TensorFlow Keras Models

compile(optimizer                ,
        loss               = None,
        metrics            = None,
        loss_weights       = None,
        sample_weight_mode = None,
        weighted_metrics   = None,
        target_tensors     = None)

fit(x                = None,
    y                = None,
    batch_size       = None,
    epochs           = 1   ,
    verbose          = 1   ,
    callbacks        = None,
    validation_split = 0.0 ,
    validation_data  = None,
    shuffle          = True,
    class_weight     = None,
    sample_weight    = None,
    initial_epoch    = 0   ,
    steps_per_epoch  = None,
    validation_steps = None)

evaluate(x             = None,
         y             = None,
         batch_size    = None,
         verbose       = 1   ,
         sample_weight = None,
         steps         = None)

predict(x,
        batch_size = None,
        verbose    = 0   ,
        steps      = None)

train_on_batch(x, y, sample_weight=None, class_weight=None)
test_on_batch (x, y, sample_weight=None)
predict_on_batch(x)

fit_generator(generator                  ,
              steps_per_epoch     = None ,
              epochs              = 1    ,
              verbose             = 1    ,
              callbacks           = None ,
              validation_data     = None ,
              validation_steps    = None ,
              class_weight        = None ,
              max_queue_size      = 10   ,
              workers             = 1    ,
              use_multiprocessing = False,
              shuffle             = True ,
              initial_epoch       = 0    )

evaluate_generator(generator                  ,
                   steps               = None ,
                   max_queue_size      = 10   ,
                   workers             = 1    ,
                   use_multiprocessing = False,
                   verbose             = 0    )

predict_generator(generator                  ,
                  steps               = None ,
                  max_queue_size      = 10   ,
                  workers             = 1    ,
                  use_multiprocessing = False,
                  verbose             = 0    )

get_layer(name=None, index=None)

Reference: keras.io