1 files changed, 44 insertions, 0 deletions
diff --git a/tensorflow/python/training/gradient_descent.py b/tensorflow/python/training/gradient_descent.py
new file mode 100644
index 0000000000..21247aacf3
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+++ b/tensorflow/python/training/gradient_descent.py
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+"""GradientDescent for TensorFlow."""
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import constant_op
+# pylint: disable=unused-import
+from tensorflow.python.ops import math_ops
+# pylint: enable=unused-import
+from tensorflow.python.training import optimizer
+from tensorflow.python.training import training_ops
+
+
+class GradientDescentOptimizer(optimizer.Optimizer):
+  """Optimizer that implements the gradient descent algorithm.
+
+  @@__init__
+  """
+
+  def __init__(self, learning_rate, use_locking=False, name="GradientDescent"):
+    """Construct a new gradient descent optimizer.
+
+    Args:
+      learning_rate: A Tensor or a floating point value.  The learning
+        rate to use.
+      use_locking: If True use locks for update operation.s
+      name: Optional name prefix for the operations created when applying
+        gradients. Defaults to "GradientDescent".
+    """
+    super(GradientDescentOptimizer, self).__init__(use_locking, name)
+    self._learning_rate = learning_rate
+
+  def _apply_dense(self, grad, var):
+    return training_ops.apply_gradient_descent(
+        var,
+        self._learning_rate_tensor,
+        grad,
+        use_locking=self._use_locking).op
+
+  def _apply_sparse(self, grad, var):
+    delta = ops.IndexedSlices(grad.values * self._learning_rate_tensor,
+                              grad.indices, grad.dense_shape)
+    return var.scatter_sub(delta, use_locking=self._use_locking)
+
+  def _prepare(self):
+    self._learning_rate_tensor = ops.convert_to_tensor(self._learning_rate,
+                                                       name="learning_rate")