Replace x.initializer.run() with self.evaluate(x.initializer) in tests.

This change makes the line V2 compatible.

sed -i "s/\([_a-z0-9]*\).initializer.run()/self.evaluate(\1.initializer)/" ./third_party/tensorflow/python/kernel_tests/*.py

PiperOrigin-RevId: 324166739
Change-Id: Icf6213784063de295f0bf7b69a847e5f3820a752

tensorflow/python/kernel_tests/array_ops_test.py

@@ -800,7 +800,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
   def testExpandVariable(self):
     with self.session(use_gpu=True):
       x = variables.Variable(7, dtype=dtypes.int32)
-      x.initializer.run()
+      self.evaluate(x.initializer)
       y = x[None].eval()
       self.assertEqual(y.shape, (1,))
       self.assertAllEqual(y, (7,))

tensorflow/python/kernel_tests/cond_v2_test.py

@@ -147,7 +147,7 @@ class CondV2Test(test.TestCase):
   def testExternalControlDependencies(self):
     with ops.Graph().as_default(), self.test_session():
       v = variables.Variable(1.0)
-      v.initializer.run()
+      self.evaluate(v.initializer)
       op = v.assign_add(1.0)
 
       def true_branch():

tensorflow/python/kernel_tests/control_flow_ops_py_test.py

@@ -1505,7 +1505,7 @@ class ControlFlowTest(test.TestCase, parameterized.TestCase):
   def testWhileExternalControlDependencies(self):
     with self.cached_session():
       v = variables.Variable(0.0)
-      v.initializer.run()
+      self.evaluate(v.initializer)
       increment = v.assign_add(1.0).read_value()
 
       def body_fn(i):
@@ -1521,7 +1521,7 @@ class ControlFlowTest(test.TestCase, parameterized.TestCase):
   def testWhileExternalControlDependenciesNoInput(self):
     with self.cached_session():
       v = variables.Variable(0.0)
-      v.initializer.run()
+      self.evaluate(v.initializer)
       # TODO(apassos): figure out why the reading is necessary here.
       increment = v.assign_add(1.0).read_value()
 

tensorflow/python/kernel_tests/dense_update_ops_test.py

@@ -36,7 +36,7 @@ class AssignOpTest(test.TestCase):
     with self.cached_session(use_gpu=use_gpu):
       p = variables.Variable(x)
       assign = state_ops.assign(p, y)
-      p.initializer.run()
+      self.evaluate(p.initializer)
       new_value = self.evaluate(assign)
       return self.evaluate(p), new_value
 
@@ -45,7 +45,7 @@ class AssignOpTest(test.TestCase):
     with self.cached_session(use_gpu=use_gpu):
       p = variables.Variable(x)
       add = state_ops.assign_add(p, y)
-      p.initializer.run()
+      self.evaluate(p.initializer)
       new_value = self.evaluate(add)
       return self.evaluate(p), new_value
 
@@ -54,7 +54,7 @@ class AssignOpTest(test.TestCase):
     with self.cached_session(use_gpu=use_gpu):
       p = variables.Variable(x)
       sub = state_ops.assign_sub(p, y)
-      p.initializer.run()
+      self.evaluate(p.initializer)
       new_value = self.evaluate(sub)
       return self.evaluate(p), new_value
 

tensorflow/python/kernel_tests/embedding_ops_test.py

@@ -808,7 +808,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
         partitioner=partitioned_variables.fixed_size_partitioner(num_shards),
         initializer=initializer))
     for w in embedding_weights:
-      w.initializer.run()
+      self.evaluate(w.initializer)
     embedding_weights = [w.eval() for w in embedding_weights]
     return embedding_weights
 

tensorflow/python/kernel_tests/init_ops_test.py

@@ -116,7 +116,7 @@ class ConstantInitializersTest(test.TestCase):
       shape = [2, 3]
       x = variable_scope.get_variable(
           "x", shape=shape, initializer=init_ops.zeros_initializer())
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertAllEqual(x, np.zeros(shape))
 
   @test_util.run_deprecated_v1
@@ -125,7 +125,7 @@ class ConstantInitializersTest(test.TestCase):
       shape = [2, 3]
       x = variable_scope.get_variable(
           "x", shape=shape, initializer=init_ops.ones_initializer())
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertAllEqual(x, np.ones(shape))
 
   @test_util.run_deprecated_v1
@@ -134,7 +134,7 @@ class ConstantInitializersTest(test.TestCase):
       shape = [2, 3]
       x = variable_scope.get_variable(
           "x", shape=shape, initializer=init_ops.constant_initializer(0.0))
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertAllEqual(x, np.zeros(shape))
 
