核心概念与术语

def generate(self, prompt: str, use_model: bool = True) -> Dict[str, Any]:
    try:
        if use_model and self.model is not None:
            # 尝试使用模型生成
            generated_text = self.generate_with_model(prompt)
        else:
            # 使用规则生成
            generated_text = self.generate_with_rules(prompt)
    except Exception as e:
        # 错误处理，使用规则回退
        generated_text = self.generate_with_rules(prompt)

# 累积梯度
if (step + 1) % gradient_accumulation_steps == 0:
    optimizer.step()
    optimizer.zero_grad()

# 自动设备映射
model = AutoModelForSeq2SeqLM.from_pretrained(
    model_name,
    device_map="auto" if torch.cuda.is_available() else None
)

# 批量推理
outputs = model.generate(
    input_ids,
    max_length=max_length,
    num_return_sequences=batch_size
)

class ModelCache:
    def __init__(self):
        self._cache = {}
    
    def get_model(self, model_path):
        if model_path not in self._cache:
            self._cache[model_path] = self._load_model(model_path)
        return self._cache[model_path]

@lru_cache(maxsize=1000)
def cached_generate(prompt: str, model_config: str):
    return generate_ui(prompt, model_config)

# 注册新组件
component_renderers = {
    "topbar": self._render_topbar,
    "tabs": self._render_tabs,
    "new_component": self._render_new_component  # 新组件
}

class NewFormatRenderer:
    def render(self, dsl: Dict[str, Any]) -> str:
        # 实现新格式的渲染逻辑
        pass

# 注册新渲染器
renderers = {
    "png": UIRenderer(),
    "vue": VueRenderer(),
    "new_format": NewFormatRenderer()  # 新格式
}

def validate_dsl(dsl: Dict[str, Any]) -> bool:
    # 验证DSL结构
    if "page" not in dsl:
        return False
    
    # 验证必要字段
    page = dsl["page"]
    required_fields = ["name", "theme", "sections"]
    return all(field in page for field in required_fields)

# 训练指标
metrics = {
    "train_loss": train_loss,
    "eval_loss": eval_loss,
    "learning_rate": learning_rate,
    "epoch": epoch
}

def evaluate_model(model, test_dataset):
    # 计算评估指标
    eval_results = trainer.evaluate()
    return {
        "loss": eval_results["eval_loss"],
        "accuracy": eval_results["eval_accuracy"],
        "bleu_score": calculate_bleu_score(predictions, references)
    }

def validate_render_output(output, format_type):
    if format_type == "png":
        # 验证图片质量
        return output.size[0] > 0 and output.size[1] > 0
    elif format_type == "vue":
        # 验证Vue代码语法
        return validate_vue_syntax(output)

# 响应时间优化
@timing
def generate_ui(prompt: str):
    start_time = time.time()
    result = _generate_ui(prompt)
    end_time = time.time()
    logger.info(f"Generation time: {end_time - start_time:.2f}s")
    return result