test=develop

add zeros_like op

paddle/fluid/API.spec

@@ -266,6 +266,7 @@ paddle.fluid.layers.has_inf (ArgSpec(args=['x'], varargs=None, keywords=None, de
 paddle.fluid.layers.has_nan (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '2e53e83127dbfd86e7098bdfe9a549e8'))
 paddle.fluid.layers.isfinite (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '0a437011c3906079fd8947ed3e52d292'))
 paddle.fluid.layers.range (ArgSpec(args=['start', 'end', 'step', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '2ec937ede953ded2fdff2675883900bb'))
+paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', '4516005c2efb5f1b0adb4d0bac231408'))
 paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.While.block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.Switch.__init__ (ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))

python/paddle/fluid/layers/tensor.py

@@ -45,6 +45,7 @@ __all__ = [
     'has_nan',
     'isfinite',
     'range',
+    'zeros_like',
 ]
 
 
@@ -827,3 +828,32 @@ def range(start, end, step, dtype):
                 'Step': step},
         outputs={'Out': [out]})
     return out
+
+
+def zeros_like(x, out=None):
+    """
+    **zeros_like**
+
+    This function creates a zeros tensor which has identical shape and dtype 
+    with `x`.
+
+    Args:
+        x(Variable): The input tensor which specifies shape and dtype.
+        out(Variable): The output tensor.
+
+    Returns:
+        Variable: The tensor variable storing the output.
+
+    Examples:
+        .. code-block:: python
+
+          data = fluid.layers.zeros_like(x)
+    """
+
+    helper = LayerHelper("zeros_like", **locals())
+    if out is None:
+        out = helper.create_variable_for_type_inference(dtype=x.dtype)
+    helper.append_op(
+        type='fill_zeros_like', inputs={'X': [x]}, outputs={'Out': [out]})
+    out.stop_gradient = True
+    return out