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1 | | -# TensorFlow NdArray |
| 1 | +# NdArray Java Library |
2 | 2 |
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3 | 3 | ## Introduction |
4 | 4 |
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5 | | -TensorFlow NdArray is a utility library used by TensorFlow to accomplish tasks that are not easily |
6 | | -achievable using a standard JDK. As opposed to other artifacts in this repository, this library does |
7 | | -not depend on TensorFlow runtime itself and can be imported by any other projects running on a JVM |
8 | | -that wants to make use of those tools. For example, an instance of `NdArray` could easily be passed |
9 | | -from one library to another for sharing data. |
| 5 | +NdArray is a library exposing utilities for manipulating data in a n-dimensional space in Java. |
| 6 | +Unlike other Java artifacts distributed by TensorFlow, this library does not depend on the TensorFlow |
| 7 | +runtime, therefore is very lightweight and can be used by any kind of Java project. |
10 | 8 |
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11 | | -To import TensorFlow NdArray in your project, simply add the following dependency: |
| 9 | +To import the NdArray library in your project, simply add the following dependency: |
12 | 10 | ```xml |
13 | 11 | <dependency> |
14 | 12 | <groupId>org.tensorflow</groupId> |
@@ -91,9 +89,9 @@ assertEquals(3, slice.getInt(1, 0)); // (1, 1, 0) in the original matrix |
91 | 89 |
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92 | 90 | ## Integration with TensorFlow |
93 | 91 |
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94 | | -TensorFlow NdArray library is independent of the TensorFlow runtime library, making it a good choice for |
95 | | -manipulating multi-dimensional data structures from anywhere. As an example, here |
96 | | -is how it is actually done by the [TensorFlow Core API](https://github.com/tensorflow/java/tree/master/tensorflow-core/tensorflow-core-api): |
| 92 | +The NdArray library is independent of the TensorFlow runtime library, making it a good choice for |
| 93 | +manipulating multi-dimensional data structures from anywhere. But as an example, here |
| 94 | +is how it is actually being used by the [TensorFlow Core API](https://github.com/tensorflow/java/tree/master/tensorflow-core/tensorflow-core-api): |
97 | 95 |
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98 | 96 | ```java |
99 | 97 | // Allocate a tensor of 32-bits integer of the shape (2, 3, 2) |
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