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edited setup file
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‎notebooks/FederatedLearning/GCP_FederatedLearning.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 191,
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"id": "1fea8332",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 192,
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"id": "497c496b",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 193,
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"id": "dcc28585",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Converted retries value: 3 -> Retry(total=3, connect=None, read=None, redirect=None, status=None)\n",
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"Starting new HTTPS connection (1): storage.googleapis.com:443\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"https://storage.googleapis.com:443 \"GET /storage/v1/b/federated-learning-resources-zy-2?fields=name&prettyPrint=false HTTP/1.1\" 200 44\n",
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"Creating PipelineJob\n",
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"Creating PipelineJob\n",
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"PipelineJob created. Resource name: projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104\n",
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"PipelineJob created. Resource name: projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104\n",
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"To use this PipelineJob in another session:\n",
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"To use this PipelineJob in another session:\n",
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"pipeline_job = aiplatform.PipelineJob.get('projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104')\n",
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"pipeline_job = aiplatform.PipelineJob.get('projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104')\n",
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"View Pipeline Job:\n",
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"https://console.cloud.google.com/vertex-ai/locations/us-central1/pipelines/runs/example-pipeline-20250421180104?project=144763482491\n",
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"View Pipeline Job:\n",
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"https://console.cloud.google.com/vertex-ai/locations/us-central1/pipelines/runs/example-pipeline-20250421180104?project=144763482491\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n",
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"PipelineJob projects/144763482491/locations/us-central1/pipelineJobs/example-pipeline-20250421180104 current state:\n",
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"3\n"
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]
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},
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{
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"ename": "RuntimeError",
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"evalue": "Job failed with:\ncode: 9\nmessage: \" The DAG failed because some tasks failed. The failed tasks are: [initialize-model].; Job (project_id = cit-oconnellka-9999, job_id = 7211998170207748096) is failed due to the above error.; Failed to handle the job: {project_number = 144763482491, job_id = 7211998170207748096}\"\n",
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"output_type": "error",
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"traceback": [
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"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
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"\u001b[31mRuntimeError\u001b[39m Traceback (most recent call last)",
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"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[193]\u001b[39m\u001b[32m, line 14\u001b[39m\n\u001b[32m 3\u001b[39m aiplatform.init(project=\u001b[33m\"\u001b[39m\u001b[33mcit-oconnellka-9999\u001b[39m\u001b[33m\"\u001b[39m, location=\u001b[33m\"\u001b[39m\u001b[33mus-central1\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 5\u001b[39m pipeline_job = aiplatform.PipelineJob(\n\u001b[32m 6\u001b[39m display_name=\u001b[33m\"\u001b[39m\u001b[33mexample-pipeline\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 7\u001b[39m template_path=\u001b[33m\"\u001b[39m\u001b[33mexample-pipeline.json\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 11\u001b[39m }\n\u001b[32m 12\u001b[39m )\n\u001b[32m---> \u001b[39m\u001b[32m14\u001b[39m \u001b[43mpipeline_job\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Library/Python/3.12/lib/python/site-packages/google/cloud/aiplatform/pipeline_jobs.py:334\u001b[39m, in \u001b[36mPipelineJob.run\u001b[39m\u001b[34m(self, service_account, network, reserved_ip_ranges, sync, create_request_timeout, enable_preflight_validations)\u001b[39m\n\u001b[32m 310\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Run this configured PipelineJob and monitor the job until completion.\u001b[39;00m\n\u001b[32m 311\u001b[39m \n\u001b[32m 312\u001b[39m \u001b[33;03mArgs:\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 330\u001b[39m \u001b[33;03m Optional. Whether to enable preflight validations for the PipelineJob.