[Auto-parallel] Fix sharding all_gather overlap in auto_dy #73717
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| def fuse_all_gather_hook_func(param_storage, comm_group): | ||
| @paddle.autograd.no_grad() | ||
| def fuse_comm(*_): | ||
| shard_size = param_storage._numel() // comm_group.nranks |
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这里，如果 param_storage._numel() 不能被整除，会怎么处理
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在 _build_fuse_param_view 中的 get_padded_size 确保了param_storage._numel() 是 comm_group.nranks 整数倍，故不会出现这种情况。
| task = paddle.distributed.all_gather( | ||
| param_storage, | ||
| slice_buffer, | ||
| group=self._sharding_group, |
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为什么 传了 comm_group 但实际用的 self._sharding_group？
| | ||
| def _set_sharding_overlap(self, enable_sharding_overlap, layers): | ||
| self.enable_sharding_overlap = enable_sharding_overlap | ||
| self._layers = layers |
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1、 后续要用到 self._layers 做参数查找和注册 hook，这里需要对 layers 参数做检查，比如，类型是 paddle.nn.Layer
2、这个函数本身就是 enable_sharding_overlap 为 True 时才会调用吧，是有有必要再传这个参数？
| 'param' | ||
| ] | ||
| layer = _find_layer_containing_param(first_param) | ||
| layer.register_forward_pre_hook( |
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- 这里每次调用 _find_layer_containing_param 都会遍历所有子layer，建议缓存 param2layer 的关系
- 考虑 layer 为 None 的情况
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已修改为用局部变量 param2layer = {} 缓存，已有 self._layers 为 None 时的报错提醒。
| ) | ||
| | ||
| def _set_tensor_fusion(self, enable_tensor_fusion): | ||
| self.enable_tensor_fusion = enable_tensor_fusion |
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这个函数本身就是 enable_tensor_fusion 为 True，不需再传参数 enable_tensor_fusion 了。建议：
def _enable_tensor_fusion(self):
self.enable_tensor_fusion = True
| ) | ||
| for layer in self._layers.sublayers(): | ||
| for p in layer.parameters(include_sublayers=False): | ||
| if param.name == p.name: |
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这里只能通过 name 来判断吗？是否参数名会被用户修改？
| sync_op=False, | ||
| ).wait() | ||
| | ||
| def _async_reduce_scatter(self): |
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6 participants
PR Category
Auto Parallel
PR Types
Bug fixes
Description
Launching all
all_gatherat once blocks overlap with other sync/comm ops.Fix: Prefetch 1 buffer ahead by hook to enable overlap.
Ref: Same fix in dynamic_hand #73406
Pcard-70448