Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add workers argument to dask make_blobs #5057

Merged
merged 2 commits into from
Dec 7, 2022
Merged

Add workers argument to dask make_blobs #5057

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
49bb586
Add workers argument to dask make_blobs
viclafargue Dec 5, 2022
d7aeae7
Addressing review
viclafargue Dec 7, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
27 changes: 25 additions & 2 deletions python/cuml/dask/datasets/blobs.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ def make_blobs(n_samples=100, n_features=2, centers=None, cluster_std=1.0,
n_parts=None, center_box=(-10, 10), shuffle=True,
random_state=None, return_centers=False,
verbose=False, order='F', dtype='float32',
client=None):
client=None, workers=None):
"""
Makes labeled Dask-Cupy arrays containing blobs
for a randomly generated set of centroids.
Expand Down Expand Up @@ -91,6 +91,10 @@ def make_blobs(n_samples=100, n_features=2, centers=None, cluster_std=1.0,
Dtype of the generated samples
client : dask.distributed.Client (optional)
Dask client to use
workers : optional, list of strings
Dask addresses of workers to use for computation.
If None, all available Dask workers will be used.
viclafargue marked this conversation as resolved.
Show resolved Hide resolved
(e.g. : `workers = list(client.scheduler_info()['workers'].keys())`)

Returns
-------
Expand All @@ -102,13 +106,32 @@ def make_blobs(n_samples=100, n_features=2, centers=None, cluster_std=1.0,
[n_centers, n_features], optional
The centers of the underlying blobs. It is returned only if
return_centers is True.

Examples
--------
.. code-block:: python

>>> from dask_cuda import LocalCUDACluster
>>> from dask.distributed import Client
>>> from cuml.dask.datasets import make_blobs

>>> cluster = LocalCUDACluster(threads_per_worker=1)
>>> client = Client(cluster)

>>> workers = list(client.scheduler_info()['workers'].keys())
>>> X, y = make_blobs(1000, 10, centers=42, cluster_std=0.1,
... workers=workers)

>>> client.close()
>>> cluster.close()
"""

client = get_client(client=client)

generator = _create_rs_generator(random_state=random_state)

workers = list(client.scheduler_info()['workers'].keys())
if workers is None:
workers = list(client.scheduler_info()['workers'].keys())

n_parts = n_parts if n_parts is not None else len(workers)
parts_workers = (workers * n_parts)[:n_parts]
Expand Down