[lazy] support from_pretrained

.github/workflows/build_on_pr.yml

@@ -141,7 +141,7 @@ jobs:
     runs-on: [self-hosted, gpu]
     container:
       image: hpcaitech/pytorch-cuda:1.12.0-11.3.0
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
     timeout-minutes: 60
     defaults:
       run:
@@ -214,6 +214,7 @@ jobs:
           NCCL_SHM_DISABLE: 1
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
           TESTMON_CORE_PKGS: /__w/ColossalAI/ColossalAI/requirements/requirements.txt,/__w/ColossalAI/ColossalAI/requirements/requirements-test.txt
+          LLAMA_PATH: /data/scratch/llama-tiny
 
       - name: Store Testmon Cache
         run: |

.github/workflows/build_on_schedule.yml

@@ -13,7 +13,7 @@ jobs:
     runs-on: [self-hosted, 8-gpu]
     container:
       image: hpcaitech/pytorch-cuda:1.12.0-11.3.0
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
     timeout-minutes: 40
     steps:
       - name: Check GPU Availability # ensure all GPUs have enough memory
@@ -64,6 +64,7 @@ jobs:
         env:
           DATA: /data/scratch/cifar-10
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+          LLAMA_PATH: /data/scratch/llama-tiny
 
       - name: Notify Lark
         id: message-preparation

.github/workflows/compatiblity_test_on_dispatch.yml

@@ -50,7 +50,7 @@ jobs:
       matrix: ${{fromJson(needs.matrix_preparation.outputs.matrix)}}
     container:
       image: ${{ matrix.container }}
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
     timeout-minutes: 120
     steps:
       - name: Install dependencies
@@ -92,3 +92,4 @@ jobs:
           DATA: /data/scratch/cifar-10
           NCCL_SHM_DISABLE: 1
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+          LLAMA_PATH: /data/scratch/llama-tiny

.github/workflows/compatiblity_test_on_pr.yml

@@ -41,7 +41,7 @@ jobs:
       matrix: ${{fromJson(needs.matrix_preparation.outputs.matrix)}}
     container:
       image: ${{ matrix.container }}
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
     timeout-minutes: 120
     concurrency:
       group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-run-test-${{ matrix.container }}
@@ -87,3 +87,4 @@ jobs:
           DATA: /data/scratch/cifar-10
           NCCL_SHM_DISABLE: 1
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+          LLAMA_PATH: /data/scratch/llama-tiny

.github/workflows/compatiblity_test_on_schedule.yml

@@ -38,7 +38,7 @@ jobs:
       matrix: ${{fromJson(needs.matrix_preparation.outputs.matrix)}}
     container:
       image: ${{ matrix.container }}
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
     timeout-minutes: 120
     steps:
       - name: Install dependencies
@@ -85,6 +85,7 @@ jobs:
           DATA: /data/scratch/cifar-10
           NCCL_SHM_DISABLE: 1
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+          LLAMA_PATH: /data/scratch/llama-tiny
 
       - name: Notify Lark
         id: message-preparation

colossalai/booster/booster.py

@@ -8,6 +8,7 @@
 from torch.optim.lr_scheduler import _LRScheduler as LRScheduler
 from torch.utils.data import DataLoader
 
+import colossalai.interface.pretrained as pretrained_utils
 from colossalai.checkpoint_io import GeneralCheckpointIO
 from colossalai.interface import ModelWrapper, OptimizerWrapper
 
@@ -131,6 +132,7 @@ def boost(
         """
         # TODO(FrankLeeeee): consider multi-model and multi-optimizer case
         # TODO(FrankLeeeee): consider multi-dataloader case
+        pretrained_path = pretrained_utils.get_pretrained_path(model)
         # transform model for mixed precision
         if self.plugin:
             model, optimizer, criterion, dataloader, lr_scheduler = self.plugin.configure(
@@ -146,6 +148,12 @@ def boost(
             # when mixed_precision is specified and the plugin is not given or does not control the precision
             model, optimizer, criterion = self.mixed_precision.configure(model, optimizer, criterion)
 
+        if pretrained_path:
+            self.load_model(model, pretrained_path)
+            # clear pretrained path attr
+            orig_model = model.unwrap() if isinstance(model, ModelWrapper) else model
+            pretrained_utils.set_pretrained_path(orig_model, None)
+
         return model, optimizer, criterion, dataloader, lr_scheduler
 
     def backward(self, loss: torch.Tensor, optimizer: Optimizer) -> None:

colossalai/interface/pretrained.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+from torch.nn import Module
+
+__all__ = [
+    "get_pretrained_path",
+    "set_pretrained_path",
+]
+
+
+def get_pretrained_path(model: Module) -> Optional[str]:
+    return getattr(model, "_pretrained", None)
+
+
+def set_pretrained_path(model: Module, path: str) -> None:
+    setattr(model, "_pretrained", path)

colossalai/lazy/lazy_init.py

@@ -11,6 +11,7 @@
 from colossalai.logging import get_dist_logger
 
 from .construction import ConstructorManager
+from .pretrained import PretrainedManager
 
 import colossalai._analyzer._subclasses._meta_registration  # noqa
 
@@ -595,11 +596,13 @@ def wrapper(*args, **kwargs):
         )
 
         ConstructorManager.apply(overrides)
+        PretrainedManager.inject()
 
     def __exit__(self, exc_type, exc_val, exc_tb):
         self.tensor_cls.default_device = self.old_default_device
         LazyInitContext._replaced = False
         ConstructorManager.clear()
+        PretrainedManager.recover()
 
     @staticmethod
     def materialize(module: nn.Module, verbose: bool = False) -> nn.Module: