[Gemini] remove static tracer (#2083)

colossalai/gemini/gemini_mgr.py

@@ -26,27 +26,13 @@ class GeminiManager:
         chunk_manager (ChunkManager): A ``ChunkManager`` instance.
     """
 
-    def __init__(self,
-                 placement_policy: str,
-                 chunk_manager: ChunkManager,
-                 module: Optional[torch.nn.Module] = None,
-                 use_static_memstats: bool = False) -> None:
+    def __init__(self, placement_policy: str, chunk_manager: ChunkManager) -> None:
 
         assert placement_policy in PlacementPolicyFactory.get_polocy_names()
         self.policy_name = placement_policy
         policy_cls = PlacementPolicyFactory.create(placement_policy)
         self._chunk_manager = chunk_manager
-        # self._mem_stats_collector = ChunkMemStatsCollector(chunk_manager) if policy_cls.need_mem_stats else None
-        self.use_static_memstats = use_static_memstats
-        if policy_cls.need_mem_stats:
-            if use_static_memstats:
-                assert module is not None
-                self._mem_stats_collector = StaticMemStatsCollector(module, chunk_manager)
-            else:
-                self._mem_stats_collector = ChunkMemStatsCollector(chunk_manager)
-        else:
-            self._mem_stats_collector = None
-
+        self._mem_stats_collector = ChunkMemStatsCollector(chunk_manager) if policy_cls.need_mem_stats else None
         self._placement_policy = policy_cls(chunk_manager, self._mem_stats_collector)
         self._compute_list: List[Tuple[Chunk, ...]] = []
         self._compute_idx: int = -1
@@ -60,11 +46,7 @@ class GeminiManager:
 
     def pre_iter(self, *args):
         if self._mem_stats_collector and self._warmup:
-            if self.use_static_memstats:
-                self._mem_stats_collector.init_mem_stats(*args)
-                self._warmup = False
-            else:
-                self._mem_stats_collector.start_collection()
+            self._mem_stats_collector.start_collection()
 
     def post_iter(self):
         """This function must be called when each iteration finishes

colossalai/gemini/memory_tracer/runtime_mem_tracer.py

@@ -9,6 +9,16 @@ __all__ = ['RuntimeMemTracer']
 
 
 class RuntimeMemTracer():
+    """RuntimeMemTracer for the module training using ColoParameter.
+
+    Trace non-model memory usage during fwd+bwd process.
+    It is obtained by using a tensor with the same shape as the training process as the inputs
+    and running an single fwd+bwd to trace the statistics.
+
+    NOTE()
+    1. The premise to use this tracer is that the target DNN execute the same operations at each iterations,
+    2. Module buffers are viewed as non-model data.
+    """
 
     def __init__(self, module: torch.nn.Module, dtype: torch.dtype = torch.half):
         super().__init__()

colossalai/nn/parallel/gemini_parallel.py

@@ -50,5 +50,5 @@ class GeminiDDP(ZeroDDP):
                                            hidden_dim=hidden_dim,
                                            search_range_mb=search_range_mb,
                                            min_chunk_size_mb=min_chunk_size_mb)
-        gemini_manager = GeminiManager(placement_policy, chunk_manager, module)
+        gemini_manager = GeminiManager(placement_policy, chunk_manager)
         super().__init__(module, gemini_manager, pin_memory, force_outputs_fp32)

tests/test_tensor/model/test_model.py

@@ -117,7 +117,7 @@ def run_1d_hybrid_tp(model_name):
             else:
                 output_torch = model_torch(data, label)
                 loss_torch = output_torch
-            assert torch.allclose(loss, loss_torch, rtol=1e-2)
+            assert torch.allclose(loss, loss_torch, rtol=1e-2), f"model_name {model_name} failed"
         torch.distributed.barrier()
 
         loss.backward()