mlx.nn.Conv2d#
- class Conv2d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, dilation: int | tuple = 1, bias: bool = True)#
Applies a 2-dimensional convolution over the multi-channel input image.
- The channels are expected to be last i.e. the input shape should be
NHWC
where: N
is the batch dimensionH
is the input image heightW
is the input image widthC
is the number of input channels
- Parameters:
in_channels (int) – The number of input channels.
out_channels (int) – The number of output channels.
kernel_size (int or tuple) – The size of the convolution filters.
stride (int or tuple, optional) – The size of the stride when applying the filter. Default: 1.
padding (int or tuple, optional) – How many positions to 0-pad the input with. Default: 0.
dilation (int or tuple, optional) – The dilation of the convolution.
bias (bool, optional) – If
True
add a learnable bias to the output. Default:True
Methods
- The channels are expected to be last i.e. the input shape should be