   @test_util.run_deprecated_v1
@@ -143,7 +143,7 @@ class ConstantInitializersTest(test.TestCase):
       shape = [2, 3]
       x = variable_scope.get_variable(
           "x", shape=shape, initializer=init_ops.constant_initializer(1.0))
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertAllEqual(x, np.ones(shape))
 
   @test_util.run_deprecated_v1
@@ -155,7 +155,7 @@ class ConstantInitializersTest(test.TestCase):
           shape=shape,
           dtype=dtypes.int32,
           initializer=init_ops.constant_initializer(7))
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertEqual(x.dtype.base_dtype, dtypes.int32)
       self.assertAllEqual(x, 7 * np.ones(shape, dtype=np.int32))
 
@@ -168,7 +168,7 @@ class ConstantInitializersTest(test.TestCase):
           shape=shape,
           dtype=dtypes.int32,
           initializer=init_ops.constant_initializer((10, 20, 30)))
-      x.initializer.run()
+      self.evaluate(x.initializer)
       self.assertEqual(x.dtype.base_dtype, dtypes.int32)
       self.assertAllEqual(x, [10, 20, 30])
 
@@ -176,7 +176,7 @@ class ConstantInitializersTest(test.TestCase):
     with self.cached_session(use_gpu=True):
       init = init_ops.constant_initializer(value, dtype=dtypes.int32)
       x = variable_scope.get_variable(name, shape=shape, initializer=init)
-      x.initializer.run()
+      self.evaluate(x.initializer)
 
       actual = array_ops.reshape(x, [-1]).eval()
       self.assertEqual(len(actual), len(expected))
@@ -201,7 +201,7 @@ class ConstantInitializersTest(test.TestCase):
     with self.cached_session(use_gpu=True):
       init = init_ops.constant_initializer(value, dtype=dtypes.int32)
       x = variable_scope.get_variable(name, shape=shape, initializer=init)
-      x.initializer.run()
+      self.evaluate(x.initializer)
 
       actual = array_ops.reshape(x, [-1]).eval()
       self.assertGreater(len(actual), len(expected))
@@ -931,7 +931,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
             "{}".format(i),
             shape=shape,
             initializer=init_ops.convolutional_delta_orthogonal)
-        x.initializer.run()
+        self.evaluate(x.initializer)
         y = self.evaluate(x)[1, 1, :, :]
         determinant = np.linalg.det(y)
         value += determinant
@@ -1000,7 +1000,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
             "{}".format(i),
             shape=shape,
             initializer=init_ops.convolutional_orthogonal_1d)
-        x.initializer.run()
+        self.evaluate(x.initializer)
         y = np.sum(x.eval(), axis=0)
         determinant = np.linalg.det(y)
         value += determinant
@@ -1229,7 +1229,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
             "{}".format(i),
             shape=shape,
             initializer=init_ops.convolutional_orthogonal_3d)
-        x.initializer.run()
+        self.evaluate(x.initializer)
         y = np.sum(x.eval(), axis=(0, 1, 2))
         determinant = np.linalg.det(y)
         value += determinant

tensorflow/python/kernel_tests/lookup_ops_test.py

@@ -306,7 +306,7 @@ class StaticHashTableTest(BaseLookupTableTest):
     # Init the table in the second session and verify that we do not get a
     # "Table already initialized" error.
     with session2:
-      table.initializer.run()
+      self.evaluate(table.initializer)
       self.assertAllEqual(3, self.evaluate(table.size()))
 
   @test_util.run_v2_only
@@ -812,7 +812,7 @@ class InitializeTableFromFileOpTest(BaseLookupTableTest):
       # Initialize with non existing file (old_file.txt) should fail.
       # TODO(yleon): Update message, which might change per FileSystem.
       with self.assertRaisesOpError("old_file.txt"):
-        table.initializer.run()
+        self.evaluate(table.initializer)
 
       # Initialize the model feeding the vocabulary file.
       filenames = ops.get_collection(ops.GraphKeys.ASSET_FILEPATHS)
@@ -2443,7 +2443,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
                   vocab_file, vocab_size=vocab_size), default_value),
           oov_buckets)
 
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       input_string = constant_op.constant(["brain", "salad", "surgery", "UNK"])
 
@@ -2466,7 +2466,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
           oov_buckets,
           key_dtype=dtypes.int32)
 
