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Add managed_pathways_service for Pathways-on-Cloud
This change introduces Managed Pathways Service for GKE. It includes: `tpu_manager.py` uses `kubectl` to deploy a Pathways proxy JobSet on a GKE cluster, sets up port forwarding, and configures JAX environment variables to connect to the proxy. `run_connect_example.py` is an example script to start the proxy. Prerequisite: A Pathways cluster is up and running with Resource Manager and worker pods deployed successfully, e.g., using pw-cluster.yaml. TESTED: on proxy 2 clients each requesting `2 x v5e-32` simultaneously. PiperOrigin-RevId: 801034430
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‎pathwaysutils/managed_pathways_service/__init__.py

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# This file marks this directory as a Python package.

‎pathwaysutils/managed_pathways_service/pw-cluster.yaml

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apiVersion: jobset.x-k8s.io/v1alpha2
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kind: JobSet
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metadata:
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name: pathways-akshu-s4-rw7
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spec:
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coordinator:
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replicatedJob: pathways-head
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failurePolicy:
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maxRestarts: 1
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restartStrategy: Recreate
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network:
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enableDNSHostnames: true
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publishNotReadyAddresses: true
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replicatedJobs:
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- name: pathways-head
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replicas: 1
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template:
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metadata:
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annotations:
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alpha.jobset.sigs.k8s.io/exclusive-topology: kubernetes.io/hostname
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spec:
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backoffLimit: 0
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completionMode: Indexed
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completions: 1
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parallelism: 1
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template:
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metadata:
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labels:
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kueue.x-k8s.io/podset: pathways-head
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spec:
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containers:
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- args:
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- --server_port=29001
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- --gcs_scratch_location=gs://akshu-v5e
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- --node_type=resource_manager
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- --instance_count=4
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- --instance_type=tpuv5e:4x8
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- --xla_tpu_use_enhanced_launch_barrier=true
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- --logtostderr
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- --stderrthreshold=0
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- --v=1
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env:
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- name: REPLICATED_JOB_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.annotations['jobset.sigs.k8s.io/replicatedjob-name']
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- name: JOBSET_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.annotations['jobset.sigs.k8s.io/jobset-name']
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- name: HOST_ADDRESS
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/coordinator']
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- name: TPU_SKIP_MDS_QUERY
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value: "true"
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image: us-docker.pkg.dev/cloud-tpu-v2-images-dev/pathways/gke/akshu/unsanitized_server:latest
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imagePullPolicy: Always
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name: pathways-rm
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ports:
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- containerPort: 29001
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protocol: TCP
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- containerPort: 29002
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protocol: TCP
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resources:
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limits:
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cpu: "8"
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memory: 16G
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nodeSelector:
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cloud.google.com/gke-nodepool: cpu-np
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dnsPolicy: ClusterFirstWithHostNet
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hostNetwork: true
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restartPolicy: OnFailure
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- name: worker
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replicas: 4
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template:
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metadata: {}
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spec:
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backoffLimit: 64
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completionMode: Indexed
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completions: 8
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parallelism: 8
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template:
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metadata:
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annotations:
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alpha.jobset.sigs.k8s.io/exclusive-topology: cloud.google.com/gke-nodepool
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labels:
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kueue.x-k8s.io/podset: worker
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spec:
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containers:
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- args:
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- --server_port=29005
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- --resource_manager_address=$(PATHWAYS_HEAD):29001
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- --gcs_scratch_location=gs://akshu-v5e
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- --xla_tpu_use_enhanced_launch_barrier=true
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- --logtostderr
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- --stderrthreshold=0
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- --v=1
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env:
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- name: TPU_MIN_LOG_LEVEL
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value: "0"
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- name: TF_CPP_MIN_LOG_LEVEL
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value: "0"
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- name: XCLOUD_ENVIRONMENT
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value: GCP
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- name: MEGASCALE_GRPC_ENABLE_XOR_TRACER
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value: "false"
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- name: MEGASCALE_NUM_SLICES
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/replicatedjob-replicas']
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- name: JOBSET_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.annotations['jobset.sigs.k8s.io/jobset-name']
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- name: REPLICATED_JOB_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.annotations['jobset.sigs.k8s.io/replicatedjob-name']
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- name: MEGASCALE_SLICE_ID
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/job-index']
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- name: PATHWAYS_HEAD
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/coordinator']
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- name: MEGASCALE_COORDINATOR_ADDRESS
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/coordinator']
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image: us-docker.pkg.dev/cloud-tpu-v2-images-dev/pathways/gke/akshu/unsanitized_server:latest
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imagePullPolicy: Always
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name: pathways-worker
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ports:
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- containerPort: 29005
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protocol: TCP
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- containerPort: 29006
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protocol: TCP
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- containerPort: 8471
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protocol: TCP
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- containerPort: 8080
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protocol: TCP
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resources:
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limits:
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google.com/tpu: "4"
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dnsPolicy: ClusterFirstWithHostNet
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hostNetwork: true
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nodeSelector:
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cloud.google.com/gke-tpu-accelerator: tpu-v5-lite-podslice
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cloud.google.com/gke-tpu-topology: 4x8
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restartPolicy: OnFailure

