nip.image_classification.pretrained_models.PretrainedImageModel

nip.image_classification.pretrained_models.PretrainedImageModel#

class nip.image_classification.pretrained_models.PretrainedImageModel(hyper_params: HyperParameters, settings: ExperimentSettings)[source]#

Base class for pretrained image models.

Methods Summary

__init__(hyper_params, settings)

generate_dataset_embeddings(datasets[, ...])

Load the model and generate embeddings for the datasets.

Attributes

allow_other_datasets

embedding_width

embedding_height

name

dataset

Methods

__init__(hyper_params: HyperParameters, settings: ExperimentSettings)[source]#
abstract generate_dataset_embeddings(datasets: Iterable[TensorDictDataset], delete_model: bool = True) Tensor[source]#

Load the model and generate embeddings for the datasets.

Parameters:
  • datasets (Iterable[TensorDictDataset]) – The datasets to generate embeddings for

  • delete_model (bool, default=True) – Whether to delete the model after generating embeddings

Returns:

embeddings (torch.Tensor) – The embeddings for the datasets