pytagi.nn.convtranspose2d#
Classes#
Applies a 2D transposed convolution operation (also known as deconvolution). |
Module Contents#
- class pytagi.nn.convtranspose2d.ConvTranspose2d(in_channels: int, out_channels: int, kernel_size: int, bias: bool = True, stride: int = 1, padding: int = 0, padding_type: int = 1, in_width: int = 0, in_height: int = 0, gain_weight: float = 1.0, gain_bias: float = 1.0, init_method: str = 'He')[source]#
Bases:
pytagi.nn.base_layer.BaseLayer
Applies a 2D transposed convolution operation (also known as deconvolution).
This layer performs a transposed convolution, which is used in tasks like image generation or segmentation to upsample feature maps. It reverses the convolution operation, increasing the spatial dimensions of the input.
- Parameters:
in_channels (int) – Number of input channels.
out_channels (int) – Number of output channels.
kernel_size (int) – Size of the convolutional kernel.
bias (bool) – Whether to include a learnable bias term. Defaults to True.
stride (int) – The step size of the kernel. Defaults to 1.
padding (int) – Amount of zero-padding added to the input. Defaults to 0.
padding_type (int) – Type of padding. Defaults to 1 (likely ‘zeros’ or similar).
in_width (int) – Input width. If 0, it might be inferred or set by the backend. Defaults to 0.
in_height (int) – Input height. If 0, it might be inferred or set by the backend. Defaults to 0.
gain_weight (float) – Initial value for the gain (scale) parameter of weights. Defaults to 1.0.
gain_bias (float) – Initial value for the gain (scale) parameter of biases. Defaults to 1.0.
init_method (str) – Method used for initializing weights. Defaults to “He”.
Initializes the ConvTranspose2d layer.
- get_layer_info() str [source]#
Retrieves detailed information about the ConvTranspose2d layer.
- Returns:
A string containing the layer’s information.
- Return type:
str