Module codeflare_sdk.cluster.config

The config sub-module contains the definition of the ClusterConfiguration dataclass, which is used to specify resource requirements and other details when creating a Cluster object.

# Copyright 2022 IBM, Red Hat
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
The config sub-module contains the definition of the ClusterConfiguration dataclass,
which is used to specify resource requirements and other details when creating a
Cluster object.
"""

from dataclasses import dataclass, field
import pathlib

dir = pathlib.Path(__file__).parent.parent.resolve()


@dataclass
class ClusterConfiguration:
    """
    This dataclass is used to specify resource requirements and other details, and
    is passed in as an argument when creating a Cluster object.
    """

    name: str
    namespace: str = None
    head_info: list = field(default_factory=list)
    machine_types: list = field(default_factory=list)  # ["m4.xlarge", "g4dn.xlarge"]
    min_cpus: int = 1
    max_cpus: int = 1
    num_workers: int = 1
    min_memory: int = 2
    max_memory: int = 2
    num_gpus: int = 0
    template: str = f"{dir}/templates/base-template.yaml"
    instascale: bool = False
    envs: dict = field(default_factory=dict)
    image: str = "quay.io/project-codeflare/ray:2.5.0-py38-cu116"
    local_interactive: bool = False
    image_pull_secrets: list = field(default_factory=list)
    dispatch_priority: str = None

Classes

class ClusterConfiguration (name: str, namespace: str = None, head_info: list = <factory>, machine_types: list = <factory>, min_cpus: int = 1, max_cpus: int = 1, num_workers: int = 1, min_memory: int = 2, max_memory: int = 2, num_gpus: int = 0, template: str = '/home/runner/work/codeflare-sdk/codeflare-sdk/src/codeflare_sdk/templates/base-template.yaml', instascale: bool = False, envs: dict = <factory>, image: str = 'quay.io/project-codeflare/ray:2.5.0-py38-cu116', local_interactive: bool = False, image_pull_secrets: list = <factory>, dispatch_priority: str = None)

This dataclass is used to specify resource requirements and other details, and is passed in as an argument when creating a Cluster object.

Expand source code

class ClusterConfiguration:
    """
    This dataclass is used to specify resource requirements and other details, and
    is passed in as an argument when creating a Cluster object.
    """

    name: str
    namespace: str = None
    head_info: list = field(default_factory=list)
    machine_types: list = field(default_factory=list)  # ["m4.xlarge", "g4dn.xlarge"]
    min_cpus: int = 1
    max_cpus: int = 1
    num_workers: int = 1
    min_memory: int = 2
    max_memory: int = 2
    num_gpus: int = 0
    template: str = f"{dir}/templates/base-template.yaml"
    instascale: bool = False
    envs: dict = field(default_factory=dict)
    image: str = "quay.io/project-codeflare/ray:2.5.0-py38-cu116"
    local_interactive: bool = False
    image_pull_secrets: list = field(default_factory=list)
    dispatch_priority: str = None

Class variables

var dispatch_priority : str

var envs : dict

var head_info : list

var image : str

var image_pull_secrets : list

var instascale : bool

var local_interactive : bool

var machine_types : list

var max_cpus : int

var max_memory : int

var min_cpus : int

var min_memory : int

var name : str

var namespace : str

var num_gpus : int

var num_workers : int

var template : str