Merge pull request #16493 from zhoukunsheng/zeros_like

Zeros like

paddle/fluid/API.spec

@@ -277,6 +277,7 @@ paddle.fluid.layers.has_nan (ArgSpec(args=['x'], varargs=None, keywords=None, de
 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.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '495e21e9a848c2d075a102802fc67756'))
+paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c7e4cfffc93ae89c8f6f53b6d650f923'))
 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

@@ -28,7 +28,7 @@ __all__ = [
     'tensor_array_to_tensor', 'concat', 'sums', 'assign',
     'fill_constant_batch_size_like', 'fill_constant', 'argmin', 'argmax',
     'argsort', 'ones', 'zeros', 'reverse', 'has_inf', 'has_nan', 'isfinite',
-    'range', 'linspace'
+    'range', 'linspace', 'zeros_like'
 ]
 
 
@@ -853,3 +853,34 @@ def linspace(start, stop, num, dtype):
                 'Num': num},
         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
+
+          x = fluid.layers.data(name='x', dtype='float32', shape=[3], append_batch_size=False)
+          data = fluid.layers.zeros_like(x) # [0.0, 0.0, 0.0]
+
+    """
+
+    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