Foo Package

.. currentmodule:: mxnet.foo

.. warning:: This package is currently experimental and may change in the near future.

Overview

Foo package is a high-level interface for MXNet designed to be easy to use while keeping most of the flexibility of low level API. Foo supports both imperative and symbolic programming, making it easy to train complex models imperatively in Python and then deploy with symbolic graph in C++ and Scala.

Parameter

.. currentmodule:: mxnet.foo

.. autoclass:: mxnet.foo.Parameter
    :members:
.. autoclass:: mxnet.foo.ParameterDict
    :members:

Neural Network Layers

.. currentmodule:: mxnet.foo.nn

Containers

.. currentmodule:: mxnet.foo.nn
.. autoclass:: mxnet.foo.nn.Layer
    :members:

    .. automethod:: __call__
.. autoclass:: mxnet.foo.nn.Sequential
    :members:

Basic Layers

.. currentmodule:: mxnet.foo.nn  
.. autoclass:: mxnet.foo.nn.Dense
    :members:
.. autoclass:: mxnet.foo.nn.Activation
    :members:
.. autoclass:: mxnet.foo.nn.Dropout
    :members:
.. autoclass:: mxnet.foo.nn.BatchNorm
    :members:
.. autoclass:: mxnet.foo.nn.LeakyReLU
    :members:
.. autoclass:: mxnet.foo.nn.Embedding
    :members:

Convolutional Layers

.. currentmodule:: mxnet.foo.nn  
.. autoclass:: mxnet.foo.nn.Conv1D
    :members:
.. autoclass:: mxnet.foo.nn.Conv2D
    :members:
.. autoclass:: mxnet.foo.nn.Conv3D
    :members:
.. autoclass:: mxnet.foo.nn.Conv1DTranspose
    :members:
.. autoclass:: mxnet.foo.nn.Conv2DTranspose
    :members:
.. autoclass:: mxnet.foo.nn.Conv3DTranspose
    :members:

Pooling Layers

.. currentmodule:: mxnet.foo.nn
.. autoclass:: mxnet.foo.nn.MaxPool1D
    :members:
.. autoclass:: mxnet.foo.nn.MaxPool2D
    :members:
.. autoclass:: mxnet.foo.nn.MaxPool3D
    :members:
.. autoclass:: mxnet.foo.nn.AvgPool1D
    :members:
.. autoclass:: mxnet.foo.nn.AvgPool2D
    :members:
.. autoclass:: mxnet.foo.nn.AvgPool3D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalMaxPool1D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalMaxPool2D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalMaxPool3D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalAvgPool1D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalAvgPool2D
    :members:
.. autoclass:: mxnet.foo.nn.GlobalAvgPool3D
    :members:

Recurrent Layers

.. currentmodule:: mxnet.foo.rnn

.. autoclass:: mxnet.foo.rnn.RecurrentCell
    :members:

    .. automethod:: __call__
.. autoclass:: mxnet.foo.rnn.LSTMCell
    :members:
.. autoclass:: mxnet.foo.rnn.GRUCell
    :members:
.. autoclass:: mxnet.foo.rnn.RNNCell
    :members:
.. autoclass:: mxnet.foo.rnn.FusedRNNCell
    :members:
.. autoclass:: mxnet.foo.rnn.SequentialRNNCell
    :members:
.. autoclass:: mxnet.foo.rnn.BidirectionalCell
    :members:
.. autoclass:: mxnet.foo.rnn.DropoutCell
    :members:
.. autoclass:: mxnet.foo.rnn.ZoneoutCell
    :members:
.. autoclass:: mxnet.foo.rnn.ResidualCell
    :members:

Trainer

.. currentmodule:: mxnet.foo

.. autoclass:: mxnet.foo.Trainer
    :members:

Loss functions

.. currentmodule:: mxnet.foo.loss

.. automethod:: mxnet.foo.loss.custom_loss
.. automethod:: mxnet.foo.loss.multitask_loss
.. automethod:: mxnet.foo.loss.l1_loss
.. automethod:: mxnet.foo.loss.l2_loss
.. automethod:: mxnet.foo.loss.softmax_cross_entropy_loss

Utilities

.. currentmodule:: mxnet.foo.utils

.. automethod:: mxnet.foo.utils.split_data
.. automethod:: mxnet.foo.utils.load_data