[gemini] improve compatibility and add static placement policy (#4479)

* [gemini] remove distributed-related part from colotensor (#4379)

* [gemini] remove process group dependency

* [gemini] remove tp part from colo tensor

* [gemini] patch inplace op

* [gemini] fix param op hook and update tests

* [test] remove useless tests

* [test] remove useless tests

* [misc] fix requirements

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [misc] update requirements

* [gemini] refactor gemini optimizer and gemini ddp (#4398)

* [gemini] update optimizer interface

* [gemini] renaming gemini optimizer

* [gemini] refactor gemini ddp class

* [example] update gemini related example

* [example] update gemini related example

* [plugin] fix gemini plugin args

* [test] update gemini ckpt tests

* [gemini] fix checkpoint io

* [example] fix opt example requirements

* [example] fix opt example

* [example] fix opt example

* [example] fix opt example

* [gemini] add static placement policy (#4443)

* [gemini] add static placement policy

* [gemini] fix param offload

* [test] update gemini tests

* [plugin] update gemini plugin

* [plugin] update gemini plugin docstr

* [misc] fix flash attn requirement

* [test] fix gemini checkpoint io test

* [example] update resnet example result (#4457)

* [example] update bert example result (#4458)

* [doc] update gemini doc (#4468)

* [example] update gemini related examples (#4473)

* [example] update gpt example

* [example] update dreambooth example

* [example] update vit

* [example] update opt

* [example] update palm

* [example] update vit and opt benchmark

* [hotfix] fix bert in model zoo (#4480)

* [hotfix] fix bert in model zoo

* [test] remove chatglm gemini test

* [test] remove sam gemini test

* [test] remove vit gemini test

* [hotfix] fix opt tutorial example (#4497)

* [hotfix] fix opt tutorial example

* [hotfix] fix opt tutorial example

colossalai/zero/gemini/chunk/search_utils.py

@@ -4,6 +4,7 @@ from typing import Dict, List, Optional, Tuple
 import numpy as np
 import torch.distributed as dist
 import torch.nn as nn
+from torch.distributed import ProcessGroup
 
 from colossalai.tensor import ColoParameter
 from colossalai.utils import is_ddp_ignored
@@ -59,7 +60,7 @@ def _get_unused_byte(size_list: List[int], chunk_size: int) -> int:
     return left + acc
 
 
-def _tensor_numel(local_param: ColoParameter, strict_ddp_flag: bool) -> int:
+def _tensor_numel(local_param: ColoParameter) -> int:
     """_tensor_numel
 
     Get the number of elements of a tensor.
@@ -71,15 +72,12 @@ def _tensor_numel(local_param: ColoParameter, strict_ddp_flag: bool) -> int:
     Returns:
         int: the number of elements.
     """
-    if strict_ddp_flag and type(local_param) is ColoParameter:
-        return local_param.numel_global()
-    else:
-        # if local_param is not ColoParameter, we assume it's replicated
-        return local_param.numel()
+    # TODO(ver217): support dtensor here
+    return local_param.numel()
 
 
 def classify_params_by_dp_degree(param_order: OrderedParamGenerator,
-                                 strict_ddp_flag: bool = False) -> Dict[int, List[ColoParameter]]:
+                                 process_group: ProcessGroup) -> Dict[int, List[ColoParameter]]:
     """classify_params_by_dp_degree
 
     Classify the parameters by their dp degree
@@ -97,13 +95,7 @@ def classify_params_by_dp_degree(param_order: OrderedParamGenerator,
         # assert isinstance(param, ColoParameter), "please init model in the ColoInitContext"
         if is_ddp_ignored(param):
             continue
-
-        if strict_ddp_flag or type(param) is not ColoParameter:
-            # if model is not initialized with ColoInitContext, we assume it's replicated
-            # TODO(ver217): integrate DTensor
-            param_key = dist.get_world_size()
-        else:
-            param_key = param.process_group.dp_world_size()
+        param_key = dist.get_world_size(process_group)
 
         if param_key not in params_dict:
             params_dict[param_key] = []
@@ -119,6 +111,7 @@ def search_chunk_configuration(
         min_chunk_size_m: float = 32,
         filter_exlarge_params: bool = True,
         strict_ddp_flag: bool = False,
+        process_group: Optional[ProcessGroup] = None,
         memstas: Optional[MemStats] = None) -> Tuple[Dict, int, int]:
     """search_chunk_configuration
 
@@ -149,7 +142,7 @@ def search_chunk_configuration(
     min_chunk_size = round(min_chunk_size_m * 1024**2)
     assert search_range >= 0
 
-    params_dict = classify_params_by_dp_degree(param_order, strict_ddp_flag)
+    params_dict = classify_params_by_dp_degree(param_order, process_group)
     size_lcm = np.lcm.reduce(list(params_dict.keys()))
     config_dict: Dict[int, Dict] = dict()
     total_param_size = 0
@@ -157,7 +150,7 @@ def search_chunk_configuration(
     size_dict: Dict[int, List[int]] = dict()
     for dp_degree in params_dict:
         params_list = params_dict[dp_degree]
-        size_list = [_tensor_numel(p, strict_ddp_flag) for p in params_list]
+        size_list = [_tensor_numel(p) for p in params_list]
         group_acc_size = sum(size_list)
         total_param_size += group_acc_size