mxnet

# Deep Learning for Crystal

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[MXNet.cr](https://github.com/toddsundsted/mxnet.cr)
provides [MXNet](https://mxnet.incubator.apache.org/)
bindings for the [Crystal](https://crystal-lang.org/) programming
language. MXNet is a framework for machine learning and deep learning
written in C++, supporting distributed training across multiple
machines and multiple GPUs (if available).

MXNet.cr follows the design of the Python bindings, albeit with
Crystal syntax. The following code:

```crystal
require "mxnet"
a = MXNet::NDArray.array([[1, 2], [3, 4]])
b = MXNet::NDArray.array([1, 0])
puts a * b
```

outputs:

```
[[1, 0], [3, 0]]
<NDArray 2x2 int32 cpu(0)>
```

# Examples

If you want to see what MXNet.cr can do, check out
[toddsundsted/deep-learning](https://github.com/toddsundsted/deep-learning).
It is a collection of problems and solutions from [Deep Learning - The
Straight Dope](https://gluon.mxnet.io/), a set of notebooks teaching
deep learning using MXNet.

# Installation

MXNet.cr requires MXNet.

Build MXNet from source (including Python language bindings) or
install the library from prebuilt packages using the Python package
manager *pip*, per the MXNet installation instructions:

https://mxnet.incubator.apache.org/install/index.html

And add the following to your application's *shard.yml*:

```yaml
dependencies:
  mxnet:
    github: toddsundsted/mxnet.cr
```

## Troubleshooting

MXNet.cr relies on the Python library to find the installed MXNet
shared library ("libmxnet.so"). You can verify MXNet is installed with
the following Python code:

```python
import mxnet as mx
a = mx.ndarray.array([[1, 2], [3, 4]])
b = mx.ndarray.array([1, 0])
print(a * b)
```

which outputs:

```
[[1. 0.]
 [3. 0.]]
<NDArray 2x2 @cpu(0)>
```

## OSX

On OSX, you may need to give your program a hint about the location of
the MXNet shared library (*libmxnet.so*). If you build and run your
program and see an error message like the following:

```
dyld: Library not loaded: lib/libmxnet.so
  Referenced from: /Users/homedirectory/.cache/crystal/crystal-run-eval.tmp
  Reason: image not found
```

you need to either: 1) explicitly set the `DYLD_FALLBACK_LIBRARY_PATH`
environment variable to point to the directory containing *libmxnet.so*,
or 2) move or copy *libmxnet.so* into a well-known location (such as
the project's own *lib* directory).

Alternatively, and more permanently, you can modify the *libmxnet.so*
shared library so that it knows where it's located at runtime (you
will modify the library's LC\_ID\_DYLIB information):

```
LIBMXNET=/Users/homedirectory/mxnet-1.5.1/lib/python3.6/site-packages/mxnet/libmxnet.so # the full path
install_name_tool -id $LIBMXNET $LIBMXNET
```

# Status

MXNet.cr currently implements a subset of
[Gluon](https://gluon.mxnet.io/), and supports a rich set of
operations on arrays and symbols (arithmetic, trigonometric,
hyperbolic, exponents and logarithms, powers, comparison, logical,
rounding, sorting, searching, reduction and indexing) with automatic
differentiation built in.

Implemented classes:
* MXNet
  * Autograd
  * Context
  * Executor
  * Optimizer
  * NDArray
  * Symbol
  * Gluon
    * Block
    * HybridBlock
    * Sequential
    * HybridSequential
    * SymbolBlock
    * Dense
    * Pooling
    * Conv1D
    * Conv2D
    * Conv3D
    * MaxPool1D
    * MaxPool2D
    * MaxPool3D
    * Flatten
    * L1Loss
    * L2Loss
    * SoftmaxCrossEntropyLoss
    * Activation
    * Trainer
    * Parameter
    * Constant