unitorch.models.swin

SwinProcessor

Bases: HfImageClassificationProcessor

Initializes the SwinProcessor.

Parameters:

Name	Type	Description	Default
vision_config_path	str	Path to the ViTImageProcessor configuration file.	required

Source code in src/unitorch/models/swin/processing.py

def __init__(
    self,
    vision_config_path: str,
):
    """
    Initializes the SwinProcessor.

    Args:
        vision_config_path (str): Path to the ViTImageProcessor configuration file.
    """
    vision_processor = ViTImageProcessor.from_json_file(vision_config_path)
    super().__init__(vision_processor=vision_processor)

SwinForImageClassification

Bases: GenericModel

Initializes the SwinForImageClassification model.

Parameters:

Name	Type	Description	Default
config_path	str	Path to the Swin Transformer configuration file.	required
num_classes	int	Number of output classes. Defaults to 1.	1

Source code in src/unitorch/models/swin/modeling.py

def __init__(
    self,
    config_path: str,
    num_classes: Optional[int] = 1,
):
    """
    Initializes the SwinForImageClassification model.

    Args:
        config_path (str): Path to the Swin Transformer configuration file.
        num_classes (int, optional): Number of output classes. Defaults to 1.
    """
    super().__init__()
    config = SwinConfig.from_json_file(config_path)
    self.swin = SwinModel(config)
    self.classifier = nn.Linear(self.swin.num_features, num_classes)
    self.init_weights()

swin instance-attribute

swin = SwinModel(config)

classifier instance-attribute

classifier = Linear(num_features, num_classes)

forward

forward(pixel_values: Tensor)

Forward pass of the SwinForImageClassification model.

Parameters:

Name	Type	Description	Default
pixel_values	Tensor	Input image pixel values.	required

Returns:

Type	Description
	torch.Tensor: Classification logits.

Source code in src/unitorch/models/swin/modeling.py

def forward(
    self,
    pixel_values: torch.Tensor,
):
    """
    Forward pass of the SwinForImageClassification model.

    Args:
        pixel_values (torch.Tensor): Input image pixel values.

    Returns:
        torch.Tensor: Classification logits.
    """
    outputs = self.swin(pixel_values=pixel_values)
    pooled_output = outputs[1]
    return self.classifier(pooled_output)