\u001b[39;00m\n\u001b[32m 331\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 332\u001b[39m network = network \u001b[38;5;129;01mor\u001b[39;00m initializer.global_config.network\n\u001b[32m--> \u001b[39m\u001b[32m334\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_run\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 335\u001b[39m \u001b[43m \u001b[49m\u001b[43mservice_account\u001b[49m\u001b[43m=\u001b[49m\u001b[43mservice_account\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 336\u001b[39m \u001b[43m \u001b[49m\u001b[43mnetwork\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnetwork\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 337\u001b[39m \u001b[43m \u001b[49m\u001b[43mreserved_ip_ranges\u001b[49m\u001b[43m=\u001b[49m\u001b[43mreserved_ip_ranges\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 338\u001b[39m \u001b[43m \u001b[49m\u001b[43msync\u001b[49m\u001b[43m=\u001b[49m\u001b[43msync\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 339\u001b[39m \u001b[43m \u001b[49m\u001b[43mcreate_request_timeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcreate_request_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 340\u001b[39m \u001b[43m \u001b[49m\u001b[43menable_preflight_validations\u001b[49m\u001b[43m=\u001b[49m\u001b[43menable_preflight_validations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 341\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Library/Python/3.12/lib/python/site-packages/google/cloud/aiplatform/base.py:863\u001b[39m, in \u001b[36moptional_sync.<locals>.optional_run_in_thread.<locals>.wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 861\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m:\n\u001b[32m 862\u001b[39m VertexAiResourceNounWithFutureManager.wait(\u001b[38;5;28mself\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m863\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 865\u001b[39m \u001b[38;5;66;03m# callbacks to call within the Future (in same Thread)\u001b[39;00m\n\u001b[32m 866\u001b[39m internal_callbacks = []\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Library/Python/3.12/lib/python/site-packages/google/cloud/aiplatform/pipeline_jobs.py:382\u001b[39m, in \u001b[36mPipelineJob._run\u001b[39m\u001b[34m(self, service_account, network, reserved_ip_ranges, sync, create_request_timeout, enable_preflight_validations)\u001b[39m\n\u001b[32m 353\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Helper method to ensure network synchronization and to run\u001b[39;00m\n\u001b[32m 354\u001b[39m \u001b[33;03mthe configured PipelineJob and monitor the job until completion.\u001b[39;00m\n\u001b[32m 355\u001b[39m \n\u001b[32m (...)\u001b[39m\u001b[32m 372\u001b[39m \u001b[33;03m Optional. Whether to enable preflight validations for the PipelineJob.\u001b[39;00m\n\u001b[32m 373\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 374\u001b[39m \u001b[38;5;28mself\u001b[39m.submit(\n\u001b[32m 375\u001b[39m service_account=service_account,\n\u001b[32m 376\u001b[39m network=network,\n\u001b[32m (...)\u001b[39m\u001b[32m 379\u001b[39m enable_preflight_validations=enable_preflight_validations,\n\u001b[32m 380\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m382\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_block_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 384\u001b[39m \u001b[38;5;66;03m# AutoSxS view model evaluations\u001b[39;00m\n\u001b[32m 385\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m details \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m.task_details:\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Library/Python/3.12/lib/python/site-packages/google/cloud/aiplatform/pipeline_jobs.py:793\u001b[39m, in \u001b[36mPipelineJob._block_until_complete\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 790\u001b[39m \u001b[38;5;66;03m# Error is only populated when the job state is\u001b[39;00m\n\u001b[32m 791\u001b[39m \u001b[38;5;66;03m# JOB_STATE_FAILED or JOB_STATE_CANCELLED.\u001b[39;00m\n\u001b[32m 792\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._gca_resource.state \u001b[38;5;129;01min\u001b[39;00m _PIPELINE_ERROR_STATES:\n\u001b[32m--> \u001b[39m\u001b[32m793\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33mJob failed with:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m\"\u001b[39m % \u001b[38;5;28mself\u001b[39m._gca_resource.error)\n\u001b[32m 794\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 795\u001b[39m _LOGGER.log_action_completed_against_resource(\u001b[33m\"\u001b[39m\u001b[33mrun\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mcompleted\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28mself\u001b[39m)\n",
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"\u001b[31mRuntimeError\u001b[39m: Job failed with:\ncode: 9\nmessage: \" The DAG failed because some tasks failed. The failed tasks are: [initialize-model].; Job (project_id = cit-oconnellka-9999, job_id = 7211998170207748096) is failed due to the above error.; Failed to handle the job: {project_number = 144763482491, job_id = 7211998170207748096}\"\n"
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]
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}
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],
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"source": [
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"from google.cloud import aiplatform\n",
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"\n",
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]
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}
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],
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"metadata": {},
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎notebooks/FederatedLearning/scripts/fl_packages/setup.py‎

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name="fl_packages",
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version="0.1",
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packages=find_packages(),
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py_modules='fl_packages.fl_class_functions',
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install_requires=[
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"torch",
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"pandas",

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