@@ -21,13 +21,18 @@ The following describes the layout of the repository and its different artifacts
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* ` tensorflow-core `
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* All artifacts that build up the core language bindings of TensorFlow for Java
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* Intended audience: projects that provide their own APIs or frameworks on top of
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- TensorFlow and just want a thin layer to access the TensorFlow runtime from the JVM
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+ TensorFlow and just want a thin layer to access the TensorFlow runtime from the JVM
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+ * ` tensorflow-core-kotlin `
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+ * Kotlin API bindings for ` tensorflow-core ` . These are thin wrappers around the core APIs
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+ to make them more idiomatic for use in Kotlin, such as using parameters with default values
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+ operation builders instead of an ` Options ` vararg.
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+
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* ` tensorflow-framework `
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* Primary API for building and training neural networks with TensorFlow
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* Intended audience: neural network developers
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* For more information: [ tensorflow-framework/README.md] ( tensorflow-framework/README.md )
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-
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+
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* ` ndarray `
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* Generic utility library for n-dimensional data I/O operations
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* Used by TensorFlow but does not depend on TensorFlow
@@ -117,6 +122,12 @@ the platforms you are targeting. For this purpose the `-platform` artifacts incl
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the conventions established on this page:
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* [ Reducing the Number of Dependencies] ( https://github.com/bytedeco/javacpp-presets/wiki/Reducing-the-Number-of-Dependencies )
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+ ### Kotlin API
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+ Since the Kotlin API is just a wrapper of the Java API, it uses the Java platform artifacts instead of providing its own.
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+ To use, follow the instructions above for the Java API, but add ` tensorflow-core-kotlin-api ` ,
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+ replacing ` tensorflow-core-api ` if you have explicitly included it.
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+
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### Snapshots
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Snapshots of TensorFlow Java artifacts are automatically distributed after each update in the code. To use them, you need
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