From 125e8a40b55b83eb5b5e282974fda78aeae7acc3 Mon Sep 17 00:00:00 2001 From: Alex Aizman Date: Mon, 28 Oct 2024 09:52:44 -0400 Subject: [PATCH] docs: fix broken references (links) * related (master to main) commit: d5c82e5e1889 Signed-off-by: Alex Aizman --- python/aistore/sdk/README.md | 2 +- .../aisio-pytorch/aisio_pytorch_example.ipynb | 12 ++++++------ python/examples/dask/dask-aistore-demo.ipynb | 14 +++++++------- python/examples/sdk/accessing-objects.ipynb | 2 +- python/examples/sdk/multi-object-operations.ipynb | 4 ++-- python/examples/sdk/sdk-etl-tutorial.ipynb | 2 +- 6 files changed, 18 insertions(+), 18 deletions(-) diff --git a/python/aistore/sdk/README.md b/python/aistore/sdk/README.md index 1511694d6c..f01b7da3d0 100644 --- a/python/aistore/sdk/README.md +++ b/python/aistore/sdk/README.md @@ -113,7 +113,7 @@ AIStore also supports [ETLs](https://aistore.nvidia.com/docs/etl), short for Ext > Note: AIS-ETL requires [Kubernetes](https://kubernetes.io/). For more information on deploying AIStore with Kubernetes (or Minikube), refer [here](https://github.com/NVIDIA/aistore/blob/main/deploy/dev/k8s/README.md). -Check out the [provided examples](https://github.com/NVIDIA/aistore/blob/main/python/aistore/sdk/etl_templates.py) to learn more about working with AIS ETL. +To learn more about working with AIS ETL, check out [examples](https://github.com/NVIDIA/aistore/blob/main/python/aistore/sdk/etl). --- diff --git a/python/examples/aisio-pytorch/aisio_pytorch_example.ipynb b/python/examples/aisio-pytorch/aisio_pytorch_example.ipynb index 760b545e0c..b91b9430ab 100644 --- a/python/examples/aisio-pytorch/aisio_pytorch_example.ipynb +++ b/python/examples/aisio-pytorch/aisio_pytorch_example.ipynb @@ -7,7 +7,7 @@ "source": [ "# PyTorch: Loading Data from AIStore \n", "\n", - "Listing and loading data from AIS buckets (buckets that are not 3rd party backend-based) and remote cloud buckets (3rd party backend-based cloud buckets) using [AISFileLister](https://pytorch.org/data/main/generated/torchdata.datapipes.iter.AISFileLister.html#aisfilelister) and [AISFileLoader](https://pytorch.org/data/main/generated/torchdata.datapipes.iter.AISFileLoader.html#torchdata.datapipes.iter.AISFileLoader).\n", + "Listing and loading data from AIS buckets (buckets that are not 3rd party backend-based) and remote cloud buckets (3rd party backend-based cloud buckets) using [AISFileLister](https://pytorch.org/data/beta/generated/torchdata.datapipes.iter.AISFileLister.html) and [AISFileLoader](https://pytorch.org/data/beta/generated/torchdata.datapipes.iter.AISFileLoader.html).\n", "\n", "In the following example, we use the [Caltech-256 Object Category Dataset](https://authors.library.caltech.edu/7694/) containing 256 object categories and a total of 30607 images stored on an AIS bucket and the [Microsoft COCO Dataset](https://cocodataset.org/#home) which has 330K images with over 200K labels of more than 1.5 million object instances across 80 object categories stored on Google Cloud. " ] @@ -37,9 +37,9 @@ "\n", "AIS is an elastic cluster that can grow and shrink at runtime and can be ad-hoc deployed, with or without Kubernetes, anywhere from a single Linux machine to a bare-metal cluster of any size. AIS fully supports Amazon S3, Google Cloud, and Microsoft Azure backends, providing a unified namespace across multiple connected backends and/or other AIS clusters, and [more](https://github.com/NVIDIA/aistore#features).\n", "\n", - "[Getting started with AIS](https://github.com/NVIDIA/aistore/blob/master/docs/getting_started.md) will take only a few minutes (prerequisites boil down to having a Linux with a disk) and can be done either by running a prebuilt [all-in-one docker image](https://github.com/NVIDIA/aistore/tree/master/deploy) or directly from the open-source.\n", + "[Getting started with AIS](https://github.com/NVIDIA/aistore/blob/main/docs/getting_started.md) will take only a few minutes (prerequisites boil down to having a Linux with a disk) and can be done either by running a prebuilt [all-in-one docker image](https://github.com/NVIDIA/aistore/tree/master/deploy) or directly from the open-source.