add identity_initializer

tensorflow/python/ops/init_ops.py

@@ -22,6 +22,7 @@
 from tensorflow.python.framework import dtypes
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import constant_op
+from tensorflow.python.ops import gen_array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import nn_ops
 from tensorflow.python.ops import random_ops
@@ -42,6 +43,22 @@ def _initializer(shape, dtype=dtypes.float32):
     return constant_op.constant(value, dtype=dtype, shape=shape)
   return _initializer
 
+def identity_initializer(x):
+  """Returns an initializer that generates identical tensors.
+
+  Args:
+    x: A tensor. All elements of the initialized variable
+      will be set to the elements of this tensor.
+
+  Returns:
+    An initializer that generates tensors with same shape and contents.
+  """
+  def _initializer(shape, dtype):
+    x_ = gen_array_ops.identity(x)
+    x_.get_shape().assert_is_compatible_with(shape)
+    return x_
+  return _initializer
+
 def random_uniform_initializer(minval=0.0, maxval=1.0, seed=None):
   """Returns an initializer that generates tensors with a uniform distribution.
 

tensorflow/python/ops/init_ops_test.py

@@ -0,0 +1,39 @@
+# Copyright 2015 Google Inc. 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 tensorflow.ops.init_ops."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import tensorflow as tf
+from tensorflow.python.ops import init_ops
+
+
+class IdentityInitializerTest(tf.test.TestCase):
+
+  def testIdentityInitialize(self):
+    with self.test_session():
+      v = tf.constant([1.0, 2.5], name="var")
+      x=tf.get_variable("x", [2], initializer=init_ops.identity_initializer(v))
+
+      tf.initialize_all_variables().run()
+
+      self.assertEqual(x.get_shape().as_list(), [2])
+      self.assertAllEqual(x.eval(), [1.0, 2.5])
+
+
+if __name__ == "__main__":
+  tf.test.main()