fix(ci): fix test model ckpt ci test (#518)

tests/test_utils/common_fixture.py

@@ -8,14 +8,25 @@ import torch
 from internlm.core.context import global_context as gpc
 from internlm.core.context.parallel_context import Config
 from internlm.solver.optimizer.hybrid_zero_optim import HybridZeroOptimizer
+from internlm.train.utils import create_param_groups
 from internlm.utils.common import SingletonMeta
 
-OSS_NAME = os.environ.get("OSS_BUCKET_NAME")
-OSS_IP = os.environ.get("OSS_IP")
-USER = os.environ.get("USER")
+OSS_NAME = os.environ.get("OSS_BUCKET_NAME", None)
+OSS_IP = os.environ.get("OSS_IP", None)
+USER = os.environ.get("USER", None)
 JOB_NAME = "CI_TEST"
 LOCAL_SAVE_PATH = "local:local_ckpt"
 
+if OSS_NAME is None or OSS_IP is None:
+    BOTO_SAVE_PATH = None
+    BOTO_SAVE_PATH_NO_PRFIX = None
+
+    VOLC_SAVE_PATH = None
+    VOLC_SAVE_PATH_NO_PRFIX = None
+
+    ALI_SAVE_PATH = None
+    ALI_SAVE_PATH_NO_PRFIX = None
+else:
     BOTO_SAVE_PATH = f"boto3:s3://{OSS_NAME}.{OSS_IP}/{USER}/{JOB_NAME}"
     BOTO_SAVE_PATH_NO_PRFIX = f"s3://{OSS_NAME}.{OSS_IP}/{USER}/{JOB_NAME}/"
 
@@ -31,7 +42,12 @@ ASYNC_TMP_FOLDER = "./async_tmp_folder"
 # 1B
 init_config = Config(
     dict(
-        parallel=dict(zero1=1, pipeline=dict(size=1, interleaved_overlap=False), sequence_parallel=False, tensor=1),
+        parallel=dict(
+            zero1=dict(size=1, fsdp=False),
+            pipeline=dict(size=1, interleaved_overlap=False),
+            sequence_parallel=False,
+            tensor=1,
+        ),
         model_type="INTERNLM",
         adam=dict(
             lr=1e-4,
@@ -90,8 +106,9 @@ def init_naive_optim(model):
 
 
 def init_hybrid_optim(model):
+    params = create_param_groups(model, 0.01)
     naive_optimizer = torch.optim.AdamW(
-        params=[{"params": model.parameters(), "weight_decay": 0.01}],
+        params=params,
         lr=1e-4,
         betas=(0.9, 0.95),
         eps=1e-8,

tests/test_utils/test_model_checkpoint.py

@@ -32,7 +32,7 @@ ckpt_config_list = [
         checkpoint_every=0,
         async_upload=True,
         async_upload_tmp_folder=ASYNC_TMP_FOLDER,
-        snapshot_ckpt_folder="/".join([BOTO_SAVE_PATH, "snapshot"]),
+        snapshot_ckpt_folder="/".join([BOTO_SAVE_PATH, "snapshot"]) if BOTO_SAVE_PATH is not None else None,
         oss_snapshot_freq=0,
         stop_file_path=None,
         load_model_only_folder=None,
@@ -207,6 +207,9 @@ def test_ckpt_mm(step_info, ckpt_config, init_dist_and_model):  # noqa # pylint:
     ckpt_config.checkpoint_every = checkpoint_every
     ckpt_config.oss_snapshot_freq = oss_snapshot_freq
 
+    if ckpt_config.save_ckpt_folder is None:
+        return
+
     bond_return_latest_save_path = partial(
         return_latest_save_path,
         ckpt_config.save_ckpt_folder,
@@ -298,12 +301,12 @@ def query_quit_file(rank, world_size=2):
     ckpt_config = Config(
         dict(
             enable_save_ckpt=True,
-            save_ckpt_folder=BOTO_SAVE_PATH,
+            save_ckpt_folder=LOCAL_SAVE_PATH,
             load_optimizer=True,
             checkpoint_every=0,
             async_upload=True,
             async_upload_tmp_folder=ASYNC_TMP_FOLDER,
-            snapshot_ckpt_folder="/".join([BOTO_SAVE_PATH, "snapshot"]),
+            snapshot_ckpt_folder="/".join([LOCAL_SAVE_PATH, "snapshot"]),
             oss_snapshot_freq=0,
             stop_file_path=STOP_FILE_PATH,
             load_model_only_folder=None,