‎pathwaysutils/managed_pathways_service/pw-proxy.yaml

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apiVersion: jobset.x-k8s.io/v1alpha2
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kind: JobSet
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metadata:
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name: ${PROXY_NAME}
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spec:
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coordinator:
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replicatedJob: pathways-head
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failurePolicy:
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maxRestarts: 1
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restartStrategy: Recreate
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network:
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enableDNSHostnames: true
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publishNotReadyAddresses: true
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replicatedJobs:
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- name: pathways-head
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replicas: 1
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template:
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metadata:
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annotations:
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alpha.jobset.sigs.k8s.io/exclusive-topology: kubernetes.io/hostname
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spec:
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backoffLimit: 0
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completionMode: Indexed
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completions: 1
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parallelism: 1
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template:
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metadata:
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labels:
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kueue.x-k8s.io/podset: pathways-head
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spec:
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containers:
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- args:
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- --server_port=29000
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- --resource_manager_address=${PATHWAYS_HEAD}:${PATHWAYS_HEAD_PORT}
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- --gcs_scratch_location=${GCS_BUCKET}
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- --virtual_slices=${EXPECTED_INSTANCES}
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env:
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- name: PATHWAYS_HEAD
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valueFrom:
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fieldRef:
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fieldPath: metadata.labels['jobset.sigs.k8s.io/coordinator']
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image: us-docker.pkg.dev/cloud-tpu-v2-images-dev/pathways/gke/akshu/unsanitized_proxy_server:latest
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imagePullPolicy: Always
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name: pathways-proxy
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ports:
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- containerPort: 29000
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protocol: TCP
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resources:
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limits:
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cpu: "16"
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memory: 100G
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nodeSelector:
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cloud.google.com/gke-nodepool: cpu-np
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dnsPolicy: ClusterFirstWithHostNet
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hostNetwork: true
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restartPolicy: OnFailure

‎pathwaysutils/managed_pathways_service/run_connect_example.py

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# Copyright 2024 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Script to run JAX code on TPU with the Managed Pathways service."""
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from collections.abc import Sequence
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from absl import app
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import tpu_manager
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def main(argv: Sequence[str]) -> None:
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if len(argv) > 1:
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raise app.UsageError("Too many command-line arguments.")
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with tpu_manager.connect(
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"pw-scale-test-v5e-32",
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"cloud-tpu-multipod-dev",
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"us-south1",
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"gs://akshu-v5e",
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"pathways-akshu-s4-rw7-pathways-head-0-0.pathways-akshu-s4-rw7:29001",
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{"tpuv5e:4x8": 2},
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) as tm:
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print(tm)
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import jax
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import jax.numpy as jnp
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import pathwaysutils
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import pprint
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import time
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pathwaysutils.initialize()
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orig_matrix = jnp.zeros(5)
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print("start")
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result_matrix = orig_matrix + 1
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print("Original Random Matrix:")
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pprint.pprint(orig_matrix)
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print("\nMatrix after adding 1:")
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pprint.pprint(result_matrix)
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if __name__ == "__main__":
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app.run(main)

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