[Gemini] mapping of preop timestep and param (#2124)

colossalai/gemini/memory_tracer/memory_stats.py

@@ -1,4 +1,6 @@
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
+
+import torch
 
 from colossalai.gemini.memory_tracer import OrderedParamGenerator
 
@@ -10,6 +12,12 @@ class MemStats(object):
         Store the non model data statistics used for Gemini and ZeroOptimizer.
         """
         # p -> list of non_model data volumn visied in order.
+
+        # (preop_moment, List[param])
+        self._step_param_dict = dict()
+        self._param_step_dict = dict()
+
+        # (param, List[preop_moment])
         self.param_non_model_data_map: Dict(Any, List[int]) = {}
 
         self._model_data_cuda_list = []
@@ -23,6 +31,8 @@ class MemStats(object):
 
         self._param_runtime_order = OrderedParamGenerator()
 
+        self._preop_step = 0
+
     def param_order(self):
         if self._param_runtime_order.is_empty():
             raise RuntimeError
@@ -113,6 +123,38 @@ class MemStats(object):
         else:
             raise TypeError
 
+    def increase_preop_step(self, param_list: List[torch.nn.Parameter]):
+        """
+        the time step is increased. param list is used between current and the next
+        time step.
+
+        Args:
+            param_list (List[torch.nn.Parameter]): a list of torch paramters.
+        """
+        for p in param_list:
+            if p not in self._param_step_dict:
+                self._param_step_dict[p] = [self._preop_step]
+            else:
+                self._param_step_dict[p].append(self._preop_step)
+            self._param_runtime_order.append(p)
+        self._step_param_dict[self._preop_step] = param_list
+        self._preop_step += 1
+
+    def param_used_timestep(self, param: torch.nn.Parameter) -> Optional[List[int]]:
+        """param_used_timestep
+        get the timestep list using the param
+
+        Args:
+            param (torch.nn.Parameter): a torch param
+
+        Returns:
+            Optional[List[int]]: a list of int indicates the time step of preop hook.
+        """
+        if param not in self._param_step_dict:
+            return None
+        else:
+            return self._param_step_dict[param]
+
     def clear(self):
         self._model_data_cuda_list = []
         self._overall_cuda_list = []
@@ -124,3 +166,6 @@ class MemStats(object):
         self._non_model_data_cuda_list = []
 
         self._param_runtime_order.clear()
+        self._step_param_dict.clear()
+        self._param_step_dict.clear()
+        self._preop_step = 0

colossalai/gemini/ophooks/runtime_mem_tracer_hook.py

@@ -98,10 +98,7 @@ class ParamMemTracerHook(ColoParamOpHook):
         self._allocate_params_on_cuda(params)
         self.sample_model_data(params)
         self.mem_monitor.start()
-
+        self._memstats.increase_preop_step(params)
-        # register the order of visited.
-        for p in params:
-            self._memstats._param_runtime_order.append(p)
 
     def post_op(self, params):
         self._free_cuda_params(params)

tests/test_gemini/update/test_gemini_use_rmt.py

@@ -45,7 +45,8 @@ def run_gemini_use_rmt(placement_policy, keep_gather, model_name: str, use_grad_
             run_fwd_bwd(runtime_mem_tracer, input_ids, label, criterion, runtime_mem_tracer)
     memstats = runtime_mem_tracer.memstats()
     runtime_tracer_non_model_data = runtime_mem_tracer._memstats._non_model_data_cuda_list
-    print('runtime tracer non model data points: ', len(runtime_tracer_non_model_data))
+    print('runtime tracer: ', runtime_tracer_non_model_data)
+    print([memstats.param_used_timestep(p) for p in model.parameters()])
 
     model = GeminiDDP(model, device='cuda', placement_policy=placement_policy, search_range_mb=1, memstats=memstats)
     zero_optim = GeminiAdamOptimizer(model, lr=1e-3, initial_scale=1)