def conv1d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1):
 f = ConvNd(_single(stride), _single(padding), _single(dilation), False, _single(0), groups)
 return (f(input, weight, bias) if (bias is not None) else f(input, weight))

def conv1d ( input , weight , bias = None , stride = 1 , padding = 0 , dilation = 1 , groups = 1 ) : f = ConvNd ( _single ( stride ) , _single ( padding ) , _single ( dilation ) , False , _single ( 0 ) , groups ) return ( f ( input , weight , bias ) if ( bias is not None ) else f ( input , weight ) )
applies a 1d convolution over an input signal composed of several input planes .