Make extract_coreml_models.py buck-runnable (pytorch#18371)

Differential Revision: D97498856

Pull Request resolved: pytorch#18371

Author: derekxu

examples/apple/coreml/scripts/BUCK

@@ -3,6 +3,19 @@ load("@fbcode_macros//build_defs:build_file_migration.bzl", "fbcode_target", "no
 # targets.bzl. This file can contain fbcode-only targets.
 load("@fbcode_macros//build_defs:python_binary.bzl", "python_binary")
 
+fbcode_target(_kind = python_binary,
+    name = "extract_coreml_models",
+    srcs = [
+        "extract_coreml_models.py",
+    ],
+    main_function = "executorch.examples.apple.coreml.scripts.extract_coreml_models.main",
+    deps = [
+        "//executorch/backends/apple/coreml:executorchcoreml",
+        "//executorch/exir:schema",
+        "//executorch/exir/_serialize:lib",
+    ],
+)
+
 fbcode_target(_kind = python_binary,
     name = "export",
     srcs = [

examples/apple/coreml/scripts/extract_coreml_models.py

@@ -12,14 +12,15 @@
 from typing import Dict, List, Optional
 
 from executorch.backends.apple.coreml import executorchcoreml
-from executorch.backends.apple.coreml.compiler import CoreMLBackend
 from executorch.exir._serialize._program import deserialize_pte_binary
 from executorch.exir.schema import (
     BackendDelegate,
     BackendDelegateDataReference,
     DataLocation,
 )
 
+COREML_BACKEND_ID = "CoreMLBackend"
+
 
 def extract_coreml_models(pte_data: bytes):
     pte_file = deserialize_pte_binary(pte_data)
@@ -39,7 +40,7 @@ def extract_coreml_models(pte_data: bytes):
         [execution_plan.delegates for execution_plan in program.execution_plan], []
     )
     coreml_delegates: List[BackendDelegate] = [
-        delegate for delegate in delegates if delegate.id == CoreMLBackend.__name__
+        delegate for delegate in delegates if delegate.id == COREML_BACKEND_ID
     ]
 
     # Track extracted models to avoid duplicates (multifunction models share partitions)
@@ -109,7 +110,7 @@ def extract_coreml_models(pte_data: bytes):
         print("The model isn't delegated to Core ML.")
 
 
-if __name__ == "__main__":
+def main() -> None:
     """
     Extracts the Core ML models embedded in the ``.pte`` file and saves them to the
     file system.
@@ -127,3 +128,7 @@ def extract_coreml_models(pte_data: bytes):
     with open(model_path, mode="rb") as pte_file:
         pte_data = pte_file.read()
         extract_coreml_models(pte_data)
+
+
+if __name__ == "__main__":
+    main()