espnet2.enh.layers.dc_crn.GluConvTranspose2d

source

class espnet2.enh.layers.dc_crn.GluConvTranspose2d(in_channels, out_channels, kernel_size, stride, padding=0, output_padding=(0, 0))

Bases: Module

ConvTranspose2d with Gated Linear Units (GLU).

Input and output shapes are the same as regular ConvTranspose2d layers.

Reference: Section III-B in [1]

• Parameters:
  • in_channels (int) – number of input channels
  • out_channels (int) – number of output channels
  • kernel_size (int/tuple) – kernel size in ConvTranspose2d
  • stride (int/tuple) – stride size in ConvTranspose2d
  • padding (int/tuple) – padding size in ConvTranspose2d
  • output_padding (int/tuple) – Additional size added to one side of each dimension in the output shape

forward(x)

DeconvGLU forward.

• Parameters:x (torch.Tensor) – (B, C_in, H_in, W_in)
• Returns: (B, C_out, H_out, W_out)
• Return type: out (torch.Tensor)