Dontopedia

worker

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

worker has 137 facts recorded in Dontopedia across 26 references, with 17 live disagreements.

137 facts·85 predicates·26 sources·17 in dispute

Mostly:returns(17), rdf:type(9), calls(6)

Maturity scale raw canonical shape-checked rule-derived certified

Returnsin disputereturns

Inbound mentions (39)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

callsCalls(2)

createdInCreated in(2)

involvesInvolves(2)

submitsTaskSubmits Task(2)

bankedInNameOfBanked in Name of(1)

cachedByCached by(1)

calculatedByCalculated by(1)

calledByCalled by(1)

causesBanCauses Ban(1)

concernsEntityConcerns Entity(1)

coordinatesCoordinates(1)

couldBeComputedByCould Be Computed by(1)

detectsGarbageDetects Garbage(1)

exchangesHalosWithExchanges Halos With(1)

executesExecutes(1)

firstArgumentFirst Argument(1)

functionFunction(1)

hasFunctionHas Function(1)

hasMethodHas Method(1)

holdsHolds(1)

indicatePurposeIndicate Purpose(1)

instantiatedInInstantiated in(1)

intendsToIncludeIntends to Include(1)

involvesActorInvolves Actor(1)

isExchangedIs Exchanged(1)

kindOfKind of(1)

mapsMaps(1)

memberOfMember of(1)

notGoodWorkerNot Good Worker(1)

orchestratesOrchestrates(1)

performedByPerformed by(1)

preventsTamperingPrevents Tampering(1)

sendsWorkToSends Work to(1)

startsFreshOnReturnStarts Fresh on Return(1)

submitsSubmits(1)

Other facts (114)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

114 facts
PredicateValueRef
Rdf:typeRole Cluster[11]
Rdf:typeCompute Node[16]
Rdf:typeProcessing Unit[17]
Rdf:typeFunction[20]
Rdf:typeFunction[21]
Rdf:typeFunction[22]
Rdf:typeAsync Method[23]
Rdf:typeFunction[25]
Rdf:typeFunction[26]
CallsExtract Metadata[20]
CallsExtract Metadata[21]
CallsExtract Metadata[22]
CallsProcess Query[23]
CallsFeedback Loop[25]
CallsUpdate Model[26]
ComputesEntire Slice[3]
Computesentire slice[14]
ComputesLocal Metrics[15]
Return Typeextract_metadata result[20]
Return TypeMetadata Dict[21]
Return TypeNone[23]
Has ParameterDocument[21]
Has ParameterData Loader[25]
Has ParameterData Loader[26]
Must ProvideInput Output Pairs[3]
Must Providespecific input/output pairs[14]
Commits toFull Output[3]
Commits tofull output[14]
Proceeds OptimisticallySpeculative Stepping With Rollback[3]
Proceeds Optimisticallytrue[14]
Cannot Retroactively FixChallenged Points[3]
Cannot Retroactively Fixchallenged points[14]
Registers ViaPost Api Resonate Register[6]
Registers ViaWorker Registration[16]
HoldsLocal Data[15]
HoldsNeighbor Halos[15]
ParameterDocument[20]
ParameterDocument[22]
CreatesLocal Model[25]
CreatesLocal Optimizer[25]
Loads State Dict FromModel State Dict[25]
Loads State Dict FromOptimizer State Dict[25]
Returns Tuple2[25]
Returns Tupletrue[26]
Creates Local OptimizerAdam[26]
Creates Local OptimizerLocal Optimizer[26]
Computes and ReturnsResult Sha256[1]
Computes Sha256Sha256 Result Nonce[1]
Computes ResultResult[1]
Heterogeneous Capabilitiestrue[2]
Returns After BatchUpdated Slice Data[3]
Before KnowingChecked Points[3]
Returns GarbageviolatesConservationLaws[3]
Makes CommitmentHash of Full Output[3]
Computes N Steps onGrid Slice[4]
Responds to ChallengeTrue[5]
Registers ThenGets Slice Assignment[5]
Computes ThenSubmits Result[5]
Disconnects bycloses WebSocket, crashes, goes offline[6]
Should SendLeaving Message[6]
Starts Computing AfterAssignment[6]
Gets Immediate Assignment IfWork Available[6]
Submits OnlyOwned Region[7]
Computes RegionsGhost L Owned Ghost R[7]
Computes IndependentlyFull Anneal[8]
Submits TuplesTuple T Xi M Squared Sin Squared[8]
Asked Wharfinger to Feelpipe bowl just lit[9]
Went to Check and Found Two Crocodiles in Shednull[10]
Computes onGrid Slice[13]
Performs StepsN Steps[13]
After ActionBatch of Steps[14]
Cannot Modifyindividual points[14]
InitializesSlice[15]
Exchanges Halos WithWorker[15]
Exchanges Halos ViaOrchestrator Relay[15]
Can Join Mid Roundtrue[16]
Receives Immediate Assignmenttrue[16]
Reports Metric toOrchestrator[18]
CapturesRing Buffer[19]
Encodes Locally WithFfmpeg[19]
Parameter Typedocument[20]
Called byMain[21]
Caller ofExtract Metadata[22]
Infinite Looptrue[23]
Gets From QueueQuery Queue[23]
Marks Task Donetrue[23]
Prints Resulttrue[23]
Is Method ofSegmentation Service[23]
Control FlowinfiniteWhileLoop[23]
SequencegetProcessMarkPrint[23]
Queue Operationget[23]
Task CompletiontaskDone[23]
Has Type Hintsfalse[23]
Task Completion Methodtask_done[23]
While ConditionTrue (infinite)[23]
Queue Get Methodasyncio.Queue.get[23]
Task Done Callquery_queue.task_done()[23]
Async Keywordtrue[23]
Shared Resourcequery_queue[23]
Parameter Namedata_loader[24]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

