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@@ -22,59 +22,9 @@ The recommended installation method is `pip <https://pip.pypa.io/en/stable/>`_-i | |
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.. code-block:: console | ||
$ git clone [email protected]:ZettaAI/zetta_utils.git | ||
$ git clone --recurse-submodules [email protected]:ZettaAI/zetta_utils.git | ||
$ cd zetta_utils | ||
$ pip install -e '.[all]' | ||
If you are a member of the Zetta team and have access to private submodules, add `--recurse-submodules` to the clone command: | ||
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.. code-block:: console | ||
$ git clone --recurse-submodules [email protected]:ZettaAI/zetta_utils.git | ||
$ cd zetta_utils | ||
$ pip install -e '.[all]' | ||
.. note:: | ||
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Please be sure to read all of the following points to avoid installation problems. | ||
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For logging purposes, **zetta_utils** requires the following two environment variables: | ||
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.. code-block:: console | ||
ZETTA_USER | ||
ZETTA_PROJECT | ||
If you are planning to interact with **Google Cloud Storage** (GCS) in any way, make sure to authenticate by running | ||
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.. code-block:: console | ||
$ gcloud auth application-default login | ||
If you are planning to use **Amazon Simple Queue Service** (SQS) for managing tasks, you must set the following environment variables: | ||
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.. code-block:: console | ||
AWS_ACCESS_KEY_ID | ||
AWS_SECRET_ACCESS_KEY | ||
AWS_DEFAULT_REGION | ||
Please consult the `AWS documentation <https://aws.amazon.com/blogs/security/wheres-my-secret-access-key/>`_ for how to generate the access key and the secret access key. | ||
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If you are planning to use **WandB** for automatic logging during training, the following environment variable needs to be set: | ||
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.. code-block:: console | ||
WANDB_API_KEY | ||
This can be done automatically by running | ||
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.. code-block:: console | ||
$ wandb login | ||
$ ./install_zutils.py | ||
If you want to let zetta_utils generate **neuroglancer** links automatically, you will need to set: | ||
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@@ -92,11 +42,6 @@ If you want to use **Grafana** integration for logging, you will need to set: | |
Please consult the `Grafana API documentation <https://grafana.com/docs/grafana-cloud/reference/create-api-key/>`_ for how to set up an API key. | ||
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If you are planning to use `zetta_utils.parsing.cue` or `zetta_utils.cli`, you will need to install `cuelang <https://cuelang.org/>`_. | ||
It is a simple two-step process which is described in detail in their `Documentation <https://cuelang.org/docs/install/>`_. | ||
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To use **KEDA** (Kubernetes Event-driven Autoscaling), you will first need to install `helm <https://helm.sh/docs/intro/install/>`_. | ||
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@@ -108,8 +53,6 @@ If you are planning to use `zetta_utils.viz` toolkit, you will need to install * | |
$ sudo apt install -y nodejs | ||
Depending on your system, you may need to install several other non-Python dependencies. Please refer to the provided `Dockerfiles <https://github.com/ZettaAI/zetta_utils/tree/main/docker>`_ for the comprehensive setup process. | ||
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The next steps will get you up and running in no time: | ||
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- `subchunkable_apply_flow_quick_start_guide` will introduce you to handling volumetric data in ``zetta_utils`` CUE files and running simple tasks using SubchunkableApplyFlow. | ||
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