deploy: add dummy metadata for builtin packages (#76211)

Summary:
This adds dummy metadata for frozen builtin packages when using `torch::deploy`. This is a bit hacky but unblocks allows Huggingface transformers library to be used within `torch::deploy` which depends on `importlib.metadata.version` to detect whether torch is installed or not.

https://github.com/huggingface/transformers/blob/main/src/transformers/utils/import_utils.py#L49

Pull Request resolved: https://github.com/pytorch/pytorch/pull/76211

Test Plan: Added `importlib.metadata.version("torch")` unit test

Reviewed By: kiukchung, PaliC

Differential Revision: D35834831

Pulled By: d4l3k

fbshipit-source-id: e58365e1ada69299adea96f0ca1fe211e092dd97
(cherry picked from commit c4b4152a24dcdf359503db2112a10a88633e67b6)

torch/csrc/deploy/interpreter/builtin_registry.cpp

@@ -66,6 +66,7 @@ void BuiltinRegistry::runPreInitialization() {
 
 const char* metaPathSetupTemplate = R"PYTHON(
 import sys
+from importlib.metadata import DistributionFinder, Distribution
 # We need to register a custom meta path finder because we are registering
 # `torch._C` as a builtin module.
 #
@@ -74,12 +75,36 @@ import sys
 # are top-level imports.  Since `torch._C` is a submodule of `torch`, the
 # BuiltinImporter skips it.
 class F:
+    MODULES = {<<<DEPLOY_BUILTIN_MODULES_CSV>>>}
+
     def find_spec(self, fullname, path, target=None):
-        if fullname in [<<<DEPLOY_BUILTIN_MODULES_CSV>>>]:
+        if fullname in self.MODULES:
             # Load this module using `BuiltinImporter`, but set `path` to None
             # in order to trick it into loading our module.
             return sys.meta_path[1].find_spec(fullname, path=None, target=None)
         return None
+
+    def find_distributions(self, context=DistributionFinder.Context()):
+        modules = {"torch"} | self.MODULES
+        # Insert dummy distribution records for each builtin module so
+        # importlib.metadata.version(...) works.
+        if context.name is None:
+            for name in modules:
+                yield DummyDistribution(name)
+        if context.name in modules:
+            yield DummyDistribution(context.name)
+
+class DummyDistribution(Distribution):
+    def __init__(self, name):
+        self._metadata = {
+            "Name": name,
+            "Version": "0.0.1+fake_multipy",
+        }
+
+    @property
+    def metadata(self):
+        return self._metadata
+
 sys.meta_path.insert(0, F())
 )PYTHON";
 
@@ -87,9 +112,9 @@ void BuiltinRegistry::runPostInitialization() {
   TORCH_INTERNAL_ASSERT(Py_IsInitialized());
   std::string metaPathSetupScript(metaPathSetupTemplate);
   std::string replaceKey = "<<<DEPLOY_BUILTIN_MODULES_CSV>>>";
-  auto itr = metaPathSetupScript.find(replaceKey);
-  if (itr != std::string::npos) {
-    metaPathSetupScript.replace(itr, replaceKey.size(), getBuiltinModulesCSV());
+  size_t pos = metaPathSetupScript.find(replaceKey);
+  if (pos != std::string::npos) {
+    metaPathSetupScript.replace(pos, replaceKey.size(), getBuiltinModulesCSV());
   }
   int r = PyRun_SimpleString(metaPathSetupScript.c_str());
   TORCH_INTERNAL_ASSERT(r == 0);

torch/csrc/deploy/interpreter/builtin_registry.h

@@ -22,7 +22,7 @@
  * BuiltinRegisterer object. The constructor of BuiltinRegisterer does the real
  * registration work.
  */
-#include <gtest/gtest.h>
+#include <gtest/gtest_prod.h>
 #include <cstdarg>
 #include <memory>
 #include <unordered_map>

torch/csrc/deploy/test_deploy.cpp

@@ -451,6 +451,18 @@ result = torch.Tensor([1,2,3])
   EXPECT_TRUE(w_grad0.equal(w_grad1));
 }
 
+TEST(TorchpyTest, ImportlibMetadata) {
+  torch::deploy::InterpreterManager m(1);
+  m.registerModuleSource("importlib_test", R"PYTHON(
+from importlib.metadata import version
+
+result = version("torch")
+)PYTHON");
+  auto I = m.allInstances()[0].acquireSession();
+  auto ver = I.global("importlib_test", "result").toIValue().toString();
+  ASSERT_EQ(ver->string(), "0.0.1+fake_multipy");
+}
+
 // OSS build does not have bultin numpy support yet. Use this flag to guard the
 // test case.
 #if HAS_NUMPY