tf.data.Dataset from text files in a directory.
tf.keras.preprocessing.text_dataset_from_directory( directory, labels='inferred', label_mode='int', class_names=None, batch_size=32, max_length=None, shuffle=True, seed=None, validation_split=None, subset=None, follow_links=False )
If your directory structure is:
main_directory/ ...class_a/ ......a_text_1.txt ......a_text_2.txt ...class_b/ ......b_text_1.txt ......b_text_2.txt
text_dataset_from_directory(main_directory, labels='inferred') will return a
tf.data.Dataset that yields batches of texts from the subdirectories
class_b, together with labels 0 and 1 (0 corresponding to
class_a and 1 corresponding to
.txt files are supported at this time.
| || Directory where the data is located. If |
| || Either "inferred" (labels are generated from the directory structure), 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 |
| || |
| ||Only valid if "labels" is "inferred". This is the explict list of class names (must match names of subdirectories). Used to control the order of the classes (otherwise alphanumerical order is used).|
| ||Size of the batches of data. Default: 32.|
| || Maximum size of a text string. Texts longer than this will be truncated to |
| ||Whether to shuffle the data. Default: True. If set to False, sorts the data in alphanumeric order.|
| ||Optional random seed for shuffling and transformations.|
| ||Optional float between 0 and 1, fraction of data to reserve for validation.|
| || One of "training" or "validation". Only used if |
| ||Whether to visits subdirectories pointed to by symlinks. Defaults to False.|
| A |
Rules regarding labels format:
int, the labels are an
int32tensor of shape
binary, the labels are a
float32tensor of 1s and 0s of shape
categorial, the labels are a
float32tensor of shape
(batch_size, num_classes), representing a one-hot encoding of the class index.
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.