Adding nesterov momentum to python momentum wrapper (#5055)

* Adding nesterov momentum to python momentum wrapper
* Fixing optimizer test after merge

python/paddle/v2/framework/optimizer.py

@@ -211,13 +211,14 @@ class MomentumOptimizer(Optimizer):
     """
     _velocity_acc_str = "velocity"
 
-    def __init__(self, learning_rate, momentum):
+    def __init__(self, learning_rate, momentum, use_nesterov=False):
         assert learning_rate is not None
         assert momentum is not None
         super(MomentumOptimizer, self).__init__()
         self.type = "momentum"
         self._learning_rate = learning_rate
         self._momentum = momentum
+        self._use_nesterov = bool(use_nesterov)
 
     def _initialize_tensors(self, block):
         assert isinstance(block, framework.Block)
@@ -259,7 +260,8 @@ class MomentumOptimizer(Optimizer):
                 "ParamOut": param_and_grad[0],
                 "VelocityOut": velocity_acc
             },
-            attrs={"mu": self._momentum})
+            attrs={"mu": self._momentum,
+                   "useNesterov": self._use_nesterov})
 
         return momentum_op
 

python/paddle/v2/framework/tests/test_optimizer.py

@@ -36,7 +36,7 @@ class TestMomentumOptimizer(unittest.TestCase):
         def get_velocity_str(self):
             return self._velocity_acc_str
 
-    def test_momentum_optimizer(self):
+    def test_vanilla_momentum_optimizer(self):
         program = framework.Program()
         block = program.global_block()
         mul_x = block.create_parameter(
@@ -60,6 +60,42 @@ class TestMomentumOptimizer(unittest.TestCase):
         self.assertEqual(len(opts), 1)
         sgd_op = opts[0]
         self.assertEqual(sgd_op.type, "momentum")
+        self.assertFalse(sgd_op.attr('useNesterov'))
+
+        # Check accumulators
+        accumulators = momentum_optimizer.get_accumulators()
+        self.assertEqual(len(accumulators), 1)
+        self.assertTrue(momentum_optimizer.get_velocity_str() in accumulators)
+        velocity_acc = accumulators[momentum_optimizer.get_velocity_str()]
+        self.assertEqual(len(velocity_acc), 1)
+        self.assertTrue(mul_x.name in velocity_acc)
+
+    def test_nesterov_momentum_optimizer(self):
+        program = framework.Program()
+        block = program.global_block()
+        mul_x = block.create_parameter(
+            dtype="float32", shape=[5, 10], lod_level=0, name="mul.x")
+        mul_y = block.create_var(
+            dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
+        mul_out = block.create_var(
+            dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
+        block.append_op(
+            type="mul",
+            inputs={"X": mul_x,
+                    "Y": mul_y},
+            outputs={"Out": mul_out},
+            attrs={"x_num_col_dims": 1})
+        momentum_optimizer = self.MockMomentum(
+            learning_rate=0.01, momentum=0.2, use_nesterov=True)
+        params_grads = append_backward_ops(mul_out)
+        self.assertEqual(len(params_grads), 1)
+        self.assertEqual(len(momentum_optimizer.get_accumulators()), 0)
+        opts = momentum_optimizer.create_optimization_pass(params_grads,
+                                                           mul_out)
+        self.assertEqual(len(opts), 1)
+        sgd_op = opts[0]
+        self.assertEqual(sgd_op.type, "momentum")
+        self.assertTrue(sgd_op.attr('useNesterov'))
 
         # Check accumulators
         accumulators = momentum_optimizer.get_accumulators()