multiple_models

MultipleModels

Bases: torch.nn.Module

Wraps a list of models, and returns their outputs as a list of tensors

Source code in pytorch_adapt\layers\multiple_models.py

class MultipleModels(torch.nn.Module):
    """
    Wraps a list of models, and returns their outputs as a list of tensors
    """

    def __init__(self, *models: torch.nn.Module):
        """
        Arguments:
            *models: The models to be wrapped.
        """
        super().__init__()
        self.models = torch.nn.ModuleList(models)

    def forward(self, x: torch.Tensor) -> List[Any]:
        """
        Arguments:
            x: the input to each model
        Returns:
            A list containing the output of each model.
        """
        outputs = []
        for m in self.models:
            outputs.append(m(x))
        return outputs

__init__(*models)

Parameters:

Name	Type	Description	Default
*models	torch.nn.Module	The models to be wrapped.	()

Source code in pytorch_adapt\layers\multiple_models.py

def __init__(self, *models: torch.nn.Module):
    """
    Arguments:
        *models: The models to be wrapped.
    """
    super().__init__()
    self.models = torch.nn.ModuleList(models)

forward(x)

Parameters:

Name	Type	Description	Default
x	torch.Tensor	the input to each model	required

Returns:

Type	Description
List[Any]	A list containing the output of each model.

Source code in pytorch_adapt\layers\multiple_models.py

def forward(self, x: torch.Tensor) -> List[Any]:
    """
    Arguments:
        x: the input to each model
    Returns:
        A list containing the output of each model.
    """
    outputs = []
    for m in self.models:
        outputs.append(m(x))
    return outputs