Apply advanced DP optimizations automatically
Apply advanced dynamic programming optimizations to improve time and space complexity of DP solutions.
{
"type": "object",
"properties": {
"dpCode": { "type": "string" },
"stateDefinition": { "type": "string" },
"transitions": { "type": "string" },
"currentComplexity": { "type": "string" },
"targetComplexity": { "type": "string" },
"optimizationType": {
"type": "string",
"enum": ["auto", "convexHull", "divideConquer", "knuth", "monotonic", "space"]
}
},
"required": ["dpCode", "optimizationType"]
}
{
"type": "object",
"properties": {
"success": { "type": "boolean" },
"optimizedCode": { "type": "string" },
"optimizationApplied": { "type": "string" },
"newComplexity": { "type": "string" },
"explanation": { "type": "string" }
},
"required": ["success"]
}
PyTorch深度学习模式与最佳实践,用于构建稳健、高效且可复现的训练流程、模型架构和数据加载。