\n", "\n", - "To keep this example simple, we will be running a [minimal standalone docker deployment](https://github.com/NVIDIA/aistore/blob/master/deploy/prod/docker/single/README.md) of AIStore." + "To keep this example simple, we will be running a [minimal standalone docker deployment](https://github.com/NVIDIA/aistore/blob/main/deploy/prod/docker/single/README.md) of AIStore." ] }, { @@ -69,7 +69,7 @@ "id": "3b067695", "metadata": {}, "source": [ - "To create and put objects (dataset) in the bucket, I am going to be using [AIS CLI](https://github.com/NVIDIA/aistore/blob/master/docs/cli.md). But we can also use the [Python SDK](https://github.com/NVIDIA/aistore/tree/master/python/aistore) for the same." + "To create and put objects (dataset) in the bucket, I am going to be using [AIS CLI](https://github.com/NVIDIA/aistore/blob/main/docs/cli.md). But we can also use the [Python SDK](https://github.com/NVIDIA/aistore/tree/master/python/aistore) for the same." ] }, { @@ -216,12 +216,12 @@ "### References\n", "- [AIStore](https://github.com/NVIDIA/aistore)\n", "- [AIStore Blog](https://aiatscale.org/blog)\n", - "- [AIS CLI](https://github.com/NVIDIA/aistore/blob/master/docs/cli.md)\n", + "- [AIS CLI](https://github.com/NVIDIA/aistore/blob/main/docs/cli.md)\n", "- [AIStore Cloud Backend Providers](https://aiatscale.org/docs/providers)\n", "- [AIStore Documentation](https://aiatscale.org/docs)\n", "- [AIStore Python SDK](https://github.com/NVIDIA/aistore/tree/master/python/aistore)\n", "- [Caltech 256 Dataset](https://authors.library.caltech.edu/7694/)\n", - "- [Getting started with AIStore](https://github.com/NVIDIA/aistore/blob/master/docs/getting_started.md)\n", + "- [Getting started with AIStore](https://github.com/NVIDIA/aistore/blob/main/docs/getting_started.md)\n", "- [Microsoft COCO Dataset](https://cocodataset.org/#home)\n" ] } diff --git a/python/examples/dask/dask-aistore-demo.ipynb b/python/examples/dask/dask-aistore-demo.ipynb index 7e83b9d16a..229a7536ef 100644 --- a/python/examples/dask/dask-aistore-demo.ipynb +++ b/python/examples/dask/dask-aistore-demo.ipynb @@ -61,9 +61,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Start by deploying an AIStore cluster. The following demonstrations will be utilizing a [Minikube (Kubernetes) deployment](https://github.com/NVIDIA/aistore/blob/master/deploy/dev/k8s/README.md) of AIStore. \n", + "Start by deploying an AIStore cluster. The following demonstrations will be utilizing a [Minikube (Kubernetes) deployment](https://github.com/NVIDIA/aistore/blob/main/deploy/dev/k8s/README.md) of AIStore. \n", "\n", - "> For information on AIStore deployment options, refer [here](https://github.com/NVIDIA/aistore/blob/master/deploy/README.md).\n", + "> For information on AIStore deployment options, refer [here](https://github.com/NVIDIA/aistore/blob/main/deploy/README.md).\n", "\n", "Once deployed, import the `aistore` package and initialize a `Client`:" ] @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**Note:** ETL processes using Dask with data on AIStore *are* possible, but has limitations as Dask does *not* currently support AIStore as a recognized storage provider. Refer to the AIS-ETL service [here](https://github.com/NVIDIA/aistore/blob/master/docs/etl.md), which offers both *offline* and *inline* custom transformations, as well as flexibility to the scope of those transformations (bucket-specific or object(s)-specific), and more." + "**Note:** ETL processes using Dask with data on AIStore *are* possible, but has limitations as Dask does *not* currently support AIStore as a recognized storage provider. Refer to the AIS-ETL service [here](https://github.com/NVIDIA/aistore/blob/main/docs/etl.md), which offers both *offline* and *inline* custom transformations, as well as flexibility to the scope of those transformations (bucket-specific or object(s)-specific), and more." ] }, { @@ -637,7 +637,7 @@ "dd.to_json(\"gcs://dask-demo-bucket/sample.json\")\n", "```\n", "\n", - "> AIStore supports a subset of S3 API and Dask supports [S3-compatible storage services](https://docs.dask.org/en/stable/how-to/connect-to-remote-data.html#using-other-s3-compatible-services). However, Dask uses Boto3 for this and AIStore does not support Boto3 as it does not follow HTTP(s) protocol. For more information on AIStore compatibility with S3, refer [here](https://github.com/NVIDIA/aistore/blob/master/docs/s3compat.md).\n", + "> AIStore supports a subset of S3 API and Dask supports [S3-compatible storage services](https://docs.dask.org/en/stable/how-to/connect-to-remote-data.html#using-other-s3-compatible-services). However, Dask uses Boto3 for this and AIStore does not support Boto3 as it does not follow HTTP(s) protocol. For more information on AIStore compatibility with S3, refer [here](https://github.com/NVIDIA/aistore/blob/main/docs/s3compat.md).