1. If a user reads a folder with grayscale and color images, ImageFolderDatasource errors.
2. There's no way to retain image shapes.
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
This PR revamps and aligns the README and Ray intro doc page:
New "What is Ray" diagram that introduces AIR vs Ray core (diagram TBD finalized, this is the working placeholder)
Update the description of Ray
Link out to the user guides for key libraries and key concepts
Remove old / broken links, as well as the inline library descriptions from the README
- Move autoscaling architecture from autoscaling page to architecture page
- Update architecture page
- Remove "Router" actor
- Update description of ServeHandle
- Update defaults about HTTPproxy (default one on each node -> default just one per cluster, on the head node)
- Add note about fault tolerance in different failure scenarios
- Assorted typos/usage nits
Co-authored-by: shrekris-anyscale <92341594+shrekris-anyscale@users.noreply.github.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
This PR migrates the old Community Supported Cluster Launcher docs to the new Ray Clusters doc structure.
Signed-off-by: Cade Daniel <cade@anyscale.com>
Removes deprecated APIs:
- serve.start()
- get_handle()
Rewrites the ServeHandle doc snippet to use the recommended workflow for ServeHandles (only access them from other deployments, pass Deployments in as input args to `.bind()`, which get resolved to ServeHandles at runtime)
Co-authored-by: shrekris-anyscale <92341594+shrekris-anyscale@users.noreply.github.com>
First of all, sorry i messed up with the previous pr when sync with the master (#27374). This PR is the duplicate of previous pr until we update the changes (change: adding the version check for the ray_lightning for the compatibility). Also, apology for the massive review requests on the previous PR.
- Currently not all code under ray-core/doc_code is covered by CI.
- tf_example.py and torch_example.py are not used anywhere.
Signed-off-by: Jiajun Yao <jeromeyjj@gmail.com>
Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>
This PR
adds a page of guidance on GPU deployment with Ray/K8s. This page is a modified and slightly expanded version of the existing page https://docs.ray.io/en/latest/cluster/kubernetes-gpu.html
moves managed K8s service intro links to their own page
Support a GPU column for the new dashboard
Have first node be default expanded
Signed-off-by: Alan Guo aguo@anyscale.comfixes#13889
Addresses comment from #26996
Converting a Pandas DataFrame column to an ndarray (e.g. via df[col].values) can often result in a full copy of the column in order to construct the ndarray due to Pandas' 2D block management. This PR ports tensor extension type checking to checking the dtype, which is always an O(1) check.
Signed-off-by: Clark Zinzow <clarkzinzow@gmail.com>
We decided to allow escaping the parent pg via `PlacementGroupSchedulingStrategy(placement_group=None)` instead of using "DEFAULT". Our doc is updated with that but in the code it's still not allowed.
Add optional last_activity_at field to /api/component_activities to record end time of most recently finished activity
Signed-off-by: Nikita Vemuri <nikitavemuri@gmail.com>
1. Add doc for python SDK and docstrings on public SDK
2. Rename list -> ray_list and get -> ray_get for better naming
3. Fix some typos
4. Auto translate address to api server url.
Co-authored-by: SangBin Cho <rkooo567@gmail.com>
Ray automatically sets OMP_NUM_THREADS=1, potentially limiting multithreading in native pytorch/tensorflow. If this leads to performance differences, we should address this either in Ray Train or in Ray core.
Signed-off-by: Kai Fricke <kai@anyscale.com>