computesAndReturnsblah/watt-activation/part-532
ex:result-sha256
computesSha256blah/watt-activation/part-532
ex:sha256-result-nonce
computesResultblah/watt-activation/part-532
ex:result
heterogeneousCapabilitiesblah/watt-activation/part-533
true
mustProvideblah/watt-activation/part-530
ex:input-output-pairs
returnsAfterBatchblah/watt-activation/part-530
ex:updated-slice-data
beforeKnowingblah/watt-activation/part-530
ex:checked-points
returnsblah/watt-activation/part-530
ex:results
returnsblah/watt-activation/part-530
ex:hash-of-full-output
commitsToblah/watt-activation/part-530
ex:full-output
returnsGarbageblah/watt-activation/part-530
violatesConservationLaws
returnsblah/watt-activation/part-530
ex:merkle-root
proceedsOptimisticallyblah/watt-activation/part-530
ex:speculative-stepping-with-rollback
computesblah/watt-activation/part-530
ex:entire-slice
cannotRetroactivelyFixblah/watt-activation/part-530
ex:challenged-points
makesCommitmentblah/watt-activation/part-530
ex:hash-of-full-output
computesNStepsOnblah/watt-activation/part-531
ex:grid-slice
returnsblah/watt-activation/part-531
ex:result
respondsToChallengeblah/watt-activation/part-547
ex:true
registersThenblah/watt-activation/part-547
ex:gets-slice-assignment
computesThenblah/watt-activation/part-547
ex:submits-result
registersViablah/watt-activation/part-550
ex:post-api-resonate-register
disconnectsByblah/watt-activation/part-550
closes WebSocket, crashes, goes offline
shouldSendblah/watt-activation/part-550
ex:leaving-message
startsComputingAfterblah/watt-activation/part-550
ex:assignment
getsImmediateAssignmentIfblah/watt-activation/part-550
ex:work-available
submitsOnlyblah/watt-activation/part-567
ex:owned-region
computesRegionsblah/watt-activation/part-567
ex:ghost-l-owned-ghost-r
computesIndependentlyblah/watt-activation/part-603
ex:full-anneal
submitsTuplesblah/watt-activation/part-603
ex:tuple-t-xi-m-squared-sin-squared
askedWharfingerToFeeltrove-cooktown/coloured-persons
pipe bowl just lit
wentToCheckAndFoundTwoCrocodilesInShedrosie-reynolds-massacre-connection/catchup-archive-downloads-batch-040
null
labelblah/omega/597
worker
computesOnblah/watt-activation/528
ex:grid-slice
performsStepsblah/watt-activation/528
ex:n-steps
returnsblah/watt-activation/528
ex:result
labelblah/watt-activation/527
Worker
proceedsOptimisticallyblah/watt-activation/527
true
afterActionblah/watt-activation/527
ex:batch-of-steps
returnsblah/watt-activation/527
ex:updated-slice-data
cannotModifyblah/watt-activation/527
individual points
computesblah/watt-activation/527
entire slice
returnsblah/watt-activation/527
ex:hash-of-full-output
mustProvideblah/watt-activation/527
specific input/output pairs
commitsToblah/watt-activation/527
full output
cannotRetroactivelyFixblah/watt-activation/527
challenged points
computesblah/watt-activation/539
ex:local-metrics
holdsblah/watt-activation/539
ex:local-data
holdsblah/watt-activation/539
ex:neighbor-halos
initializesblah/watt-activation/539
ex:slice
exchangesHalosWithblah/watt-activation/539
ex:worker
exchangesHalosViablah/watt-activation/539
ex:orchestrator-relay
typeblah/watt-activation/547
ex:ComputeNode
registersViablah/watt-activation/547
ex:worker-registration
canJoinMidRoundblah/watt-activation/547
true
receivesImmediateAssignmentblah/watt-activation/547
true
typeblah/watt-activation/552
ex:ProcessingUnit
reportsMetricToblah/watt-activation/559
ex:orchestrator
capturesblah/watt-activation/586
ex:ring-buffer
encodesLocallyWithblah/watt-activation/586
ex:ffmpeg
typebeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
ex:Function
labelbeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
worker
callsbeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
ex:extract_metadata
parameterbeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
ex:document
returnsbeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
ex:extract_metadata result
parameterTypebeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
document
returnTypebeam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
extract_metadata result
typebeam/59323be7-0344-48af-a986-55126680111b
ex:Function
labelbeam/59323be7-0344-48af-a986-55126680111b
worker
hasParameterbeam/59323be7-0344-48af-a986-55126680111b
ex:document
returnsbeam/59323be7-0344-48af-a986-55126680111b
ex:metadata-dict
callsbeam/59323be7-0344-48af-a986-55126680111b
