analogvnn.nn.normalize.Clamp#

Module Contents#

Classes#

Clamp

Implements the clamp normalization function with range [-1, 1].

Clamp01

Implements the clamp normalization function with range [0, 1].

class analogvnn.nn.normalize.Clamp.Clamp[source]#

Bases: analogvnn.nn.normalize.Normalize.Normalize, analogvnn.backward.BackwardIdentity.BackwardIdentity

Implements the clamp normalization function with range [-1, 1].

static forward(x: torch.Tensor)[source]#

Forward pass of the clamp normalization function with range [-1, 1].

Parameters:

x (Tensor) – the input tensor.

Returns:

the output tensor.

Return type:

Tensor

backward(grad_output: Optional[torch.Tensor]) Optional[torch.Tensor][source]#

Backward pass of the clamp normalization function with range [-1, 1].

Parameters:

grad_output (Optional[Tensor]) – the gradient of the output tensor.

Returns:

the gradient of the input tensor.

Return type:

Optional[Tensor]

class analogvnn.nn.normalize.Clamp.Clamp01[source]#

Bases: analogvnn.nn.normalize.Normalize.Normalize, analogvnn.backward.BackwardIdentity.BackwardIdentity

Implements the clamp normalization function with range [0, 1].

static forward(x: torch.Tensor)[source]#

Forward pass of the clamp normalization function with range [0, 1].

Parameters:

x (Tensor) – the input tensor.

Returns:

the output tensor.

Return type:

Tensor

backward(grad_output: Optional[torch.Tensor]) Optional[torch.Tensor][source]#

Backward pass of the clamp normalization function with range [0, 1].

Parameters:

grad_output (Optional[Tensor]) – the gradient of the output tensor.

Returns:

the gradient of the input tensor.

Return type:

Optional[Tensor]