# Train supervised model: fetch binaries → hyperopt → train → evaluate → upload.
#
# Usage (any of the 8 supervised models):
#   argo submit --from=wftmpl/train-supervised -p model=tft -p binary-tag=latest
#   argo submit --from=wftmpl/train-supervised -p model=mamba2 -p binary-tag=dev-abc1234
#   argo submit --from=wftmpl/train-supervised -p model=kan -p binary-tag=latest -p train-epochs=100
#
# Supported models: tft, mamba2, tggn, tlob, liquid, kan, xlstm, diffusion
#
# Thin wrapper around training-pipeline (templateRef) with supervised defaults.
# Uses hyperopt_baseline_supervised / train_baseline_supervised / evaluate_supervised.
---
apiVersion: argoproj.io/v1alpha1
kind: WorkflowTemplate
metadata:
  name: train-supervised
  namespace: foxhunt
  labels:
    app.kubernetes.io/name: train-supervised
    app.kubernetes.io/part-of: foxhunt
    app.kubernetes.io/component: gpu-test
spec:
  entrypoint: pipeline
  serviceAccountName: argo-workflow
  podMetadata:
    labels:
      app.kubernetes.io/part-of: foxhunt
      app.kubernetes.io/component: gpu-test
      app.kubernetes.io/component: training
  securityContext:
    runAsUser: 1000
    runAsGroup: 1000
    fsGroup: 1000
  ttlStrategy:
    secondsAfterCompletion: 3600
  activeDeadlineSeconds: 28800  # 8 hours

  arguments:
    parameters:
      - name: model
        # One of: tft, mamba2, tggn, tlob, liquid, kan, xlstm, diffusion
        value: tft
      - name: commit-sha
        value: HEAD
      - name: git-branch
        value: main
      - name: gpu-pool
        value: ci-training-h100
      - name: hyperopt-trials
        value: "20"
      - name: hyperopt-epochs
        value: "8"
      - name: train-epochs
        value: "50"
      - name: symbol
        value: ES.FUT
      - name: data-dir
        value: /data/futures-baseline
      - name: mbp10-data-dir
        value: /data/futures-baseline-mbp10
      - name: trades-data-dir
        value: /data/futures-baseline-trades
      - name: tx-cost-bps
        value: "0.1"
      - name: tick-size
        value: "0.25"
      - name: spread-ticks
        value: "1.0"
      - name: initial-capital
        value: "35000"
      - name: feature-cache-dir
        value: /feature-cache
      - name: ensemble-top-k
        value: "5"
      - name: cuda-compute-cap
        value: "90"

  # Volumes required by compile-and-train steps
  volumes:
    - name: git-ssh-key
      secret:
        secretName: argo-git-ssh-key
        defaultMode: 256
    - name: training-data
      persistentVolumeClaim:
        claimName: training-data-pvc
        readOnly: true
    - name: cargo-target-cuda
      persistentVolumeClaim:
        claimName: cargo-target-cuda
    - name: feature-cache
      persistentVolumeClaim:
        claimName: feature-cache-pvc

  volumeClaimTemplates:
    - metadata:
        name: workspace
      spec:
        accessModes: ["ReadWriteOnce"]
        storageClassName: scw-bssd
        resources:
          requests:
            storage: 5Gi

  templates:
    - name: pipeline
      steps:
        - - name: compile-and-train
            templateRef:
              name: compile-and-train
              template: pipeline