Model(Container)

fit 
evaluate
predict
train on batch # fit generator calls this func
test_on_batch
predict_on_batch
evaluate_generator
predict_generator

Container

class Container(Layer):
    """A Container is a directed acyclic graph of layers.

    It is the topological form of a "model". A Model
    is
 
 simply a Container with added training routines.

    # Properties
        name
        inputs
        outputs
        input_layers
        output_layers
        input_spec (list of class instances)
            each entry describes one required input:
                - ndim
                - dtype
        trainable (boolean)
        input_shape
        output_shape
        inbound_nodes: list of
 
 nodes
        outbound_nodes: list of nodes
        trainable_weights (list of variables)
        non_trainable_weights (list of variables)

    # Methods
        summary
        get_layer  ### 
        get_weights
        set_weights
        get_config
        compute_output_shape

    # Class Methods
        from_config
 

Layer

    # Methods
        call(x, mask=None): Where the layer's logic lives.
        __call__(x, mask=None): Wrapper around the layer logic (`call`).
            If x is a Keras tensor:
                - Connect current layer with last layer from tensor:
                    `self._add_inbound_node(last_layer)`
                - Add layer to tensor history
            If layer is not built:
                - Build from x._keras_shape
        get_weights()
        set_weights(weights)
        get_config()
        count_params()
        compute_output_shape(input_shape)
        compute_mask(x, mask)
        get_input_at(node_index)
        get_output_at(node_index)
        get_input_shape_at(node_index)
        get_output_shape_at(node_index)
        get_input_mask_at(node_index)
        get_output_mask_at(node_index)