\n", "\n", "While we cannot directly write to AIStore with Dask API (`dd.to_csv(\"ais://bucket/file.csv\")` not supported as of now), we can convert the DataFrame to bytes and move it using AIStore's own API:" ] @@ -668,7 +668,7 @@ "source": [ "However, the above method of converting a Dask DataFrame to a Pandas DataFrame may not be ideal as it defeats some of the performance advantages of using Dask. Converting a Dask DataFrame to a Pandas DataFrame only makes sense to do if the data can fully fit into memory (i.e. data has been filtered and is now much smaller).\n", "\n", - "For much larger datasets, [AIS-ETL](https://github.com/NVIDIA/aistore/blob/master/docs/etl.md) may offer better performance while offering similar ETL capabilities to those demonstrated above. Please refer [here](https://github.com/NVIDIA/aistore/blob/master/docs/etl.md) for more information." + "For much larger datasets, [AIS-ETL](https://github.com/NVIDIA/aistore/blob/main/docs/etl.md) may offer better performance while offering similar ETL capabilities to those demonstrated above. Please refer [here](https://github.com/NVIDIA/aistore/blob/main/docs/etl.md) for more information." ] }, { @@ -723,8 +723,8 @@ "source": [ "* [Dask API](https://docs.dask.org/en/stable/dataframe-api.html)\n", "* [Pandas API](https://pandas.pydata.org/docs/reference/index.html)\n", - "* [AIStore Python SDK](https://github.com/NVIDIA/aistore/blob/master/docs/python_sdk.md)\n", - "* [AIS-ETL](https://github.com/NVIDIA/aistore/blob/master/docs/etl.md)" + "* [AIStore Python SDK](https://github.com/NVIDIA/aistore/blob/main/docs/python_sdk.md)\n", + "* [AIS-ETL](https://github.com/NVIDIA/aistore/blob/main/docs/etl.md)" ] } ], diff --git a/python/examples/sdk/accessing-objects.ipynb b/python/examples/sdk/accessing-objects.ipynb index b78dd3550a..ca0fb28bea 100644 --- a/python/examples/sdk/accessing-objects.ipynb +++ b/python/examples/sdk/accessing-objects.ipynb @@ -254,7 +254,7 @@ }, "source": [ "## Working with multiple objects\n", - "AIS supports multi-object operations on groups of objects. For examples of working with groups of objects see [here](https://github.com/NVIDIA/aistore/blob/master/python/examples/sdk/multi-object-operations.ipynb)" + "AIS supports multi-object operations on groups of objects. For examples of working with groups of objects see [here](https://github.com/NVIDIA/aistore/blob/main/python/examples/sdk/multi-object-operations.ipynb)" ] } ], diff --git a/python/examples/sdk/multi-object-operations.ipynb b/python/examples/sdk/multi-object-operations.ipynb index 5ff9c2e16f..2c9c0f5e46 100644 --- a/python/examples/sdk/multi-object-operations.ipynb +++ b/python/examples/sdk/multi-object-operations.ipynb @@ -125,7 +125,7 @@ }, "source": [ "### Create Object Group by Template String\n", - "String templates can be passed directly to AIS following the [syntax described here](https://github.com/NVIDIA/aistore/blob/master/docs/batch.md#operations-on-multiple-selected-objects)" + "String templates can be passed directly to AIS following the [syntax described here](https://github.com/NVIDIA/aistore/blob/main/docs/batch.md#operations-on-multiple-selected-objects)" ] }, { @@ -226,7 +226,7 @@ "source": [ "#### Transform -- Provide an ETL to be performed on each object so the result appears in the destination bucket.\n", "\n", - "Note: This step requires the AIS cluster to be running in Kubernetes; see [getting_started](https://github.com/NVIDIA/aistore/blob/master/docs/getting_started.md#kubernetes-playground) for setup info." + "Note: This step requires the AIS cluster to be running in Kubernetes; see [getting_started](https://github.com/NVIDIA/aistore/blob/main/docs/getting_started.md#kubernetes-playground) for setup info." ] }, { diff --git a/python/examples/sdk/sdk-etl-tutorial.ipynb b/python/examples/sdk/sdk-etl-tutorial.ipynb index a913c9fe0d..09a32d10ce 100644 --- a/python/examples/sdk/sdk-etl-tutorial.ipynb +++ b/python/examples/sdk/sdk-etl-tutorial.ipynb @@ -102,7 +102,7 @@ { "cell_type": "markdown", "source": [ - "Refer to more ETL templates [here](https://github.com/NVIDIA/aistore/blob/master/python/aistore/sdk/etl_templates.py)." + "Refer to more ETL templates [here](https://github.com/NVIDIA/aistore/blob/main/python/aistore/sdk/etl)." ], "metadata": { "collapsed": false