No need for unique variable names in eager.

PiperOrigin-RevId: 173954805

tensorflow/contrib/eager/python/metrics_test.py

@@ -121,9 +121,10 @@ class MetricsTest(test.TestCase):
     # accidentally share state.
     m1 = metrics.Mean()
     m1(0)
-    with self.assertRaises(ValueError):
     m2 = metrics.Mean()
     m2(2)
+    self.assertAllEqual(0.0, m1.result())
+    self.assertAllEqual(2.0, m2.result())
 
   def testNamesWithSpaces(self):
     # Verify two metrics with the same class and name don't

tensorflow/python/kernel_tests/resource_variable_ops_test.py

@@ -54,6 +54,18 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
                                                    0,
                                                    dtype=dtypes.int32)).run()
 
+  def testEagerNameNotIdentity(self):
+    with context.eager_mode():
+      v0 = resource_variable_ops.ResourceVariable(1.0, name="a")
+      v1 = resource_variable_ops.ResourceVariable(2.0, name="a")
+      self.assertAllEqual(v0.numpy(), 1.0)
+      self.assertAllEqual(v1.numpy(), 2.0)
+
+  def testEagerNameNotNeeded(self):
+    with context.eager_mode():
+      v0 = resource_variable_ops.ResourceVariable(1.0)
+      self.assertAllEqual(v0.numpy(), 1.0)
+
   def testReadVariableDtypeMismatchEager(self):
     with context.eager_mode():
       handle = resource_variable_ops.var_handle_op(
@@ -332,27 +344,26 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
       with self.assertRaisesRegexp(ValueError, "No attr named '_class'"):
         _ = w.value().op.get_attr("_class")
 
-  @test_util.run_in_graph_and_eager_modes()
   def testSharedName(self):
+    with self.test_session():
       v = resource_variable_ops.ResourceVariable(300.0, name="var4")
-    self.evaluate(variables.global_variables_initializer())
+      variables.global_variables_initializer().run()
 
       w = resource_variable_ops.var_handle_op(
           dtype=v.dtype.base_dtype, shape=v.get_shape(), shared_name="var4",
           # Needed in Eager since we get a unique container name by default.
           container=ops.get_default_graph()._container)
       w_read = resource_variable_ops.read_variable_op(w, v.dtype.base_dtype)
-    self.assertEqual(300.0, self.evaluate(w_read))
+      self.assertEqual(300.0, w_read.eval())
 
       x = resource_variable_ops.var_handle_op(
           dtype=v.dtype.base_dtype, shape=v.get_shape(), shared_name="var5",
           container=ops.get_default_graph()._container)
       with self.assertRaisesOpError("Resource .*/var5/.* does not exist"):
-      x_read = resource_variable_ops.read_variable_op(x, v.dtype.base_dtype)
+        resource_variable_ops.read_variable_op(x, v.dtype.base_dtype).eval()
-      self.evaluate(x_read)
 
-  @test_util.run_in_graph_and_eager_modes()
   def testSharedNameWithNamescope(self):
+    with self.test_session():
       with ops.name_scope("foo"):
         v = resource_variable_ops.ResourceVariable(300.0, name="var6")
         self.assertEqual("foo/var6", v._shared_name)  # pylint: disable=protected-access
@@ -468,25 +479,10 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
                                                    name="var8")
       var.__del__()
       with self.assertRaisesRegexp(errors.NotFoundError,
-                                   r"Resource .*\/var8\/.* does not exist."):
+                                   r"Resource .* does not exist."):
         resource_variable_ops.destroy_resource_op(var._handle,
                                                   ignore_lookup_error=False)
 
-  def testSharingViaResourceVariableObject(self):
-    with context.eager_mode():
-      _ = resource_variable_ops.ResourceVariable(1.0, name="var0")
-      with self.assertRaisesRegexp(ValueError,
-                                   "'var0' already created"):
-        _ = resource_variable_ops.ResourceVariable(2.0, name="var0")
-      with ops.Graph().as_default():
-        _ = resource_variable_ops.ResourceVariable(2.0, name="var0")
-
-  def testVariableNameMissing(self):
-    with context.eager_mode():
-      with self.assertRaisesRegexp(ValueError,
-                                   "Variables need to have explicit names"):
-        _ = resource_variable_ops.ResourceVariable(1.0)
-
 
 if __name__ == "__main__":
   test.main()

tensorflow/python/ops/resource_variable_ops.py

@@ -43,6 +43,10 @@ def _eager_safe_variable_handle(shape, dtype, shared_name, name, graph_mode):
   container = ops.get_default_graph()._container  # pylint: disable=protected-access
   if container is None:
     container = ""
+  if not graph_mode:
+    # When in eager mode use a uid for the shared_name, to prevent accidental
+    # sharing.
+    shared_name = str(ops.uid())
   handle = gen_resource_variable_ops.var_handle_op(shape=shape, dtype=dtype,
                                                    shared_name=shared_name,
                                                    name=name,
@@ -293,12 +297,6 @@ class ResourceVariable(variables.Variable):
     # Save the graph's container prefix for error checking. Reading the value of
     # the ResourceVariable from another Graph in Eager mode is an error.
     self._container_prefix = ops.get_default_graph()._container_prefix  # pylint: disable=protected-access
-    if not self._in_graph_mode and not name:
-      # TODO(ashankar,josh11b): make this unnecessary using the same
-      # logic as in layer
-      raise ValueError("Variables need to have explicit names when eager "
-                       "execution is enabled")
-
     with ops.control_dependencies(None):
       with ops.name_scope(name, "Variable", []
                           if init_from_fn else [initial_value]) as name: