[MLF] Add support for multiple modules in Model Library Format

apps/microtvm/arduino/template_project/microtvm_api_server.py

@@ -214,14 +214,21 @@ def _template_model_header(self, source_dir, metadata):
         with open(source_dir / "model.h", "r") as f:
             model_h_template = Template(f.read())
 
-        assert (
-            metadata["style"] == "full-model"
+        all_module_names = []
+        for name in metadata["modules"].keys():
+            all_module_names.append(name)
+
+        assert all(
+            metadata["modules"][mod_name]["style"] == "full-model" for mod_name in all_module_names
         ), "when generating AOT, expect only full-model Model Library Format"
 
-        template_values = {
-            "workspace_size_bytes": metadata["memory"]["functions"]["main"][0][
+        workspace_size_bytes = 0
+        for mod_name in all_module_names:
+            workspace_size_bytes += metadata["modules"][mod_name]["memory"]["functions"]["main"][0][
                 "workspace_size_bytes"
-            ],
+            ]
+        template_values = {
+            "workspace_size_bytes": workspace_size_bytes,
         }
 
         with open(source_dir / "model.h", "w") as f:

python/tvm/driver/tvmc/model.py

@@ -391,9 +391,20 @@ def import_package(self, package_path: str):
             with open(temp.relpath("metadata.json")) as metadata_json:
                 metadata = json.load(metadata_json)
 
-            has_graph_executor = "graph" in metadata["executors"]
-            graph = temp.relpath("executor-config/graph/graph.json") if has_graph_executor else None
-            params = temp.relpath(f'parameters/{metadata["model_name"]}.params')
+            all_module_names = []
+            for name in metadata["modules"].keys():
+                all_module_names.append(name)
+            assert len(all_module_names) == 1, "Multiple modules in MLF is not supported."
+
+            module_name = all_module_names[0]
+            module_metdata = metadata["modules"][module_name]
+            has_graph_executor = "graph" in module_metdata["executors"]
+            graph = (
+                temp.relpath(f"executor-config/graph/{module_name}.graph")
+                if has_graph_executor
+                else None
+            )
+            params = temp.relpath(f"parameters/{module_name}.params")
 
             self.type = "mlf"
         else:

python/tvm/micro/contrib/stm32/emitter.py

@@ -482,8 +482,18 @@ def parse_library_format(self, model_library_format_path, quantization=None):
         with tarfile.TarFile(model_library_format_path) as f:
             f.extractall(extract_path)
 
+        with open(os.path.join(extract_path, "metadata.json")) as metadata_f:
+            metadata = json.load(metadata_f)
+
+        all_module_names = []
+        for name in metadata["modules"].keys():
+            all_module_names.append(name)
+        assert len(metadata["modules"]) == 1, "Multiple modules is not supported."
+
         # Extract informations from the Model Library Format
-        graph_file = os.path.join(extract_path, "executor-config", "graph", "graph.json")
+        graph_file = os.path.join(
+            extract_path, "executor-config", "graph", f"{all_module_names[0]}.graph"
+        )
         with open(graph_file, "r") as f:
             # returns JSON object as a dictionary
             graph_dict = json.load(f)