DO NOT EDIT.
This file was autogenerated. Do not edit it by hand, since your modifications would be overwritten.
Modules
legacy module: DO NOT EDIT.
Classes
class CustomObjectScope: Exposes custom classes/functions to Keras deserialization internals.
class FeatureSpace: One-stop utility for preprocessing and encoding structured data.
class Progbar: Displays a progress bar.
class PyDataset: Base class for defining a parallel dataset using Python code.
class Sequence: Base class for defining a parallel dataset using Python code.
class custom_object_scope: Exposes custom classes/functions to Keras deserialization internals.
Functions
array_to_img(...): Converts a 3D NumPy array to a PIL Image instance.
audio_dataset_from_directory(...): Generates a tf.data.Dataset from audio files in a directory.
clear_session(...): Resets all state generated by Keras.
deserialize_keras_object(...): Retrieve the object by deserializing the config dict.
disable_interactive_logging(...): Turn off interactive logging.
enable_interactive_logging(...): Turn on interactive logging.
get_custom_objects(...): Retrieves a live reference to the global dictionary of custom objects.
get_file(...): Downloads a file from a URL if it not already in the cache.
get_registered_name(...): Returns the name registered to an object within the Keras framework.
get_registered_object(...): Returns the class associated with name if it is registered with Keras.
get_source_inputs(...): Returns the list of input tensors necessary to compute tensor.
image_dataset_from_directory(...): Generates a tf.data.Dataset from image files in a directory.
img_to_array(...): Converts a PIL Image instance to a NumPy array.
is_interactive_logging_enabled(...): Check if interactive logging is enabled.
is_keras_tensor(...): Returns whether x is a Keras tensor.
load_img(...): Loads an image into PIL format.
model_to_dot(...): Convert a Keras model to dot format.
normalize(...): Normalizes an array.
pack_x_y_sample_weight(...): Packs user-provided data into a tuple.
pad_sequences(...): Pads sequences to the same length.
plot_model(...): Converts a Keras model to dot format and save to a file.
register_keras_serializable(...): Registers an object with the Keras serialization framework.
save_img(...): Saves an image stored as a NumPy array to a path or file object.
serialize_keras_object(...): Retrieve the config dict by serializing the Keras object.
set_random_seed(...): Sets all random seeds (Python, NumPy, and backend framework, e.g. TF).
split_dataset(...): Splits a dataset into a left half and a right half (e.g. train / test).
text_dataset_from_directory(...): Generates a tf.data.Dataset from text files in a directory.
timeseries_dataset_from_array(...): Creates a dataset of sliding windows over a timeseries provided as array.
to_categorical(...): Converts a class vector (integers) to binary class matrix.
unpack_x_y_sample_weight(...): Unpacks user-provided data tuple.