Enable constant propagation across Enter nodes, but only if is_constant is true.

Don't propagate constants with control dependencies through Merge nodes.

PiperOrigin-RevId: 191663396

1 files changed, 69 insertions, 0 deletions

diff --git a/tensorflow/python/grappler/constant_folding_test.py b/tensorflow/python/grappler/constant_folding_test.py
new file mode 100644
index 0000000000..ab1d0ed25b
--- /dev/null
+++ b/tensorflow/python/grappler/constant_folding_test.py
@@ -0,0 +1,69 @@
+# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for Grappler Constant Folding."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+
+from tensorflow.python.client import session
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import control_flow_ops
+from tensorflow.python.ops import functional_ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.platform import test
+
+
+class ConstantFoldingTest(test.TestCase):
+
+  # See b/76008022.
+  def testScanInsideWhile(self):
+
+    def loop_cond(idx_step, *unused_args):
+      return idx_step < 1
+
+    def loop_body(idx_step, y):
+      x = array_ops.zeros([10, 20, 30], dtype=dtypes.float32)
+      x = functional_ops.scan(
+          math_ops.add,
+          x,
+          initializer=array_ops.zeros([20, 30], dtype=dtypes.float32),
+          back_prop=False,
+          parallel_iterations=1)
+
+      with ops.device('/cpu:0'):
+        y = array_ops.identity(x)
+
+        return idx_step + 1, y
+
+    if test.is_gpu_available(cuda_only=True):
+      init_y = array_ops.zeros([10, 20, 30], dtype=dtypes.float32)
+      _, y = control_flow_ops.while_loop(
+          loop_cond,
+          loop_body,
+          loop_vars=[0, init_y],
+          back_prop=False,
+          parallel_iterations=1)
+      with session.Session() as sess:
+        y_v = sess.run(y)
+        self.assertAllEqual(np.zeros([10, 20, 30]), y_v)
+
+
+if __name__ == '__main__':
+  test.main()