@@ -11,7 +11,6 @@ Learning (NSL) in TensorFlow:
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` pip ` package manager.
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* If you have a unique machine configuration,
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[ build NSL] ( #build-the-neural-structured-learning-pip-package ) from source.
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- * You can also use [ Docker for installing NSL] ( #using-docker ) .
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## Install Neural Structured Learning using pip
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@@ -134,44 +133,3 @@ Note: To exit the virtual environment, run `deactivate`.
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</pre >
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Success: The Neural Structured Learning package is built.
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- ## Using Docker
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- Create a Neural Structured Learning development environment using Docker on
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- Ubuntu or macOS.
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- ### 1. Install Docker.
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- [ Install Docker] ( https://docs.docker.com/install/ ) on your local machine.
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- ### 2. Clone the latest Neural Structured Learning source.
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- <pre class =" prettyprint lang-bsh " >
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- <code class =" devsite-terminal " >git clone https://github.com/tensorflow/neural-structured-learning.git</code >
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- <code class =" devsite-terminal " >cd neural_structured_learning</code >
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- </pre >
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-
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- ### 3. Build a Docker image.
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- <pre class =" prettyprint lang-bsh " >
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- <code class =" devsite-terminal " >docker build . \
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- --tag neural-structured-learning:latest</code >
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- </pre >
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-
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- ### 4. Start a Docker container.
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- <pre class =" prettyprint lang-bsh " >
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- <code class =" devsite-terminal " >docker run -it \
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- --workdir /neural_structured_learning \
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- --volume $(pwd):/neural_structured_learning \
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- neural-structured-learning:latest \
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- bash</code >
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- </pre >
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-
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- ### 5. (Optional) Test Neural Structured Learning.
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- <pre class =" prettyprint lang-bsh " >
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- <code class =" devsite-terminal " >bazel test //neural_structured_learning/...</code >
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- </pre >
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- Success: The Neural Structured Learning development environment is ready.
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