test anysat

Author: yawenzzzz

olmoearth_pretrain/internal/all_evals.py

@@ -400,39 +400,39 @@ def load_user_module(path: str) -> Any:
 }
 
 FT_EVAL_TASKS = {
-    "m_eurosat": DownstreamTaskConfig(
-        dataset="m-eurosat",
-        ft_batch_size=64,
-        num_workers=0,
-        pooling_type=PoolingType.MEAN,
-        norm_stats_from_pretrained=True,
-        epochs=50,
-    ),
-    "m_bigearthnet": DownstreamTaskConfig(
-        dataset="m-bigearthnet",
-        ft_batch_size=16,
-        num_workers=4,
-        pooling_type=PoolingType.MEAN,
-        norm_stats_from_pretrained=True,
-        epochs=50,
-    ),
-    "m_so2sat": DownstreamTaskConfig(
-        dataset="m-so2sat",
-        ft_batch_size=32,
-        num_workers=4,
-        pooling_type=PoolingType.MEAN,
-        norm_stats_from_pretrained=True,
-        epochs=50,
-    ),
-    "m_sa_crop_type": DownstreamTaskConfig(
-        dataset="m-sa-crop-type",
-        ft_batch_size=32,
-        num_workers=2,
-        pooling_type=PoolingType.MEAN,
-        norm_stats_from_pretrained=False,
-        norm_method=NormMethod.NORM_NO_CLIP_2_STD,
-        epochs=50,
-    ),
+    # "m_eurosat": DownstreamTaskConfig(
+    #     dataset="m-eurosat",
+    #     ft_batch_size=64,
+    #     num_workers=0,
+    #     pooling_type=PoolingType.MEAN,
+    #     norm_stats_from_pretrained=True,
+    #     epochs=50,
+    # ),
+    # "m_bigearthnet": DownstreamTaskConfig(
+    #     dataset="m-bigearthnet",
+    #     ft_batch_size=16,
+    #     num_workers=4,
+    #     pooling_type=PoolingType.MEAN,
+    #     norm_stats_from_pretrained=True,
+    #     epochs=50,
+    # ),
+    # "m_so2sat": DownstreamTaskConfig(
+    #     dataset="m-so2sat",
+    #     ft_batch_size=32,
+    #     num_workers=4,
+    #     pooling_type=PoolingType.MEAN,
+    #     norm_stats_from_pretrained=True,
+    #     epochs=50,
+    # ),
+    # "m_sa_crop_type": DownstreamTaskConfig(
+    #     dataset="m-sa-crop-type",
+    #     ft_batch_size=32,
+    #     num_workers=2,
+    #     pooling_type=PoolingType.MEAN,
+    #     norm_stats_from_pretrained=False,
+    #     norm_method=NormMethod.NORM_NO_CLIP_2_STD,
+    #     epochs=50,
+    # ),
     "mados": DownstreamTaskConfig(
         dataset="mados",
         ft_batch_size=16,