promptbind.utils.fabind_inference_dataset.InferenceDataset

class promptbind.utils.fabind_inference_dataset.InferenceDataset(index_csv, pdb_file_dir, preprocess_dir)

__init__(index_csv, pdb_file_dir, preprocess_dir)

Methods

__init__(index_csv, pdb_file_dir, preprocess_dir)
download()	Downloads the dataset to the self.raw_dir folder.
get(idx)	Gets the data object at index idx.
get_summary()	Collects summary statistics for the dataset.
index_select(idx)	Creates a subset of the dataset from specified indices idx.
indices()
len()	Returns the number of data objects stored in the dataset.
print_summary([fmt])	Prints summary statistics of the dataset to the console.
process()	Processes the dataset to the self.processed_dir folder.
shuffle([return_perm])	Randomly shuffles the examples in the dataset.
to_datapipe()	Converts the dataset into a torch.utils.data.DataPipe.

Attributes

has_download	Checks whether the dataset defines a download() method.
has_process	Checks whether the dataset defines a process() method.
num_classes	Returns the number of classes in the dataset.
num_edge_features	Returns the number of features per edge in the dataset.
num_features	Returns the number of features per node in the dataset.
num_node_features	Returns the number of features per node in the dataset.
processed_dir
processed_file_names	The name of the files in the self.processed_dir folder that must be present in order to skip processing.
processed_paths	The absolute filepaths that must be present in order to skip processing.
raw_dir
raw_file_names	The name of the files in the self.raw_dir folder that must be present in order to skip downloading.
raw_paths	The absolute filepaths that must be present in order to skip downloading.