Add python wrapper for pad_op

python/paddle/fluid/layers/nn.py

@@ -75,6 +75,7 @@ __all__ = [
     'autoincreased_step_counter',
     'lod_reset',
     'lrn',
+    'pad',
 ]
 
 
@@ -3482,3 +3483,60 @@ def lrn(input, n=5, k=1.0, alpha=1e-4, beta=0.75, name=None):
                "beta": beta})
 
     return lrn_out
+
+
+def pad(x, paddings, pad_value=0., name=None):
+    """
+    Pads a tensor with a constant value given by :attr:pad_value, and the
+    padded width is specified by :attr:paddings. 
+
+    Specifically, the number of values padded before each dimension 
+    :attr:i is indicated by :attr:paddings[i], and the number of values padded
+    after each dimension :attr:i is indicated by :attr:paddings[i+1].
+
+    See below for an example.
+
+    .. code-block:: text
+
+        Given:
+            x = [[1, 2], [3, 4]]
+
+            paddings = [0, 1, 1, 2]
+
+            pad_value = 0
+
+        Return:
+
+            out = [[0, 1, 2, 0, 0]
+                   [0, 3, 4, 0, 0]
+                   [0, 0, 0, 0, 0]]
+
+    Args:
+        x (Variable): The input tensor variable.
+        paddings (list): A list of integers. Its elements specify the padded
+                         width before and after for each dimension in turn.
+                         The length of :attr:paddings must be 
+                         :math:`rank(x) \\times 2`.
+        pad_value (float): The constant value used to pad.
+        name(str|None): A name for this layer(optional). If set None, the layer
+                        will be named automatically.
+
+    Returns:
+        Variable: The padded tensor variable.
+
+    Examples:
+        .. code-block:: python
+            # x is a rank 2 tensor variable.
+            out = fluid.layers.pad(
+                x=x, paddings=[0, 1, 1, 2], pad_value=0.)
+    """
+    helper = LayerHelper('pad', input=x, **locals())
+    dtype = helper.input_dtype()
+    out = helper.create_tmp_variable(dtype)
+    helper.append_op(
+        type='pad',
+        inputs={'X': x},
+        outputs={'Out': out},
+        attrs={'paddings': paddings,
+               'pad_value': float(pad_value)})
+    return out