7f3847917
|
|
@ -7,7 +7,7 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
self,
|
||||
num_features: int,
|
||||
eps: float = 1e-5,
|
||||
momentum: bool = True,
|
||||
momentum: float = 0.1,
|
||||
affine: bool = True,
|
||||
track_running_stats: bool = True,
|
||||
):
|
||||
|
|
@ -25,12 +25,11 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
self.eps = eps
|
||||
|
||||
if self.affine:
|
||||
values = torch.Tensor(self.num_features)
|
||||
self.Wrr = nn.parameter.Parameter(values)
|
||||
self.Wri = nn.parameter.Parameter(values)
|
||||
self.Wii = nn.parameter.Parameter(values)
|
||||
self.Br = nn.parameter.Parameter(values)
|
||||
self.Bi = nn.parameter.Parameter(values)
|
||||
self.Wrr = nn.parameter.Parameter(torch.Tensor(self.num_features))
|
||||
self.Wri = nn.parameter.Parameter(torch.Tensor(self.num_features))
|
||||
self.Wii = nn.parameter.Parameter(torch.Tensor(self.num_features))
|
||||
self.Br = nn.parameter.Parameter(torch.Tensor(self.num_features))
|
||||
self.Bi = nn.parameter.Parameter(torch.Tensor(self.num_features))
|
||||
else:
|
||||
self.register_parameter("Wrr", None)
|
||||
self.register_parameter("Wri", None)
|
||||
|
|
@ -39,7 +38,7 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
self.register_parameter("Bi", None)
|
||||
|
||||
if self.track_running_stats:
|
||||
values = torch.Tensor(self.num_features)
|
||||
values = torch.zeros(self.num_features)
|
||||
self.register_buffer("Mean_real", values)
|
||||
self.register_buffer("Mean_imag", values)
|
||||
self.register_buffer("Var_rr", values)
|
||||
|
|
@ -111,8 +110,8 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
batch_mean_real = self.Mean_real.view(vdim)
|
||||
batch_mean_imag = self.Mean_imag.view(vdim)
|
||||
|
||||
real -= batch_mean_real
|
||||
imag -= batch_mean_imag
|
||||
real = real - batch_mean_real
|
||||
imag = imag - batch_mean_imag
|
||||
|
||||
if training:
|
||||
batch_var_rr = real * real
|
||||
|
|
@ -141,7 +140,7 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
s = batch_var_rr * batch_var_ii - batch_var_ri * batch_var_ri
|
||||
t = (tau + 2 * s).sqrt()
|
||||
|
||||
rst = 1 / (s * t)
|
||||
rst = (s * t).reciprocal()
|
||||
Urr = (batch_var_ii + s) * rst
|
||||
Uri = -batch_var_ri * rst
|
||||
Uii = (batch_var_rr + s) * rst
|
||||
|
|
@ -162,6 +161,10 @@ class ComplexBatchNorm2D(nn.Module):
|
|||
yr = (Zrr * real) + (Zri * imag)
|
||||
yi = (Zir * real) + (Zii * imag)
|
||||
|
||||
if self.affine:
|
||||
yr = yr + self.Br.view(vdim)
|
||||
yi = yi + self.Bi.view(vdim)
|
||||
|
||||
outputs = torch.cat([yr, yi], 1)
|
||||
return outputs
|
||||
|
||||
|
|
@ -178,3 +181,15 @@ class ComplexRelu(nn.Module):
|
|||
real = self.real_relu(real)
|
||||
imag = self.imag_relu(imag)
|
||||
return torch.cat([real, imag], dim=1)
|
||||
|
||||
|
||||
def complex_cat(inputs, axis=1):
|
||||
|
||||
real, imag = [], []
|
||||
for data in inputs:
|
||||
real_data, imag_data = torch.chunk(data, 2, axis)
|
||||
real.append(real_data)
|
||||
imag.append(imag_data)
|
||||
real = torch.cat(real, axis)
|
||||
imag = torch.cat(imag, axis)
|
||||
return torch.cat([real, imag], axis)
|
||||
|
|
|
|||
Loading…
Reference in New Issue