mirror of
https://github.com/hanzo-ml/katib.git
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77 lines
2.1 KiB
YAML
77 lines
2.1 KiB
YAML
---
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apiVersion: kubeflow.org/v1beta1
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kind: Experiment
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metadata:
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name: xgb-svhn-fpga
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namespace: kubeflow
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spec:
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algorithm:
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algorithmName: random
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maxFailedTrialCount: 3
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maxTrialCount: 10
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objective:
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additionalMetricNames:
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- time
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goal: 0.99
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objectiveMetricName: accuracy
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type: maximize
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parallelTrialCount: 1
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parameters:
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- feasibleSpace:
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min: "0.00"
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max: "0.05"
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name: alpha
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parameterType: double
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- feasibleSpace:
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min: "0.1"
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max: "0.4"
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name: eta
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parameterType: double
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- feasibleSpace:
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min: "0.6"
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max: "1.0"
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name: subsample
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parameterType: double
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trialTemplate:
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primaryContainerName: training-container
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trialParameters:
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- name: alpha
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description: L1 regularization term on weights
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reference: alpha
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- name: eta
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description: Step size shrinkage used in update to prevent overfitting
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reference: eta
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- name: subsample
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description: Subsample ratio of the training instances
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reference: subsample
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trialSpec:
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apiVersion: batch/v1
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kind: Job
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spec:
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template:
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metadata:
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labels:
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inaccel/fpga: enabled
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annotations:
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inaccel/cli: |
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bitstream install --mode others https://store.inaccel.com/artifactory/bitstreams/xilinx/aws-vu9p-f1/dynamic-shell/aws/com/inaccel/xgboost/0.1/2exact
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spec:
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containers:
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- name: training-container
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image: "docker.io/inaccel/jupyter:lab"
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command:
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- python3
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- XGBoost/parameter-tuning.py
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args:
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- "--name=SVHN"
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- "--test-size=0.35"
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- "--tree-method=fpga_exact"
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- "--max-depth=10"
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- "--alpha=${trialParameters.alpha}"
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- "--eta=${trialParameters.eta}"
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- "--subsample=${trialParameters.subsample}"
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resources:
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limits:
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xilinx/aws-vu9p-f1: 1
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restartPolicy: Never
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