From abcbb523ef96e1003546b463064fc108068be11b Mon Sep 17 00:00:00 2001 From: Matthew Deng Date: Fri, 12 Aug 2022 01:37:01 -0700 Subject: [PATCH 1/3] [data][docs] fix broken links Signed-off-by: Matthew Deng --- doc/source/ray-air/examples/torch_incremental_learning.ipynb | 2 +- python/ray/util/actor_group.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/source/ray-air/examples/torch_incremental_learning.ipynb b/doc/source/ray-air/examples/torch_incremental_learning.ipynb index c333bb7a3294..18158fb0a82d 100644 --- a/doc/source/ray-air/examples/torch_incremental_learning.ipynb +++ b/doc/source/ray-air/examples/torch_incremental_learning.ipynb @@ -246,7 +246,7 @@ "This will allow us to apply built-in preprocessors to the Ray Dataset and allow Ray Datasets to be used with Ray AIR Predictors.\n", " \n", "\n", - "For this example, since we are just working with MNIST dataset, which is small, we use the [`SimpleTorchDataSource`](https://docs.ray.io/en/master/data/package-ref.html?highlight=SimpleTorchDatasource#ray.data.datasource.SimpleTorchDatasource) which just loads the full MNIST dataset into memory.\n", + "For this example, since we are just working with MNIST dataset, which is small, we use the [`SimpleTorchDataSource`](https://docs.ray.io/en/master/data/api/input_output.html?highlight=SimpleTorchDatasource#ray.data.datasource.SimpleTorchDatasource) which just loads the full MNIST dataset into memory.\n", "\n", "For loading larger datasets in a parallel fashion, you should use [Ray Dataset's additional read APIs](https://docs.ray.io/en/master/data/dataset.html#supported-input-formats) to load data from parquet, csv, image files, and more!" ] diff --git a/python/ray/util/actor_group.py b/python/ray/util/actor_group.py index 6324ee85ff51..bf964789a55f 100644 --- a/python/ray/util/actor_group.py +++ b/python/ray/util/actor_group.py @@ -56,7 +56,7 @@ def remote(self, *args, **kwargs): f"in https://docs.ray.io/en/{get_ray_doc_version()}/ray-more-libs/multiprocessing.html. " # noqa: E501 "For stateful/actor processing such as batch prediction, use " "Datasets.map_batches(compute=ActorPoolStrategy, ...), see details in " - f"https://docs.ray.io/en/{get_ray_doc_version()}/data/package-ref.html#ray.data.Dataset.map_batches." # noqa: E501 + f"https://docs.ray.io/en/{get_ray_doc_version()}/data/api/dataset.html#ray.data.Dataset.map_batches." # noqa: E501 ) class ActorGroup: """Group of Ray Actors that can execute arbitrary functions. From b9b1e165307c9b73b62abf167cc14dca6cce0a02 Mon Sep 17 00:00:00 2001 From: Matthew Deng Date: Fri, 12 Aug 2022 01:39:49 -0700 Subject: [PATCH 2/3] + Signed-off-by: Matthew Deng --- python/ray/util/actor_pool.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/ray/util/actor_pool.py b/python/ray/util/actor_pool.py index ed14371ab7af..1799a71a805b 100644 --- a/python/ray/util/actor_pool.py +++ b/python/ray/util/actor_pool.py @@ -10,7 +10,7 @@ f"in https://docs.ray.io/en/{get_ray_doc_version()}/ray-more-libs/multiprocessing.html. " # noqa: E501 "For stateful/actor processing such as batch prediction, use " "Datasets.map_batches(compute=ActorPoolStrategy, ...), see details in " - f"https://docs.ray.io/en/{get_ray_doc_version()}/data/package-ref.html#ray.data.Dataset.map_batches." # noqa: E501 + f"https://docs.ray.io/en/{get_ray_doc_version()}/data/api/dataset.html#ray.data.Dataset.map_batches." # noqa: E501 ) @PublicAPI(stability="beta") class ActorPool: From 73e201c81cfa72e721b15d9c16ca1e8dca8ab9d5 Mon Sep 17 00:00:00 2001 From: Matthew Deng Date: Fri, 12 Aug 2022 08:56:26 -0700 Subject: [PATCH 3/3] use reference Signed-off-by: Matthew Deng --- doc/source/ray-air/examples/torch_incremental_learning.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/ray-air/examples/torch_incremental_learning.ipynb b/doc/source/ray-air/examples/torch_incremental_learning.ipynb index 18158fb0a82d..28436fb270b3 100644 --- a/doc/source/ray-air/examples/torch_incremental_learning.ipynb +++ b/doc/source/ray-air/examples/torch_incremental_learning.ipynb @@ -246,7 +246,7 @@ "This will allow us to apply built-in preprocessors to the Ray Dataset and allow Ray Datasets to be used with Ray AIR Predictors.\n", " \n", "\n", - "For this example, since we are just working with MNIST dataset, which is small, we use the [`SimpleTorchDataSource`](https://docs.ray.io/en/master/data/api/input_output.html?highlight=SimpleTorchDatasource#ray.data.datasource.SimpleTorchDatasource) which just loads the full MNIST dataset into memory.\n", + "For this example, since we are just working with MNIST dataset, which is small, we use the {py:class}`~ray.data.datasource.SimpleTorchDatasource` which just loads the full MNIST dataset into memory.\n", "\n", "For loading larger datasets in a parallel fashion, you should use [Ray Dataset's additional read APIs](https://docs.ray.io/en/master/data/dataset.html#supported-input-formats) to load data from parquet, csv, image files, and more!" ]