deepspeedai / deepspeedai/DeepSpeed

[BUG] misc false: parameter object has no attribute "comm"

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Description

    return self._return_mics_optimizer(optimizer, timers)
  File "/home/ma-user/anaconda3/envs/PyTorch-1.8/lib/python3.7/site-packages/deepspeed/runtime/engine.py", line 1525, in _return_mics_optimizer
    communication_data_type=self.communication_data_type)
  File "/home/ma-user/anaconda3/envs/PyTorch-1.8/lib/python3.7/site-packages/deepspeed/runtime/zero/mics.py", line 396, in __init__
    self.dp_process_group = first_param.comm.param_shard_group
AttributeError: 'Parameter' object has no attribute 'comm'

I use the ds_config as follows:

    "zero_optimization": {
        "stage": 3,
        "offload_optimizer": {
            "device": "cpu",
            "pin_memory": true
        },
        "offload_param": {
            "device": "cpu",
            "pin_memory": true
        },
        "mics_shard_size": 4,
        "mics_hierarchical_params_gather": false,
        "overlap_comm": true,
        "contiguous_gradients": true,
        "stage3_max_live_parameters" : 1e9,
        "stage3_max_reuse_distance" : 1e9,
        "stage3_prefetch_bucket_size" : 5e8,
        "stage3_param_persistence_threshold" : 1e6,
        "sub_group_size" : 1e12,
        "stage3_gather_16bit_weights_on_model_save": true

what i know : i know i need to call misc_init instead of deepspeed init after I view the deepspeed.py code at 378 line.

i need to know: how and where can I call the misc_init ?

Bests

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Research direction

Start with deepspeed/runtime/engine.py around _configure_zero_optimizer and _return_mics_optimizer, then inspect deepspeed/runtime/zero/mics.py around its constructor and the misc_init path mentioned near deepspeed.py line 378. Reproduce with the supplied ZeRO-3 configuration and determine the supported initialization sequence. Done means the configuration initializes without the missing comm attribute and the required call path is clear.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
distributed-systems, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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