ex:extract_metadata
returnTypebeam/59323be7-0344-48af-a986-55126680111b
ex:metadata-dict
calledBybeam/59323be7-0344-48af-a986-55126680111b
ex:main
typebeam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
ex:Function
parameterbeam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
ex:document
callsbeam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
ex:extract_metadata
callerOfbeam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
ex:extract_metadata
typebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
ex:AsyncMethod
labelbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
worker
infiniteLoopbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
true
getsFromQueuebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
ex:queryQueue
callsbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
ex:processQuery
marksTaskDonebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
true
printsResultbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
true
isMethodOfbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
ex:SegmentationService
controlFlowbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
infiniteWhileLoop
sequencebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
getProcessMarkPrint
queueOperationbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
get
taskCompletionbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
taskDone
hasTypeHintsbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
false
taskCompletionMethodbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
task_done
whileConditionbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
True (infinite)
queueGetMethodbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
asyncio.Queue.get
taskDoneCallbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
query_queue.task_done()
asyncKeywordbeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
true
returnTypebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
None
sharedResourcebeam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
query_queue
parameterNamebeam/9151b445-41b5-4d53-900d-4199adc168c1
data_loader
typebeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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callsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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returnsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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returnsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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createsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
ex:local_model
createsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
ex:local_optimizer
loadsStateDictFrombeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
ex:model_state_dict
loadsStateDictFrombeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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2
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ex:stateDicts
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ex:modelStateDict
returnsbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
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isolatedEnvironmentbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
true
parallelUnitbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
true
runsInbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
ex:separateProcess
producesbeam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
ex:localStates
typebeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:Function
hasParameterbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:data_loader
createsLocalModelbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:MyModel
createsLocalOptimizerbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:Adam
callsbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
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true
isolatedExecutionbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
true
returnsbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:tuple
parallelWorkerbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
true
executesInbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:ProcessPoolExecutor
2024-03-02
typeclaims/session/smoke:2026-06-04:1
ex:RoleCluster
2024-03-02
labelclaims/session/smoke:2026-06-04:1
worker

