[zero] find miss code (#378)

colossalai/utils/commons/__init__.py

@@ -0,0 +1,3 @@
+from .bucket_tensor_copy import BucketizedTensorCopy
+
+__all__ = ['BucketizedTensorCopy']

colossalai/utils/commons/bucket_tensor_copy.py

@@ -0,0 +1,61 @@
+import torch
+from colossalai.zero.sharded_param import ShardedParamV2
+from colossalai.utils import get_current_device
+from typing import List
+
+
+class BucketizedTensorCopy(object):
+
+    def __init__(
+        self,
+        chunk_size: int,
+    ):
+        r""" 
+        torch.nn.Parameter CPU (fp32) -> ShardedParam GPU (fp16)
+        TODO(jiaruifang) The class is a little bit hardcoded
+        I will make it more general later.
+        """
+
+        self.chunk_size = chunk_size
+        self._offset = 0
+        self._cpu_buffer = torch.empty(chunk_size, dtype=torch.float, device=torch.device("cpu:0"), pin_memory=True)
+        self._cuda_buffer = torch.empty(chunk_size,
+                                        dtype=torch.half,
+                                        device=torch.device(f"cuda:{get_current_device()}"))
+
+        self._buffered_param_list: List[ShardedParamV2] = []
+        self._numel_list = []
+
+    def copy(self, src_param: torch.nn.Parameter, target_param: ShardedParamV2):
+        assert isinstance(target_param, ShardedParamV2)
+        assert isinstance(src_param, torch.nn.Parameter)
+
+        numel = src_param.numel()
+
+        if self._offset + numel > self.chunk_size:
+            self.flush()
+
+        assert src_param.data.device.type == 'cpu'
+        self._cpu_buffer.narrow(0, self._offset, numel).copy_(src_param.data.view(-1))
+
+        self._buffered_param_list.append(target_param)
+        self._numel_list.append(numel)
+
+        self._offset += numel
+
+    def flush(self):
+        """
+        flush to cuda memory
+        """
+        self._cuda_buffer.copy_(self._cpu_buffer)
+        flush_offset = 0
+        for sparam, numel in zip(self._buffered_param_list, self._numel_list):
+            sparam.data.copy_payload(self._cpu_buffer.narrow(0, flush_offset, numel))
+            flush_offset += numel
+
+        self.reset()
+
+    def reset(self):
+        self._buffered_param_list = []
+        self._numel_list = []
+        self._offset = 0