Implementation of the Keras API, the high-level API of TensorFlow.
Detailed documentation and user guides are available at keras.io.
Modules
activations
module: Built-in activation functions.
applications
module: Keras Applications are canned architectures with pre-trained weights.
backend
module: Keras backend API.
callbacks
module: Callbacks: utilities called at certain points during model training.
constraints
module: Constraints: functions that impose constraints on weight values.
datasets
module: Small NumPy datasets for debugging/testing.
estimator
module: Keras estimator API.
experimental
module: Public API for tf.keras.experimental namespace.
initializers
module: Keras initializer serialization / deserialization.
layers
module: Keras layers API.
losses
module: Built-in loss functions.
metrics
module: Built-in metrics.
mixed_precision
module: Keras mixed precision API.
models
module: Code for model cloning, plus model-related API entries.
optimizers
module: Built-in optimizer classes.
preprocessing
module: Provides keras data preprocessing utils to pre-process tf.data.Datasets before they are fed to the model.
regularizers
module: Built-in regularizers.
utils
module: Public API for tf.keras.utils namespace.
wrappers
module: Public API for tf.keras.wrappers namespace.
Classes
class Model
: Model
groups layers into an object with training and inference features.
class Sequential
: Sequential
groups a linear stack of layers into a tf.keras.Model
.
Functions
Input(...)
: Input()
is used to instantiate a Keras tensor.