References (26)

26 references
  1. [1]Part 5323 facts
    ctx:discord/blah/watt-activation/part-532
  2. [2]Part 5331 fact
    ctx:discord/blah/watt-activation/part-533
  3. [3]Part 53012 facts
    ctx:discord/blah/watt-activation/part-530
  4. [4]Part 5312 facts
    ctx:discord/blah/watt-activation/part-531
  5. [5]Part 5473 facts
    ctx:discord/blah/watt-activation/part-547
  6. [6]Part 5505 facts
    ctx:discord/blah/watt-activation/part-550
  7. [7]Part 5672 facts
    ctx:discord/blah/watt-activation/part-567
  8. [8]Part 6032 facts
    ctx:discord/blah/watt-activation/part-603
  9. ctx:genes/trove-cooktown/coloured-persons
  10. ctx:genes/rosie-reynolds-massacre-connection/catchup-archive-downloads-batch-040
  11. ctx:memory/claims/session/smoke:2026-06-04:1
    • full textctx:memory/claims/session/smoke:2026-06-04:1
      text/plain293 Bdoc:memory/claims/session/smoke:2026-06-04:1
      Show excerpt
      On 2 March 2024, Mariana Velasco joined Helix Robotics in Lyon as a senior control engineer. She had previously led the navigation team at Aurora Mobility for three years, and she speaks French, Spanish and English. Her manager is Tomas Bra
  12. [12]5971 fact
    ctx:discord/blah/omega/597
    • full textomega-597
      text/plain3 KBdoc:agent/omega-597/a99e2827-2975-4e37-a903-b333b5004d67
      Show excerpt
      [2025-12-05 19:09] omega [bot]: Got it — issue #688 created. I’ll open the PR now as ready for review (not a draft) on branch feat/schema-suprema, target main, include the migrations + /api/schema-requests skeleton + worker + jest placehold
  13. [13]5283 facts
    ctx:discord/blah/watt-activation/528
    • full textwatt-activation-528
      text/plain1 KBdoc:agent/watt-activation-528/d9997e5c-02a8-42fa-90d0-6a40513d3b21
      Show excerpt
      [2026-03-23 02:24] xenonfun: Approach 1: Redundant computation with voting (SETI@home style) The simplest: send the same grid slice to 2-3 workers, compare results. If they agree within floating-point tolerance (~1e-4), accept. If they
  14. [14]52710 facts
    ctx:discord/blah/watt-activation/527
    • full textwatt-activation-527
      text/plain3 KBdoc:agent/watt-activation-527/0be3d479-52b6-4409-a2a0-c599ac4b236c
      Show excerpt
      [2026-03-23 02:18] xenonfun: Practical tricks for WAN async: 1. Speculative stepping with rollback: Worker proceeds optimistically. When the real halo arrives, if the difference exceeds a threshold, re-compute the boundary strip (only
  15. [15]5396 facts
    ctx:discord/blah/watt-activation/539
    • full textwatt-activation-539
      text/plain3 KBdoc:agent/watt-activation-539/fc9eb1c3-c75c-4d70-897c-3146da8496bb
      Show excerpt
      [2026-03-23 04:24] xenonfun: ``` ⏺ Yes — the orchestrator currently holds the full global field in memory (field_data: Vec<f32>, N×6 floats). For a 16M-point grid that's 384 MB. For a billion-point grid it'd be 24 GB. But it doesn't ac
  16. [16]5474 facts
    ctx:discord/blah/watt-activation/547
    • full textwatt-activation-547
      text/plain2 KBdoc:agent/watt-activation-547/5df4b8d4-896d-4a30-bbd9-886176abaf0c
      Show excerpt
      [2026-03-23 06:10] xenonfun: ⏺ Yes — the current design handles that naturally: Joining: A worker registers at any time via POST /api/resonate/register, gets an immediate assignment if there's work available, and starts computing. Mid-
