Add PyMemberDef for __dict__ on eager tensors.

This fixes dir() calls on instances of eager tensors so that it correctly
accesses the __dict__ of EagerTensorType.

Earlier it would fail due to an infinite "loop" in subtype_dict: 7e610bcdf1/Objects/typeobject.c (L2145)

get_builtin_base_with_dict will return the same type (though I'm not sure this is reasonable behavior given its name).
The __dict__ getter for the type is subtype_dict creating an infinite tail recursion.

PiperOrigin-RevId: 212020695

tensorflow/python/eager/pywrap_tensor.cc

@@ -27,6 +27,8 @@ limitations under the License.
 #include "tensorflow/core/lib/strings/strcat.h"
 #include "tensorflow/python/lib/core/ndarray_tensor.h"
 
+#include "structmember.h"  // NOLINT // For PyMemberDef
+
 // forward declare
 struct EagerTensor;
 
@@ -643,6 +645,15 @@ static PyGetSetDef EagerTensor_getseters[] = {
     {nullptr} /* Sentinel */
 };
 
+#if PY_MAJOR_VERSION < 3
+// Only used for Python2 since Python3 seems to set the __dict__ correctly.
+static PyMemberDef EagerTensor_members[] = {
+    {const_cast<char*>("__dict__"), T_OBJECT, offsetof(EagerTensor, dict),
+     READONLY},
+    {nullptr},
+};
+#endif
+
 static PyMethodDef EagerTensor_methods[] = {
     {"_numpy", (PyCFunction)EagerTensor_numpy, METH_NOARGS,
      PyDoc_STR("_numpy")},
@@ -717,7 +728,7 @@ static PyTypeObject _EagerTensorType = {
     nullptr,                            /* tp_iter */
     nullptr,                            /* tp_iternext */
     EagerTensor_methods,                /* tp_methods */
-    nullptr,                            /* tp_members */
+    EagerTensor_members,                /* tp_members */
     EagerTensor_getseters,              /* tp_getset */
     nullptr,                            /* tp_base */
     nullptr,                            /* tp_dict */
@@ -853,7 +864,7 @@ PyObject* TFE_Py_InitEagerTensor(PyObject* base_class) {
   }
   EagerTensorType->tp_dictoffset = offsetof(EagerTensor, dict);
 #else
-  _EagerTensorType.tp_base = reinterpret_cast<PyTypeObject*>(base_class);
+  _EagerTensorType.tp_base = base_class_type;
 
   if (PyType_Ready(&_EagerTensorType) < 0) {
     if (PyErr_Occurred()) return nullptr;

tensorflow/python/eager/tensor_test.py

@@ -31,6 +31,7 @@ from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import test_util
+from tensorflow.python.ops import array_ops
 
 
 def _create_tensor(value, device=None, dtype=None):
@@ -333,6 +334,19 @@ class TFETensorUtilTest(test_util.TensorFlowTestCase):
         "but tensor at index 2 has rank 0"):
       pywrap_tensorflow.TFE_Py_TensorShapeSlice([t2, t1, t3], 0)
 
+  @test_util.assert_no_new_pyobjects_executing_eagerly
+  def testTensorDir(self):
+    t = array_ops.zeros(1)
+    t.test_attr = "Test"
+
+    instance_dir = dir(t)
+    type_dir = dir(ops.EagerTensor)
+
+    # Monkey patched attributes should show up in dir(t)
+    self.assertIn("test_attr", instance_dir)
+    instance_dir.remove("test_attr")
+    self.assertEqual(instance_dir, type_dir)
+
 
 if __name__ == "__main__":
   test.main()

tensorflow/python/framework/test_util.py

@@ -465,29 +465,31 @@ def assert_no_new_pyobjects_executing_eagerly(f):
       f(self, **kwargs)
       gc.collect()
       previous_count = len(gc.get_objects())
-      collection_sizes_before = {
+      if ops.has_default_graph():
-          collection: len(ops.get_collection(collection))
+        collection_sizes_before = {
-          for collection in ops.get_default_graph().collections
+            collection: len(ops.get_collection(collection))
-      }
+            for collection in ops.get_default_graph().collections
+        }
       for _ in range(3):
         f(self, **kwargs)
       # Note that gc.get_objects misses anything that isn't subject to garbage
       # collection (C types). Collections are a common source of leaks, so we
       # test for collection sizes explicitly.
-      for collection_key in ops.get_default_graph().collections:
+      if ops.has_default_graph():
-        collection = ops.get_collection(collection_key)
+        for collection_key in ops.get_default_graph().collections:
-        size_before = collection_sizes_before.get(collection_key, 0)
+          collection = ops.get_collection(collection_key)
-        if len(collection) > size_before:
+          size_before = collection_sizes_before.get(collection_key, 0)
-          raise AssertionError(
+          if len(collection) > size_before:
-              ("Collection %s increased in size from "
+            raise AssertionError(
-               "%d to %d (current items %s).") % (collection_key, size_before,
+                ("Collection %s increased in size from "
-                                                  len(collection), collection))
+                 "%d to %d (current items %s).") %
-        # Make sure our collection checks don't show up as leaked memory by
+                (collection_key, size_before, len(collection), collection))
-        # removing references to temporary variables.
+          # Make sure our collection checks don't show up as leaked memory by
-        del collection
+          # removing references to temporary variables.
-        del collection_key
+          del collection
-        del size_before
+          del collection_key
-      del collection_sizes_before
+          del size_before
+        del collection_sizes_before
       gc.collect()
       # There should be no new Python objects hanging around.
       new_count = len(gc.get_objects())