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Clotho data handling

Welcome to Clotho data handling repository. This repository has the necessary code for using the DataLoader class from PyTorch package (torch.utils.data.dataloader.DataLoader) with the Clotho dataset.

You can use the present data loader of Clotho directly with the examples created by the Clotho baseline dataset repository.

If you are looking at this README file, then I suppose that you already know what is a DataLoader from PyTorch. Nevertheless, the Clotho dataset has sequences as inputs and outputs, and each sequence is of arbitrary length (15 to 30 seconds for the input and 8 to 20 words for the output). For that reason, this data loader already provides a collate function.

This repository is maintained by K. Drossos.

Clotho dataset class

In the data_handling package, there is the clotho_dataset.py, which holds the ClothoDataset class. This class offers the functionality of a PyTorch dataset object, tuned for the Clotho dataset.

The ClothoDataset object needs the following arguments:

• data_dir which is the directory that has the data of the Clotho dataset (i.e. the root directory of the Clotho dataset). This argument should be of type pathlib.Path.

• spilt which is the split that you want to use, and the argument should be of type str.

• input_field_name which is the field name of the numpy.recarray that holds the input data to your audio captioning method. Currently, only single input fields are supported (i.e. you cannot specify multiple fields). The type of this argument should be str.

• output_field_name is the ield name of the numpy.recarray that holds the output data to your audio captioning method. Currently, only single output fields are supported (i.e. you cannot specify multiple fields). The type of this argument should be str.

• load_into_memory which is a bool flag for indicating if the data in the dataset should be loaded into memory or read from the disk when needed.

Clotho data loader

The data loader is just a function, wrapping the creation of a torch.utils.data.DataLoader class, that also offers functionality for instantiating the ClothoDataset class and the collate function, that will be used with the data loader.

The data loader of Clotho needs the following arguments:

• data_dir which is the directory that has the data of the Clotho dataset (i.e. the root directory of the Clotho dataset). This argument should be of type pathlib.Path.
• spilt which is the split that you want to use, and the argument should be of type str.
• input_field_name which is the field name of the numpy.recarray that holds the input data to your audio captioning method. Currently, only single input fields are supported (i.e. you cannot specify multiple fields). The type of this argument should be str.
• output_field_name is the ield name of the numpy.recarray that holds the output data to your audio captioning method. Currently, only single output fields are supported (i.e. you cannot specify multiple fields). The type of this argument should be str.
• load_into_memory which is a bool flag for indicating if the data in the dataset should be loaded into memory or read from the disk when needed.
• batch_size is the batch size to be used with the data loader. This argument should be an int.
• nb_t_steps_pad is the number of time-steps to pad or truncate the sequences using the collate function. This argument can be an int (i.e. the actual time-steps) but also can be the strings max or min, meaning pad/truncate to maximum/minimum amount of time-steps in the batch. Currently, zeros (input audio) and <EOF> tokens (output words) are supported for padding.
  the padding. Supported values for str are max and min.
• shuffle flag to indicate the shuffling of the data, exactly as in the torch.utils.data.DataLoader class. This argument should be a bool.
• drop_last flag to indicate the dropping of the examples that cannot grouped in a batch,
  exactly as in the torch.utils.data.DataLoader class. This argument should be a bool.
• input_pad_at where to pad the input sequence at, i.e. at the start or at the end? This argument should be a str and supported strings are start and end.
• output_pad_at the same as input_pad_at, but for the output sequence.
• num_workers is the amount of workers to be used for the data loader, exactly as in the torch.utils.data.DataLoader class. This argument should be an int.

Collate function

To be able to use the sequences of Clotho in a batch, you most likely will need some kind of padding policy. This repository already offers a collate function to be used with the Clotho data.

With the provided collate function, you can choose to either:

• pad the data with zeros (for input audio data) and end-of-sequence symbol (for the output/words), to the length of the longest input (for the inputs) and output (for the outputs) sequence in tha batch
• truncate the input and the output to the minimum length of the input and output in the batch, and
• use a constant length for input and output, and either truncate or pad.

Enjoy and if you have any issues, please let me know in the issue section.