Source code for codeflare_sdk.ray.cluster.generate_yaml

# 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
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"""
This sub-module exists primarily to be used internally by the Cluster object
(in the cluster sub-module) for AppWrapper generation.
"""

import json
import typing
import yaml
import os
import uuid
from kubernetes import client
from ...common import _kube_api_error_handling
from ...common.kueue import add_queue_label
from ...common.kubernetes_cluster.auth import (
    get_api_client,
    config_check,
)
import codeflare_sdk


[docs] def read_template(template): with open(template, "r") as stream: try: return yaml.safe_load(stream) except yaml.YAMLError as exc: print(exc)
[docs] def gen_names(name): if not name: gen_id = str(uuid.uuid4()) appwrapper_name = "appwrapper-" + gen_id cluster_name = "cluster-" + gen_id return appwrapper_name, cluster_name else: return name, name
# Check if the routes api exists
[docs] def is_openshift_cluster(): try: config_check() for api in client.ApisApi(get_api_client()).get_api_versions().groups: for v in api.versions: if "route.openshift.io/v1" in v.group_version: return True else: return False except Exception as e: # pragma: no cover return _kube_api_error_handling(e)
[docs] def is_kind_cluster(): try: config_check() v1 = client.CoreV1Api() label_selector = "kubernetes.io/hostname=kind-control-plane" nodes = v1.list_node(label_selector=label_selector) # If we find one or more nodes with the label, assume it's a KinD cluster return len(nodes.items) > 0 except Exception as e: print(f"Error checking if cluster is KinD: {e}") return False
[docs] def update_names( cluster_yaml: dict, cluster: "codeflare_sdk.ray.cluster.cluster.Cluster", ): metadata = cluster_yaml.get("metadata") metadata["name"] = cluster.config.name metadata["namespace"] = cluster.config.namespace
[docs] def update_image(spec, image): containers = spec.get("containers") if image != "": for container in containers: container["image"] = image
[docs] def update_image_pull_secrets(spec, image_pull_secrets): template_secrets = spec.get("imagePullSecrets", []) spec["imagePullSecrets"] = template_secrets + [ {"name": x} for x in image_pull_secrets ]
[docs] def update_env(spec, env): containers = spec.get("containers") for container in containers: if env: if "env" in container: container["env"].extend(env) else: container["env"] = env
[docs] def update_resources( spec, cpu_requests, cpu_limits, memory_requests, memory_limits, custom_resources, ): container = spec.get("containers") for resource in container: requests = resource.get("resources").get("requests") if requests is not None: requests["cpu"] = cpu_requests requests["memory"] = memory_requests limits = resource.get("resources").get("limits") if limits is not None: limits["cpu"] = cpu_limits limits["memory"] = memory_limits for k in custom_resources.keys(): limits[k] = custom_resources[k] requests[k] = custom_resources[k]
[docs] def head_worker_gpu_count_from_cluster( cluster: "codeflare_sdk.ray.cluster.cluster.Cluster", ) -> typing.Tuple[int, int]: head_gpus = 0 worker_gpus = 0 for k in cluster.config.head_extended_resource_requests.keys(): resource_type = cluster.config.extended_resource_mapping[k] if resource_type == "GPU": head_gpus += int(cluster.config.head_extended_resource_requests[k]) for k in cluster.config.worker_extended_resource_requests.keys(): resource_type = cluster.config.extended_resource_mapping[k] if resource_type == "GPU": worker_gpus += int(cluster.config.worker_extended_resource_requests[k]) return head_gpus, worker_gpus
FORBIDDEN_CUSTOM_RESOURCE_TYPES = ["GPU", "CPU", "memory"]
[docs] def head_worker_resources_from_cluster( cluster: "codeflare_sdk.ray.cluster.cluster.Cluster", ) -> typing.Tuple[dict, dict]: to_return = {}, {} for k in cluster.config.head_extended_resource_requests.keys(): resource_type = cluster.config.extended_resource_mapping[k] if resource_type in FORBIDDEN_CUSTOM_RESOURCE_TYPES: continue to_return[0][resource_type] = cluster.config.head_extended_resource_requests[ k ] + to_return[0].get(resource_type, 0) for k in cluster.config.worker_extended_resource_requests.keys(): resource_type = cluster.config.extended_resource_mapping[k] if resource_type in FORBIDDEN_CUSTOM_RESOURCE_TYPES: continue to_return[1][resource_type] = cluster.config.worker_extended_resource_requests[ k ] + to_return[1].get(resource_type, 0) return to_return
