gluon-tutorial | Gluon Tutorial for Deep Learning Researchers | Machine Learning library
kandi X-RAY | gluon-tutorial Summary
kandi X-RAY | gluon-tutorial Summary
This repository provides tutorial code for deep learning researchers && engineers to learn Gluon. In the tutorial, most of the models were implemented with less than 50 lines of code. You will find Gluon and PyTorch share lots of similarities. After reading PyTorch to MXNet, you can easily convert your project between Pytorch and Gluon and learn both of them well. Before starting this tutorial, it is recommended to finish Crash Course. Then you can read Dive into Deep Learning to get a more comprehensive study.
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- Initialize ResNetV2 .
- Compute the residual layer .
- Create features .
- Forward propagation .
- Create a network layer .
- Return the data item at index .
- Returns a resnet instance .
- Update learning rate .
- Get a VGG network .
- Creates a convolutional convolutional layer .
gluon-tutorial Key Features
gluon-tutorial Examples and Code Snippets
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QUESTION
I am reading a tutorial about MxNet. The writers use ‘mxnet.gluon.nn.Sequential()’ as a container to store some blocks (see code 1); then, they rewrite the connection of blocks in ‘def forward(self, x)’ (see codes 2 and 3). Is there any side effect by doing this? By the way, what is the difference between ‘Sequential()’ and ‘HybridSequential()’. I try a list to replace the ‘Sequential’, and I get following warnings doing the initialization process.
“ToySSD.downsamplers” is a container with Blocks. Note that Blocks inside the list, tuple or dict will not be registered automatically. Make sure to register them using register_child() or switching to nn.Sequential/nn.HybridSequential instead.’
As far as I know, if you put some blocks in ‘mxnet.gluon.nn.Sequential()’ or ‘mxnet.gluon.nn.HybridSequential()’, this action is telling the computer that these blocks are connected. However, if you design the relationship of blocks in the ‘forward’ function, you are telling the computer to connect these blocks in another way. Will it lead to confusion? If I only design some block connections in ‘forward’, what are the relationships of the other blocks in ‘Sequential()’ that are not designed in ‘forward’ function?
The entire tutorial can be found in here.
code 1：
...ANSWER
Answered 2018-May-22 at 23:21In Gluon, networks are build using Blocks. If something is not a Block, it cannot be part of a Gluon network. Dense layer is a Block, Convolution is a Block, Pooling layer is a Block, etc.
Sometimes you might want a Block that is not a pre-defined block in Gluon but is a sequence of predefined Gluon blocks. For example,
Conv2D -> MaxPool2D -> Conv2D -> MaxPool2D -> Flatten -> Dense -> Dense
Gluon doesn't have a pre-defined block that does the above sequence of operation. But Gluon does have Blocks that does each of the individual operation. So, you can create your own block that does the above sequence of operation by stringing together predefined Gluon blocks. Example:
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Install gluon-tutorial
You can use gluon-tutorial like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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