Class Model

tensorlayer/models/core.py:21–983

The :class:`Model` class represents a neural network. It should be subclassed when implementing a dynamic model, where 'forward' method must be overwritten. Otherwise, please specify 'inputs' tensor(s) and 'outputs' tensor(s) to create a static model. In that case, 'inputs' tensors

class Model(object):
    """The :class:`Model` class represents a neural network.

    It should be subclassed when implementing a dynamic model,
    where 'forward' method must be overwritten.
    Otherwise, please specify 'inputs' tensor(s) and 'outputs' tensor(s)
    to create a static model. In that case, 'inputs' tensors should come
    from tl.layers.Input().

    Parameters
    -----------
    inputs : a Layer or list of Layer
        The input(s) to the model.
    outputs : a Layer or list of Layer
        The output(s) to the model.
    name : None or str
        The name of the model.

    Methods
    ---------
    __init__(self, inputs=None, outputs=None, name=None)
        Initializing the Model.
    inputs()
        Get input tensors to this network (only avaiable for static model).
    outputs()
        Get output tensors to this network (only avaiable for static model).
    __call__(inputs, is_train=None, **kwargs)
        Forward input tensors through this network.
    all_layers()
        Get all layer objects of this network in a list of layers.
    weights()
        Get the weights of this network in a list of tensors.
    train()
        Set this network in training mode. (affect layers e.g. Dropout, BatchNorm).
    eval()
        Set this network in evaluation mode.
    as_layer()
        Set this network as a ModelLayer so that it can be integrated into another Model.
    release_memory()
        Release the memory that was taken up by tensors which are maintained by this network.
    save_weights(self, filepath, format='hdf5')
        Save the weights of this network in a given format.
    load_weights(self, filepath, format=None, in_order=True, skip=False)
        Load weights into this network from a specified file.
    save(self, filepath, save_weights=True)
        Save the network with/without weights.
    load(filepath, save_weights=True)
        Load the network with/without weights.

    Examples
    ---------
    >>> import tensorflow as tf
    >>> import numpy as np
    >>> from tensorlayer.layers import Input, Dense, Dropout
    >>> from tensorlayer.models import Model

    Define static model