  17. [17]5521 fact
    ctx:discord/blah/watt-activation/552
    • full textwatt-activation-552
      text/plain2 KBdoc:agent/watt-activation-552/c4f0a098-8fce-4f71-b1dc-3ff84647b488
      Show excerpt
      [2026-03-23 06:46] xenonfun: ``` ⏺ Right now it's lossless only. The encode/decode has three modes but they're not wired up as user options: ┌──────────┬────────────────┬──────────────────────────────────┐ │ Mode │ Error
  18. [18]5591 fact
    ctx:discord/blah/watt-activation/559
    • full textwatt-activation-559
      text/plain3 KBdoc:agent/watt-activation-559/bbe3ab7e-095c-4003-be7c-af6b9d5c98c4
      Show excerpt
      [2026-03-23 08:34] xenonfun: ``` All 3 agents confirmed complete. Everything integrated and verified — 1,166 tests, zero failures. Now to your P2P and latency questions. Yes — direct peer-to-peer halo exchange makes perfect sense. Ri
  19. [19]5862 facts
    ctx:discord/blah/watt-activation/586
    • full textwatt-activation-586
      text/plain3 KBdoc:agent/watt-activation-586/0edfdeb1-609b-4200-8ce0-a20b85f76d99
      Show excerpt
      [2026-04-01 12:59] xenonfun: Next up: ``` FFmpeg Sidecar Video Streaming Context The current heatmap streaming sends raw/compressed binary frames over WebSocket — 100KB-2MB per frame. This works well on LAN/1Gbps but fails for remote o
  20. ctx:claims/beam/956d1ee7-8b5b-4c69-8872-b3e16e4e4d1e
  21. ctx:claims/beam/59323be7-0344-48af-a986-55126680111b
  22. ctx:claims/beam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
    • full textbeam-chunk
      text/plain1 KBdoc:beam/0056782a-c15a-4862-87e7-83bbf2c2b1a0
      Show excerpt
      - **Profiling**: Use profiling tools like `cProfile` to identify bottlenecks in your code and further optimize it. - **Parallelism**: Depending on the nature of the `extract_metadata` function, you might also consider using asynchronous pr
  23. ctx:claims/beam/f3d8a17a-ceb3-4261-a329-bc8bd3818ae1
  24. ctx:claims/beam/9151b445-41b5-4d53-900d-4199adc168c1
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9151b445-41b5-4d53-900d-4199adc168c1
      Show excerpt
      model = MyModel().to(device) optimizer = optim.Adam(model.parameters(), lr=0.001) # Define the update logic def update_model(model, optimizer, data_loader): model.train() for data, _ in data_loader: data = data.to(device)
  25. ctx:claims/beam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
    • full textbeam-chunk
      text/plain1 KBdoc:beam/ba5a30a2-7fbc-4f67-963e-8bb558a62cdc
      Show excerpt
      data = data.to(device) optimizer.zero_grad() outputs = model(data) loss = nn.MSELoss()(outputs, data) loss.backward() optimizer.step() # Generate synthetic data num_queries = 3500 batch_size
  26. ctx:claims/beam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
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      text/plain1 KBdoc:beam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
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      optimizer = optim.Adam(model.parameters(), lr=0.001) # Define the update logic def update_model(model, optimizer, data_loader): model.train() for data, _ in data_loader: data = data.to(device) optimizer.zero_grad()

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