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       values = constant_op.constant((42, 1, -1000, 11), dtype=dtypes.int32)
 
@@ -2487,7 +2487,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
                   vocab_file, vocab_size=vocab_size, key_dtype=dtypes.int64),
               default_value), oov_buckets)
 
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       values = constant_op.constant((42, 1, -1000, 11), dtype=dtypes.int64)
 
@@ -2503,7 +2503,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
       # Set a table that only uses hash buckets, for each input value returns
       # an id calculated by fingerprint("input") mod oov_buckets.
       table = lookup_ops.IdTableWithHashBuckets(None, oov_buckets)
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       values = constant_op.constant(("brain", "salad", "surgery"))
 
@@ -2526,7 +2526,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
       # an id calculated by fingerprint("input") mod oov_buckets.
       table = lookup_ops.IdTableWithHashBuckets(
           None, oov_buckets, key_dtype=dtypes.int32)
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       input_string = constant_op.constant([42, 1, -1000], dtype=dtypes.int32)
 
@@ -2606,7 +2606,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
                   vocab_file, vocab_size=vocab_size), default_value),
           oov_buckets)
 
-      table1.initializer.run()
+      self.evaluate(table1.initializer)
 
       input_string_1 = constant_op.constant(
           ["brain", "salad", "surgery", "UNK"])
@@ -2622,7 +2622,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
       oov_buckets = 1
 
       # Underlying lookup table already initialized in previous session.
-      # No need to call table2.initializer.run()
+      # No need to call self.evaluate(table2.initializer)
       table2 = lookup_ops.IdTableWithHashBuckets(
           lookup_ops.StaticHashTable(
               lookup_ops.TextFileIdTableInitializer(
@@ -2687,7 +2687,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
           lookup_ops.StaticHashTable(
               lookup_ops.TextFileIdTableInitializer(vocab_file, vocab_size=3),
               -1), 1)
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       sp_ids = table.lookup(sp_features)
 
@@ -2716,7 +2716,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
                   (42, 1, -1000), (0, 1, 2), dtypes.int64, dtypes.int64), -1),
           1,
           key_dtype=dtypes.int32)
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       sp_ids = table.lookup(sp_features)
 
@@ -2745,7 +2745,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
                   (42, 1, -1000), (0, 1, 2), dtypes.int64, dtypes.int64), -1),
           1,
           key_dtype=dtypes.int64)
-      table.initializer.run()
+      self.evaluate(table.initializer)
 
       sp_ids = table.lookup(sp_features)
 

tensorflow/python/kernel_tests/scatter_nd_ops_test.py

@@ -150,7 +150,7 @@ class StatefulScatterNdTest(test.TestCase):
         np_scatter(new, indices, updates)
         # Scatter via tensorflow
         ref_var = variables.VariableV1(ref)
-        ref_var.initializer.run()
+        self.evaluate(ref_var.initializer)
         tf_scatter(ref_var, indices, updates).eval()
 
         # Compare
@@ -276,7 +276,7 @@ class StatefulScatterNdTest(test.TestCase):
   #     update1 = tf.compat.v1.scatter_nd_update(
   #         var, tf.constant(
   #             [[0]], dtype=tf.int64), [False])
-  #     var.initializer.run()
+  #     self.evaluate(var.initializer)
   #     session.run([update0, update1])
   #     self.assertAllEqual([False, True], self.evaluate(var))
 
@@ -292,7 +292,7 @@ class StatefulScatterNdTest(test.TestCase):
       updates = np.array([-3, -4, -5]).astype(np.float32)
       with self.cached_session(use_gpu=False):
         ref = variables.VariableV1(params)
-        ref.initializer.run()
+        self.evaluate(ref.initializer)
 
         # Indices all in range, no problem.
         indices = np.array([[2], [0], [5]])
@@ -325,7 +325,7 @@ class StatefulScatterNdTest(test.TestCase):
         initial_value=lambda: array_ops.zeros(shape=[], dtype=dtypes.float32),
         dtype=dtypes.float32)
     with self.cached_session():
-      res.initializer.run()
+      self.evaluate(res.initializer)
       with self.assertRaisesOpError("Output must be at least 1-D"):
         state_ops.scatter_nd_update(res, [[0]], [0.22]).eval()
 
@@ -340,7 +340,7 @@ class StatefulScatterNdTest(test.TestCase):
 
     expected_result = np.zeros([2, 2], dtype=np.int32)
     with self.cached_session():
-      ref.initializer.run()
+      self.evaluate(ref.initializer)
       self.assertAllEqual(expected_result, self.evaluate(scatter_update))
 
