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@@ -23,7 +23,7 @@ conda activate hls4ml-tutorial
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## Docker without Vivado
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Pull the prebuilt image from the GitHub Container Registry:
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```bash
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docker pull ghcr.io/fastmachinlearning/hls4ml-tutorial/hls4ml-0.7.1:latest
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docker pull ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.7.1:latest
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```
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Follow these steps to build a Docker image that can be used locally, or on a JupyterHub instance.
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```bash
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git clone https://github.com/fastmachinelearning/hls4ml-tutorial
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cd hls4ml-tutorial
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docker build -f docker/Dockerfile -t ghcr.io/fastmachinlearning/hls4ml-tutorial/hls4ml-0.7.1:latest .
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docker build -f docker/Dockerfile -t ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.7.1:latest .
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```
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Then to start the container:
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```bash
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docker run -p 8888:8888 ghcr.io/fastmachinlearning/hls4ml-tutorial/hls4ml-0.7.1:latest
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docker run -p 8888:8888 ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.7.1:latest
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```
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When the container starts, the Jupyter notebook server is started, and the link to open it in your browser is printed.
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You can clone the repository inside the container and run the notebooks.
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## Docker with Vivado
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Pull the prebuilt image from the GitHub Container Registry:
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```bash
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docker pull ghcr.io/fastmachinlearning/hls4ml-tutorial/hls4ml-0.7.1-vivado-2019.2:latest
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docker pull ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.7.1-vivado-2019.2:latest
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```
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To build the image with Vivado, run (Warning: takes a long time and requires a lot of disk space):
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```bash
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docker build -f docker/Dockerfile.vivado -t ghcr.io/fastmachinlearning/hls4ml-tutorial:hls4ml-0.7.1-vivado-2019.2:latest .
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docker build -f docker/Dockerfile.vivado -t ghcr.io/fastmachinelearning/hls4ml-tutorial:hls4ml-0.7.1-vivado-2019.2:latest .
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```
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Then to start the container:
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```bash
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docker run -p 8888:8888 ghcr.io/fastmachinlearning/hls4ml-tutorial/hls4ml-0.7.1-vivado-2019.2:latest
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docker run -p 8888:8888 ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.7.1-vivado-2019.2:latest
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```
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## Companion material

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