update maisi

ci/run_premerge_gpu.sh

@@ -102,19 +102,6 @@ verify_bundle() {
             fi
             # verify bundle
             python $(pwd)/ci/verify_bundle.py --b "$bundle"
-            # unzip data and do unit tests
-            DATA_DIR="$(pwd)/models/maisi_ct_generative/datasets"
-            ZIP_FILE="$DATA_DIR/all_masks_flexible_size_and_spacing_3000.zip"
-            UNZIP_DIR="$DATA_DIR/all_masks_flexible_size_and_spacing_3000"
-            if [ -f "$ZIP_FILE" ]; then
-                if [ ! -d "$UNZIP_DIR" ]; then
-                    echo "Unzipping files for MAISI Bundle..."
-                    unzip $ZIP_FILE -d $DATA_DIR
-                    echo "Unzipping complete."
-                else
-                    echo "Unzipped content already exists, continuing..."
-                fi
-            fi
             test_cmd="python $(pwd)/ci/unit_tests/runner.py --b \"$bundle\""
             if [ "$dist_flag" = "True" ]; then
                 test_cmd="torchrun $(pwd)/ci/unit_tests/runner.py --b \"$bundle\" --dist True"

ci/verify_bundle.py

@@ -21,10 +21,13 @@
     exclude_verify_shape_list,
     exclude_verify_torchscript_list,
 )
-from monai.bundle import ckpt_export, create_workflow, verify_metadata, verify_net_in_out
+from monai.bundle import ckpt_export, verify_metadata, verify_net_in_out
 from monai.bundle.config_parser import ConfigParser
+from monai.utils.module import optional_import
 from utils import download_large_files, get_json_dict
 
+create_workflow, has_create_workflow = optional_import("monai.bundle", name="create_workflow")
+
 # files that must be included in a bundle
 necessary_files_list = ["configs/metadata.json", "LICENSE"]
 # files that are preferred to be included in a bundle
@@ -246,11 +249,11 @@ def check_properties(**kwargs):
     kwargs.pop("properties_path", None)
     print(kwargs)
 
-    workflow = create_workflow(**kwargs)
     if app_properties_path is not None and os.path.isfile(app_properties_path):
         shutil.copy(app_properties_path, "ci/bundle_properties.py")
         from bundle_properties import InferProperties, MetaProperties
 
+        workflow = create_workflow(**kwargs)
         workflow.properties = {**MetaProperties, **InferProperties}
         check_result = workflow.check_properties()
         if check_result is not None and len(check_result) > 0:
@@ -287,7 +290,6 @@ def verify_bundle_properties(model_path: str, bundle: str):
             if "supported_apps" in metadata:
                 supported_apps = metadata["supported_apps"]
                 all_properties = []
-                print("vista3d sopperted apps: ", supported_apps)
                 for app, version in supported_apps.items():
                     properties_path = get_app_properties(app, version)
                     if properties_path is not None:
@@ -299,7 +301,8 @@ def verify_bundle_properties(model_path: str, bundle: str):
                     check_properties(**check_property_args)
                     print("successfully checked properties.")
             else:
-                check_properties(**check_property_args)
+                # skip property check if supported_apps is not provided
+                pass
 
 
 def verify(bundle, models_path="models", mode="full"):

models/maisi_ct_generative/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_ldm_20240318.json",
-    "version": "0.4.0",
+    "version": "0.4.1",
     "changelog": {
+        "0.4.1": "update large files",
         "0.4.0": "update to use monai 1.4, model ckpt updated, rm GenerativeAI repo, add quality check",
         "0.3.6": "first oss version"
     },
@@ -11,7 +12,7 @@
     "optional_packages_version": {
         "fire": "0.6.0",
         "nibabel": "5.2.1",
-        "tqdm": "4.66.2"
+        "tqdm": "4.66.4"
     },
     "supported_apps": {
         "maisi-nim": ""