   @test_util.run_deprecated_v1
@@ -397,7 +397,7 @@ class StatefulScatterNdTest(test.TestCase):
       # We don't test the implementation; just test there's no failures.
       with self.cached_session(force_gpu=True):
         ref = variables.Variable(params)
-        ref.initializer.run()
+        self.evaluate(ref.initializer)
 
         # Indices all in range, no problem.
         indices = np.array([2, 0, 5])

tensorflow/python/kernel_tests/stack_op_test.py

@@ -306,7 +306,7 @@ class AutomaticStackingTest(test.TestCase):
     with self.session(use_gpu=True):
       v = variables.Variable(17)
       result = ops.convert_to_tensor([[0, 0, 0], [0, v, 0], [0, 0, 0]])
-      v.initializer.run()
+      self.evaluate(v.initializer)
       self.assertAllEqual([[0, 0, 0], [0, 17, 0], [0, 0, 0]],
                           self.evaluate(result))
 

tensorflow/python/kernel_tests/topk_op_test.py

@@ -240,7 +240,7 @@ class TopKBenchmark(test.Benchmark):
           v = resource_variable_ops.ResourceVariable(x)
           op = nn_ops.top_k(v, k)
         with session.Session() as sess:
-          v.initializer.run()
+          self.evaluate(v.initializer)
           r = self.run_op_benchmark(sess, op, min_iters=100, name=name)
           gb_processed_input = m * n / 1.0e9
           throughput = gb_processed_input / r["wall_time"]

tensorflow/python/kernel_tests/variables_test.py

@@ -656,14 +656,14 @@ class IsInitializedTest(test.TestCase):
       self.assertAllEqual(np.array([b"v", b"w"]), self.evaluate(uninited))
       self.evaluate(w.initializer)
       self.assertAllEqual(np.array([b"v"]), self.evaluate(uninited))
-      v.initializer.run()
+      self.evaluate(v.initializer)
       self.assertEqual(0, self.evaluate(uninited).size)
 
   def testZeroSizeVarInitialized(self):
     with ops.Graph().as_default(), self.cached_session() as sess:
       v = variables.Variable(array_ops.zeros([0, 2]), name="v")
       uninited = variables.report_uninitialized_variables()
-      v.initializer.run()  # not strictly necessary
+      self.evaluate(v.initializer)  # not strictly necessary
       self.assertEqual(0, self.evaluate(uninited).size)
 
   def testTrainingWithZeroSizeVar(self):
@@ -707,7 +707,7 @@ class ObsoleteIsInitializedTest(test.TestCase):
       self.evaluate(w.initializer)
       with self.assertRaisesOpError("Attempting to use uninitialized value"):
         inited.op.run()
-      v.initializer.run()
+      self.evaluate(v.initializer)
       inited.op.run()
 
 

tensorflow/python/kernel_tests/where_op_test.py

@@ -284,7 +284,7 @@ class WhereBenchmark(test.Benchmark):
           v = resource_variable_ops.ResourceVariable(x)
           op = array_ops.where(v)
         with session.Session(config=benchmark.benchmark_config()) as sess:
-          v.initializer.run()
+          self.evaluate(v.initializer)
           r = self.run_op_benchmark(sess, op, min_iters=100, name=name)
           gb_processed_input = m * n / 1.0e9
           # approximate size of output: m*n*p int64s for each axis.
@@ -310,9 +310,9 @@ class WhereBenchmark(test.Benchmark):
           c = resource_variable_ops.ResourceVariable(c_gen)
           op = array_ops.where(c, x, y)
         with session.Session(config=benchmark.benchmark_config()) as sess:
-          x.initializer.run()
-          y.initializer.run()
-          c.initializer.run()
+          self.evaluate(x.initializer)
+          self.evaluate(y.initializer)
+          self.evaluate(c.initializer)
           r = self.run_op_benchmark(sess, op, min_iters=100, name=name)
           # approximate size of output: m*n*2 floats for each axis.
           gb_processed = m * n * 8 / 1.0e9

tensorflow/python/kernel_tests/while_v2_test.py

@@ -174,7 +174,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
   def testExternalControlDependencies(self):
     with ops.Graph().as_default(), self.test_session():
       v = variables.Variable(1.)
-      v.initializer.run()
+      self.evaluate(v.initializer)
       op = v.assign_add(1.)
 
       def body_fn(i):  # pylint: disable=invalid-name