[docs] def update_nodes( ray_cluster_dict: dict, cluster: "codeflare_sdk.ray.cluster.cluster.Cluster", ): head = ray_cluster_dict.get("spec").get("headGroupSpec") worker = ray_cluster_dict.get("spec").get("workerGroupSpecs")[0] head_gpus, worker_gpus = head_worker_gpu_count_from_cluster(cluster) head_resources, worker_resources = head_worker_resources_from_cluster(cluster) head_resources = json.dumps(head_resources).replace('"', '\\"') head_resources = f'"{head_resources}"' worker_resources = json.dumps(worker_resources).replace('"', '\\"') worker_resources = f'"{worker_resources}"' head["rayStartParams"]["num-gpus"] = str(head_gpus) head["rayStartParams"]["resources"] = head_resources # Head counts as first worker worker["replicas"] = cluster.config.num_workers worker["minReplicas"] = cluster.config.num_workers worker["maxReplicas"] = cluster.config.num_workers worker["groupName"] = "small-group-" + cluster.config.name worker["rayStartParams"]["num-gpus"] = str(worker_gpus) worker["rayStartParams"]["resources"] = worker_resources for comp in [head, worker]: spec = comp.get("template").get("spec") update_image_pull_secrets(spec, cluster.config.image_pull_secrets) update_image(spec, cluster.config.image) update_env(spec, cluster.config.envs) if comp == head: # TODO: Eventually add head node configuration outside of template update_resources( spec, cluster.config.head_cpu_requests, cluster.config.head_cpu_limits, cluster.config.head_memory_requests, cluster.config.head_memory_limits, cluster.config.head_extended_resource_requests, ) else: update_resources( spec, cluster.config.worker_cpu_requests, cluster.config.worker_cpu_limits, cluster.config.worker_memory_requests, cluster.config.worker_memory_limits, cluster.config.worker_extended_resource_requests, )
[docs] def del_from_list_by_name(l: list, target: typing.List[str]) -> list: return [x for x in l if x["name"] not in target]
[docs] def augment_labels(item: dict, labels: dict): if not "labels" in item["metadata"]: item["metadata"]["labels"] = {} item["metadata"]["labels"].update(labels)
[docs] def notebook_annotations(item: dict): nb_prefix = os.environ.get("NB_PREFIX") if nb_prefix: if not "annotations" in item["metadata"]: item["metadata"]["annotations"] = {} item["metadata"]["annotations"].update( {"app.kubernetes.io/managed-by": nb_prefix} )
[docs] def wrap_cluster(cluster_yaml: dict, appwrapper_name: str, namespace: str): return { "apiVersion": "workload.codeflare.dev/v1beta2", "kind": "AppWrapper", "metadata": {"name": appwrapper_name, "namespace": namespace}, "spec": {"components": [{"template": cluster_yaml}]}, }
[docs] def write_user_yaml(user_yaml, output_file_name): # Create the directory if it doesn't exist directory_path = os.path.dirname(output_file_name) if not os.path.exists(directory_path): os.makedirs(directory_path) with open(output_file_name, "w") as outfile: yaml.dump(user_yaml, outfile, default_flow_style=False) print(f"Written to: {output_file_name}")
[docs] def generate_appwrapper(cluster: "codeflare_sdk.ray.cluster.cluster.Cluster"): cluster_yaml = read_template(cluster.config.template) appwrapper_name, _ = gen_names(cluster.config.name) update_names( cluster_yaml, cluster, ) update_nodes(cluster_yaml, cluster) augment_labels(cluster_yaml, cluster.config.labels) notebook_annotations(cluster_yaml) user_yaml = ( wrap_cluster(cluster_yaml, appwrapper_name, cluster.config.namespace) if cluster.config.appwrapper else cluster_yaml ) add_queue_label(user_yaml, cluster.config.namespace, cluster.config.local_queue) if cluster.config.write_to_file: directory_path = os.path.expanduser("~/.codeflare/resources/") outfile = os.path.join(directory_path, appwrapper_name + ".yaml") write_user_yaml(user_yaml, outfile) return outfile else: user_yaml = yaml.dump(user_yaml) print(f"Yaml resources loaded for {cluster.config.name}") return user_yaml