Then calling text_dataset_from_directory(main_directory,
labels='inferred') will return a tf.data.Dataset that yields batches of
texts from the subdirectories class_a and class_b, together with labels
0 and 1 (0 corresponding to class_a and 1 corresponding to class_b).
Only .txt files are supported at this time.
Args
directory
Directory where the data is located.
If labels is "inferred", it should contain
subdirectories, each containing text files for a class.
Otherwise, the directory structure is ignored.
labels
Either "inferred"
(labels are generated from the directory structure),
None (no labels),
or a list/tuple of integer labels of the same size as the number of
text files found in the directory. Labels should be sorted according
to the alphanumeric order of the text file paths
(obtained via os.walk(directory) in Python).
label_mode
String describing the encoding of labels. Options are:
"int": means that the labels are encoded as integers
(e.g. for sparse_categorical_crossentropy loss).
"categorical" means that the labels are
encoded as a categorical vector
(e.g. for categorical_crossentropy loss).
"binary" means that the labels (there can be only 2)
are encoded as float32 scalars with values 0 or 1
(e.g. for binary_crossentropy).
None (no labels).
class_names
Only valid if "labels" is "inferred".
This is the explicit list of class names
(must match names of subdirectories). Used to control the order
of the classes (otherwise alphanumerical order is used).
batch_size
Size of the batches of data. Defaults to 32.
If None, the data will not be batched
(the dataset will yield individual samples).
max_length
Maximum size of a text string. Texts longer than this will
be truncated to max_length.
shuffle
Whether to shuffle the data. Defaults to True.
If set to False, sorts the data in alphanumeric order.
seed
Optional random seed for shuffling and transformations.
validation_split
Optional float between 0 and 1,
fraction of data to reserve for validation.
subset
Subset of the data to return.
One of "training", "validation" or "both".
Only used if validation_split is set.
When subset="both", the utility returns a tuple of two datasets
(the training and validation datasets respectively).
follow_links
Whether to visits subdirectories pointed to by symlinks.
Defaults to False.
verbose
Whether to display number information on classes and
number of files found. Defaults to True.