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Sketch 设计中 Hint 模式参数空间配置指南,用于从任务描述中提取参数范围并生成可调优的参数空间配置

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Hint 模式:参数空间配置指南

概述

Hint 模式用于从任务描述中识别参数范围约束,生成参数空间配置(space_config),支持后续的自动调优。

Hint 语法格式

标准格式

# @hint: param in [val1, val2, ...]         → type='choice', values=[...]
# @hint: param in range(min, max, step=N)   → type='range', min=..., max=..., step=...
# @hint: param = value                      → type='fixed', value=...
# @hint: param in pow2(min_pow, max_pow)    → type='power_of_2', min_pow=..., max_pow=...
# @hint: param in pow of 2                  → type='power_of_2'

兼容格式

# @range_hint("param", start=min, end=max)  → type='range', min=..., max=...
# @elemwise_hint("param", [val1, val2])     → type='choice', values=[...]
# @elem_hint("param", [val1, val2])         → type='choice', values=[...]

示例

# @hint: batch_size in pow of 2             → {'type': 'power_of_2', 'min_pow': 3, 'max_pow': 6}  # [8, 16, 32, 64]
# @hint: dim in range(16, 65536)            → {'type': 'range', 'min': 16, 'max': 65536, 'step': 1}
# @hint: BLOCK_M in [64, 128, 256]          → {'type': 'choice', 'values': [64, 128, 256]}

Hint 提取规则

  1. 识别所有 hint:包括被注释掉的 hint(# @range_hint),都应识别并提取
  2. 完整提取:如果有多个 hint,必须全部提取,不能遗漏
  3. 格式转换:
    • 装饰器格式(如 @range_hint("param", st=8, ed=64))→ 提取括号内信息
    • 注释格式(如 # @hint: param in range(16, 65536))→ 提取冒号后声明
    • 统一转换为标准的 SPACE_CONFIG 字典格式

参数空间配置模板

"""参数空间配置"""
import torch  # 或 import mindspore as ms

# ===== 参数空间定义 =====
SPACE_CONFIG = {
    'param1': {'type': 'choice', 'values': [val1, val2, ...]},
    'param2': {'type': 'range', 'min': min_val, 'max': max_val, 'step': step_val},
    'param3': {'type': 'power_of_2', 'min_pow': min_exp, 'max_pow': max_exp},
    # ... 根据 hint 提取的所有参数
}

# ===== 元信息 =====
META_INFO = {
    'op_name': 'op_name',
    'framework': 'torch',  # 或 'mindspore'
    'param_names': ['param1', 'param2', ...]  # 参数名列表,保持顺序!
}

# ===== 输入构造函数 =====
def create_inputs(param1, param2, ...):
    """
    根据参数生成输入
    参数顺序必须与 META_INFO['param_names'] 一致
    """
    ...
    return [tensor1, tensor2, ...]

# ===== 初始化输入函数(可选)=====
def get_init_inputs():
    """如果原始代码有此函数,完整复制"""
    return []  # 或 ["auto"]

BLOCK_SIZE 配置选择原则

参数范围较小(如 M in [128, 256])

  • 避免过大 BLOCK_SIZE,推荐 [32, 64, 128]
  • 确保最小值至少能容纳一个 BLOCK

参数范围较大(如 M in range(128, 8192))

  • 提供多种选择 [64, 128, 256, 512]
  • 使用 autotune 适配不同大小

边界处理策略

选项A:使用 mask(推荐)

  • 支持任意 shape
  • 在草图注释中说明:使用 mask,支持任意 shape

选项B:不使用 mask(性能更优)

  • 要求 shape 整除 BLOCK_SIZE
  • 在草图注释中说明:M % 64 == 0(不使用 mask)

设计适用范围注释

在草图中必须添加"设计适用范围"注释:

# 设计适用范围:
# - 参数范围:M in [128, 2048], N in [128, 4096]
# - 边界处理:使用 mask / 不使用 mask(需整除)
# - BLOCK_SIZE 配置:[64, 128, 256]
# - 约束条件:如不使用 mask,M % 64 == 0

重要:

  • 无论 sketch 用几维,"设计适用范围"注释中必须对原始输入的每个维度分别说明范围
  • 不要只写总元素数的范围,要分别写每个维度的范围
  • 如果是 2 的幂次也需要标出