# tensorplay.nn.functional.conv2d

Source: https://www.tensorplay.cn/docs/generated/tensorplay.nn.functional.conv2d.html

# tensorplay.nn.functional.conv2d

tensorplay.nn.functional.conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1)[[source]](../_modules/tensorplay/nn/functional.html#conv2d)

Applies a 2D convolution over an input image composed of several input planes.

See Conv2d for details and output shape.

Parameters:

- input – input tensor of shape \((\text{minibatch} , \text{in\_channels} , iH , iW)\)

- weight – filters of shape \((\text{out\_channels} , \frac{\text{in\_channels}}{\text{groups}} , kH , kW)\)

- bias – optional bias tensor of shape \((\text{out\_channels})\) . Default: None

- stride – the stride of the convolving kernel. Can be a single number or a tuple (sH, sW) . Default: 1

- padding – implicit paddings on both sides of the input. Can be a single number or a tuple (padH, padW) . Default: 0

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

- groups – split input into groups, both \(\text{in\_channels}\) and \(\text{out\_channels}\) should be divisible by the number of groups. Default: 1

Examples:

```
>>> # With square kernels and equal stride
>>> filters = tp.randn(8, 4, 3, 3)
>>> inputs = tp.randn(1, 4, 5, 5)
>>> F.conv2d(inputs, filters, padding=1)
```