| .. Licensed to the Apache Software Foundation (ASF) under one |
| or more contributor license agreements. See the NOTICE file |
| distributed with this work for additional information |
| regarding copyright ownership. The ASF licenses this file |
| to you under the Apache License, Version 2.0 (the |
| "License"); you may not use this file except in compliance |
| with the License. You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, |
| software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| KIND, either express or implied. See the License for the |
| specific language governing permissions and limitations |
| under the License. |
| |
| mxnet.gluon |
| ============ |
| |
| The Gluon library in Apache MXNet provides a clear, concise, and simple API for deep learning. |
| It makes it easy to prototype, build, and train deep learning models without sacrificing training speed. |
| |
| Example |
| ------- |
| |
| The following example shows how you might create a simple neural network with three layers: |
| one input layer, one hidden layer, and one output layer. |
| |
| .. code-block:: python |
| |
| net = gluon.nn.Sequential() |
| # When instantiated, Sequential stores a chain of neural network layers. |
| # Once presented with data, Sequential executes each layer in turn, using |
| # the output of one layer as the input for the next |
| with net.name_scope(): |
| net.add(gluon.nn.Dense(256, activation="relu")) # 1st layer (256 nodes) |
| net.add(gluon.nn.Dense(256, activation="relu")) # 2nd hidden layer |
| net.add(gluon.nn.Dense(num_outputs)) |
| |
| |
| .. automodule:: mxnet.gluon |
| |
| |
| Tutorials |
| --------- |
| |
| .. container:: cards |
| |
| .. card:: |
| :title: Gluon Guide |
| :link: ../../tutorials/packages/gluon/index.html |
| |
| The Gluon guide. Start here! |
| |
| .. card:: |
| :title: Gluon-CV Toolkit |
| :link: https://gluon-cv.mxnet.io/ |
| |
| A Gluon add-on module for computer vision. |
| |
| .. card:: |
| :title: Gluon-NLP Toolkit |
| :link: https://gluon-nlp.mxnet.io/ |
| |
| A Gluon add-on module for natural language processing. |
| |
| |
| APIs and Packages |
| ----------------- |
| |
| Core Modules |
| ~~~~~~~~~~~~ |
| |
| .. container:: cards |
| |
| .. card:: |
| :title: gluon.nn |
| :link: nn/index.html |
| |
| Neural network components. |
| |
| .. card:: |
| :title: gluon.rnn |
| :link: rnn/index.html |
| |
| Recurrent neural network components. |
| |
| Training |
| ~~~~~~~~ |
| |
| .. container:: cards |
| |
| .. card:: |
| :title: gluon.loss |
| :link: loss/index.html |
| |
| Loss functions for training neural networks. |
| |
| .. card:: |
| :title: gluon.Parameter |
| :link: parameter.html |
| |
| Parameter getting and setting functions. |
| |
| .. card:: |
| :title: gluon.Trainer |
| :link: trainer.html |
| |
| Functions for applying an optimizer on a set of parameters. |
| |
| Data |
| ~~~~ |
| |
| .. container:: cards |
| |
| .. card:: |
| :title: gluon.data |
| :link: data/index.html |
| |
| Dataset utilities. |
| |
| .. card:: |
| :title: gluon.data.vision |
| :link: data/vision/index.html |
| |
| Image dataset utilities. |
| |
| .. card:: |
| :title: gluon.model_zoo.vision |
| :link: model_zoo/index.html |
| |
| A module for loading pre-trained neural network models. |
| |
| |
| Utilities |
| ~~~~~~~~~ |
| |
| .. container:: cards |
| |
| .. card:: |
| :title: gluon.utils |
| :link: utils/index.html |
| |
| A variety of utilities for training. |
| |
| .. toctree:: |
| :hidden: |
| :maxdepth: 2 |
| :glob: |
| |
| block |
| hybrid_block |
| symbol_block |
| constant |
| parameter |
| parameter_dict |
| trainer |
| */index |