ReddRadar
Agent skill
tensorflow-trainer
TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/data-science-ml/skills/tensorflow-trainer
SKILL.md
tensorflow-trainer
Overview
TensorFlow/Keras model training skill with callbacks, distributed strategies, TensorBoard integration, and production-ready model export capabilities.
Capabilities
- Keras model training with callbacks
- Custom training loops with tf.GradientTape
- Distribution strategy configuration (MirroredStrategy, MultiWorkerMirroredStrategy, TPUStrategy)
- TensorBoard logging and visualization
- SavedModel export for TF Serving
- TFLite conversion for edge deployment
- Mixed precision training
Target Processes
- Model Training Pipeline with Experiment Tracking
- Distributed Training Orchestration
- Model Deployment Pipeline
Tools and Libraries
- TensorFlow
- Keras
- TensorBoard
- TensorFlow Serving
- TensorFlow Lite
Input Schema
{
"type": "object",
"required": ["modelConfig", "dataConfig", "trainingConfig"],
"properties": {
"modelConfig": {
"type": "object",
"properties": {
"modelPath": { "type": "string" },
"modelType": { "type": "string", "enum": ["sequential", "functional", "subclassed"] }
}
},
"dataConfig": {
"type": "object",
"properties": {
"trainPath": { "type": "string" },
"valPath": { "type": "string" },
"batchSize": { "type": "integer" },
"prefetch": { "type": "boolean" }
}
},
"trainingConfig": {
"type": "object",
"properties": {
"epochs": { "type": "integer" },
"optimizer": { "type": "string" },
"learningRate": { "type": "number" },
"loss": { "type": "string" },
"metrics": { "type": "array", "items": { "type": "string" } },
"callbacks": { "type": "array", "items": { "type": "string" } },
"distributionStrategy": { "type": "string" }
}
},
"exportConfig": {
"type": "object",
"properties": {
"savedModelPath": { "type": "string" },
"tflitePath": { "type": "string" },
"servingSignatures": { "type": "array", "items": { "type": "string" } }
}
}
}
}
Output Schema
{
"type": "object",
"required": ["status", "metrics", "modelPath"],
"properties": {
"status": {
"type": "string",
"enum": ["success", "error", "early_stopped"]
},
"metrics": {
"type": "object",
"properties": {
"loss": { "type": "number" },
"valLoss": { "type": "number" },
"accuracy": { "type": "number" },
"valAccuracy": { "type": "number" },
"epochsTrained": { "type": "integer" }
}
},
"modelPath": {
"type": "string"
},
"savedModelPath": {
"type": "string"
},
"tensorboardLogDir": {
"type": "string"
},
"history": {
"type": "object",
"description": "Training history with all metrics per epoch"
}
}
}
Usage Example
{
kind: 'skill',
title: 'Train TensorFlow model',
skill: {
name: 'tensorflow-trainer',
context: {
modelConfig: {
modelPath: 'models/cnn_model.py',
modelType: 'functional'
},
dataConfig: {
trainPath: 'data/train',
valPath: 'data/val',
batchSize: 64,
prefetch: true
},
trainingConfig: {
epochs: 50,
optimizer: 'adam',
learningRate: 0.001,
loss: 'sparse_categorical_crossentropy',
metrics: ['accuracy'],
callbacks: ['early_stopping', 'model_checkpoint', 'tensorboard']
}
}
}
}
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