# Aggregation Functions¶

`condensa.functional.``l2norm`(tensor, dim, keepdim)

Computes the l2-norm of elements in input tensor.

Parameters
• tensor (torch.nn.Module) – PyTorch tensor.

• dim (int) – Reduction dimension.

• keepdim (bool) – Whether the output has dim retained.

Returns

l2-norm of input tensor.

`condensa.functional.``max`(tensor, dim, keepdim)

Computes the maximum value of elements in input tensor.

Parameters
• tensor (torch.nn.Module) – PyTorch tensor.

• dim (int) – Reduction dimension.

• keepdim (bool) – Whether the output has dim retained.

Returns

Max of input tensor.

`condensa.functional.``mean`(tensor, dim, keepdim)

Computes the mean value of elements in input tensor.

Parameters
• tensor (torch.nn.Module) – PyTorch tensor.

• dim (int) – Reduction dimension.

• keepdim (bool) – Whether the output has dim retained.

Returns

Mean value of input tensor.

`condensa.functional.``min`(tensor, dim, keepdim)

Computes the minimum value of elements in input tensor.

Parameters
• tensor (torch.nn.Module) – PyTorch tensor.

• dim (int) – Reduction dimension.

• keepdim (bool) – Whether the output has dim retained.

Returns

Min of input tensor.

`condensa.functional.``sum`(tensor, dim, keepdim)

Computes the sum of elements in input tensor.

Parameters
• tensor (torch.nn.Module) – PyTorch tensor.

• dim (int) – Reduction dimension.

• keepdim (bool) – Whether the output has dim retained.

Returns

Sum of input tensor.