Merge pull request #13837 from velconia/add_pyramid_dnn_support

Add margin_rank_loss_op to python

paddle/fluid/API.spec

@@ -127,6 +127,7 @@ paddle.fluid.layers.relu ArgSpec(args=['x', 'name'], varargs=None, keywords=None
 paddle.fluid.layers.log ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.crop ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None))
 paddle.fluid.layers.rank_loss ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.layers.margin_rank_loss ArgSpec(args=['label', 'left', 'right', 'margin', 'name'], varargs=None, keywords=None, defaults=(0.1, None))
 paddle.fluid.layers.elu ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(1.0, None))
 paddle.fluid.layers.relu6 ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(6.0, None))
 paddle.fluid.layers.pow ArgSpec(args=['x', 'factor', 'name'], varargs=None, keywords=None, defaults=(1.0, None))

python/paddle/fluid/layers/nn.py

@@ -107,6 +107,7 @@ __all__ = [
     'log',
     'crop',
     'rank_loss',
+    'margin_rank_loss',
     'elu',
     'relu6',
     'pow',
@@ -5827,6 +5828,54 @@ def rank_loss(label, left, right, name=None):
     return out
 
 
+def margin_rank_loss(label, left, right, margin=0.1, name=None):
+    """
+    Margin Ranking Loss Layer for ranking problem,
+    which compares left score and right score passed in.
+    The ranking loss can be defined as following equation:
+
+    .. math::
+
+        rank\_loss &= max(0, -label * (left - right) + margin)
+
+    Args:
+       label (Variable): Indicates whether the left is ranked higher than the right or not.
+       left (Variable): Ranking score for left.
+       right (Variable): Ranking score for right.
+       margin (float): Indicates the given margin.
+       name (str|None): A name for this layer (optional). If set None, the layer
+                       will be named automatically.
+    Returns:
+       Variable: The ranking loss.
+    Raises:
+       ValueError: Any of label, left, and right is not a Variable.
+    Examples:
+        .. code-block:: python
+           label = fluid.layers.data(name="label", shape=[4, 1], dtype="float32")
+           left = fluid.layers.data(name="left", shape=[4, 1], dtype="float32")
+           right = fluid.layers.data(name="right", shape=[4, 1], dtype="float32")
+           out = fluid.layers.margin_rank_loss(label, left, right)
+    """
+    helper = LayerHelper('margin_rank_loss', **locals())
+    if not isinstance(label, Variable):
+        raise ValueError("The label should be a Variable.")
+    if not isinstance(left, Variable):
+        raise ValueError("The left should be a Variable.")
+    if not isinstance(right, Variable):
+        raise ValueError("The right should be a Variable.")
+    out = helper.create_tmp_variable(left.dtype)
+    act = helper.create_tmp_variable(left.dtype)
+    helper.append_op(
+        type='margin_rank_loss',
+        inputs={"Label": label,
+                "X1": left,
+                "X2": right},
+        outputs={'Out': out,
+                 'Activated': act},
+        attrs={'margin': margin})
+    return out
+
+
 def pad2d(input,
           paddings=[0, 0, 0, 0],
           mode='constant',
@@ -6290,6 +6339,7 @@ def sequence_enumerate(input, win_size, pad_value=0, name=None):
         outputs={'Out': out},
         attrs={'win_size': win_size,
                'pad_value': pad_value})
+    return out
 
 
 def sequence_mask(x, maxlen=None, dtype='int64', name=None):