models/maisi_ct_generative/large_files.yml

@@ -1,23 +1,45 @@
 large_files:
-  - path: "models/autoencoder_epoch273.pt"
-    url: "https://drive.google.com/file/d/1Ojw25lFO8QbHkxazdK4CgZTyp3GFNZGz/view?usp=sharing"
-  - path: "models/input_unet3d_data-all_steps1000size512ddpm_random_current_inputx_v1.pt"
-    url: "https://drive.google.com/file/d/1lklNv4MTdI_9bwFRMd98QQ7JLerR5gC_/view?usp=drive_link"
-  - path: "models/controlnet-20datasets-e20wl100fold0bc_noi_dia_fsize_current.pt"
-    url: "https://drive.google.com/file/d/1mLYeqeZ819_WpZPlAInhcWuCIHgn3QNT/view?usp=drive_link"
-  - path: "models/mask_generation_autoencoder.pt"
-    url: "https://drive.google.com/file/d/19JnX-C6QAg4RfghTwpPnj4KEWhtawpCy/view?usp=drive_link"
-  - path: "models/mask_generation_diffusion_unet.pt"
-    url: "https://drive.google.com/file/d/1yOQvlhXFGY1ZYavADM3N34vgg5AEitda/view?usp=drive_link"
-  - path: "configs/candidate_masks_flexible_size_and_spacing_3000.json"
-    url: "https://drive.google.com/file/d/1yMkH-lrAsn2YUGoTuVKNMpicziUmU-1J/view?usp=sharing"
-  - path: "configs/all_anatomy_size_condtions.json"
-    url: "https://drive.google.com/file/d/1AJyt1DSoUd2x2AOQOgM7IxeSyo4MXNX0/view?usp=sharing"
-  - path: "datasets/all_masks_flexible_size_and_spacing_3000.zip"
-    url: "https://drive.google.com/file/d/16MKsDKkHvDyF2lEir4dzlxwex_GHStUf/view?usp=sharing"
-  - path: "datasets/IntegrationTest-AbdomenCT.nii.gz"
-    url: "https://drive.google.com/file/d/1OTgt_dyBgvP52krKRXWXD3u0L5Zbj5JR/view?usp=share_link"
-  - path: "datasets/C4KC-KiTS_subset.zip"
-    url: "https://drive.google.com/file/d/1r62pLTowfrHhKW5YPl5pWygIDZSOI-VT/view?usp=sharing"
-  - path: "datasets/C4KC-KiTS_subset.json"
-    url: "https://drive.google.com/file/d/1tzpglihyZwlJcuEYJQeuB4zW8UrXyNO3/view?usp=sharing"
+- path: "models/autoencoder_epoch273.pt"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_autoencoder_epoch273_alternative.pt"
+  hash_val: "917cfb1e49631c8a713e3bb7c758fbca"
+  hash_type: "md5"
+- path: "models/input_unet3d_data-all_steps1000size512ddpm_random_current_inputx_v1.pt"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_input_unet3d_data-all_steps1000size512ddpm_random_current_inputx_v1_alternative.pt"
+  hash_val: "623bd02ff223b70d280cc994fcb70a69"
+  hash_type: "md5"
+- path: "models/controlnet-20datasets-e20wl100fold0bc_noi_dia_fsize_current.pt"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_controlnet-20datasets-e20wl100fold0bc_noi_dia_fsize_current_alternative.pt"
+  hash_val: "6c36572335372f405a0e85c760fa6dee"
+  hash_type: "md5"
+- path: "models/mask_generation_autoencoder.pt"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/mask_generation_autoencoder.pt"
+  hash_val: "b177778820f412abc9218cdb7ce3b653"
+  hash_type: "md5"
+- path: "models/mask_generation_diffusion_unet.pt"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_mask_generation_diffusion_unet_v2.pt"
+  hash_val: "e96310b960a748d68737d190712fbb80"
+  hash_type: "md5"
+- path: "configs/candidate_masks_flexible_size_and_spacing_3000.json"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/candidate_masks_flexible_size_and_spacing_3000.json"
+  hash_val: "cacb2f92b9f31270b0161412655be62b"
+  hash_type: "md5"
+- path: "configs/all_anatomy_size_condtions.json"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/all_anatomy_size_condtions.json"
+  hash_val: "fe37057ebac067fb2d17cc8cb921534b"
+  hash_type: "md5"
+- path: "datasets/all_masks_flexible_size_and_spacing_3000.zip"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_all_masks_flexible_size_and_spacing_3000.zip"
+  hash_val: "081827e9b9f55b1abbeb94682ac52d36"
+  hash_type: "md5"
+- path: "datasets/IntegrationTest-AbdomenCT.nii.gz"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_Case_00047_0000_zs0_pseudo_label_wbdm.nii.gz"
+  hash_val: "d3e7a212ac5afc51c4b7e3d6c1d6413f"
+  hash_type: "md5"
+- path: "datasets/C4KC-KiTS_subset.zip"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_C4KC-KiTS_subset.zip"
+  hash_val: "1e2279fd613ddf3a2a5f787180d171ca"
+  hash_type: "md5"
+- path: "datasets/C4KC-KiTS_subset.json"
+  url: "https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_maisi_C4KC-KiTS_subset.json"
+  hash_val: "2b8a0aebc31f5dcae5fc496d92e2beb9"
+  hash_type: "md5"

models/maisi_ct_generative/scripts/utils.py

@@ -31,13 +31,23 @@
 
 
 def unzip_dataset(dataset_dir):
-    if not os.path.exists(dataset_dir):
-        zip_file_path = dataset_dir + ".zip"
-        if not os.path.isfile(zip_file_path):
-            raise ValueError(f"Please downloaded {zip_file_path}.")
-        with zipfile.ZipFile(zip_file_path, "r") as zip_ref:
-            zip_ref.extractall(path=os.path.dirname(dataset_dir))
-        print(f"Unzipped {zip_file_path} to {dataset_dir}.")
+    if dist.is_available() and dist.is_initialized():
+        rank = dist.get_rank()
+    else:
+        rank = 0
+
+    if rank == 0:
+        if not os.path.exists(dataset_dir):
+            zip_file_path = dataset_dir + ".zip"
+            if not os.path.isfile(zip_file_path):
+                raise ValueError(f"Please download {zip_file_path}.")
+            with zipfile.ZipFile(zip_file_path, "r") as zip_ref:
+                zip_ref.extractall(path=os.path.dirname(dataset_dir))
+            print(f"Unzipped {zip_file_path} to {dataset_dir}.")
+
+    if dist.is_available() and dist.is_initialized():
+        dist.barrier()  # Synchronize all processes
+
     return