74 lines
2.2 KiB
Markdown
74 lines
2.2 KiB
Markdown
Jumpy: Python interface for [nd4j](https://nd4j.org)
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===========================================
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[](https://gitter.im/deeplearning4j/deeplearning4j?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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[](https://github.com/deeplearning4j/deeplearning4j/blob/master/jumpy/LICENSE)
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[](https://badge.fury.io/py/jumpy)
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Jumpy allows you to use ND4J from Python _without any network communication_. Many other Python libraries bridging Java
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have considerable overhead, jumpy uses pointers to directly access your numpy arrays. Under the hood, Jumpy uses `pydl4j`
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for dependency management and `pyjnius` to load Java classes.
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## Installation
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Jumpy is on PyPI, simply install it with
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```bash
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pip install jumpy
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```
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or build it from source:
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```bash
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python setup.py install
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```
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## Using Jumpy
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### Creating arrays
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Just like numpy, you can initialize an array using `.zeros()` or `.ones()`
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```python
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import jumpy as jp
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x = jp.zeros((32, 16))
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y = jp.ones((32, 16))
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```
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### Converting numpy array to jumpy array
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A numpy `ndarray` instance can be converted to a jumpy `ndarray` instance (and vice-versa) without copying the data
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```python
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import jumpy as jp
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import numpy as np
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x_np = np.random.random((100, 50))
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x_jp = jp.array(x_np)
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```
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### Converting jumpy array to numpy array
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Simply call the `.numpy()` method of `jumpy.ndarray.ndarray`
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```python
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import jumpy as jp
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x_jp = jp.zeros((100,50))
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x_np = x_jp.numpy()
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```
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### Operations
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* Basic operators like `+` `-` `*` `/` `+=` `-=` `*=` `/=` are overloaded and broadcasting is supported.
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* Indexing, slicing and assignment behaviour has been made as close to numpy as possible.
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* Check `jumpy/ops/` to see available ops.
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---
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## Contribute
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* Check for open issues, or open a new issue to start a discussion around a feature idea or a bug.
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* We could use more ops! Have a look at available ops (`jumpy/ops/`), it's quite easy to add new ones.
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* Send a pull request and bug us on Gitter until it gets merged and published. :)
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