ConvTranspose2d

Applies a 2D transposed convolution operator over an input image composed of several input planes. The input tensor in forward(input) is expected to be a 4D tensor (nInputPlane x height x width).

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Usage

from tinygrad.nn import ConvTranspose2d
 
BS, C1, H, W = 4, 16, 224, 224
C2, K, S, P = 64, 7, 2, 1
 
layer = ConvTranspose2d(C1, C2, K, S, P)

Arguments

in_channels

The number of channels in the input image

out_channels

The number of channels produced by the convolution

kernel_size

The size of the convolving kernel

stride (default=1)

The stride of the convolution. Can be a single number or a tuple (sH, sW). Default: 1

padding (default=0)

The padding added to the input planes

dilation (default=1)

The spacing between kernel elements. Can be a single number or a tuple (dH, dW). Default: 1

groups (default=1)

The number of blocked connections from input channels to output channels. Default: 1

bias (default=True)

The bias added to the output