Cherry pick floor div mod (#20538)

* fix elementwise floordiv mod; test=develop

* restore nn.py; test=release/1.6

* change floordiv, mod  doc; test=release/1.6

paddle/fluid/API.spec

@@ -251,8 +251,8 @@ paddle.fluid.layers.elementwise_mul (ArgSpec(args=['x', 'y', 'axis', 'act', 'nam
 paddle.fluid.layers.elementwise_max (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '27e1e1604433f85cd7c4c320cb7b9a5f'))
 paddle.fluid.layers.elementwise_min (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'cdbfe2042da18b0e2a2fd79fde944dc2'))
 paddle.fluid.layers.elementwise_pow (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '6fc5d7492830d60c7fa61b3bc8f0d7e7'))
-paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '4101ee1f9280f00dce54054ccc434890'))
-paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '67e6101c31314d4082621e8e443cfb68'))
+paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '7bc28b6e147067a220f8e00b9055f62e'))
+paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '0035541f94bddb5ad472f9788384ca6a'))
 paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0)), ('document', 'cfa120e583cd4a5bfa120c8a26f98a28'))
 paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'dd4ddb66c78a2564e5d1e0e345d8286f'))
 paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '9ac9bdc45be94494d8543b8cec5c26e0'))

paddle/fluid/operators/elementwise/elementwise_floordiv_op.cc

@@ -22,6 +22,22 @@ class ElementwiseFloorDivOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "FloorDiv"; }
   std::string GetEquation() const override { return "Out = X // Y"; }
+
+  void AddInputX() override {
+    AddInput("X",
+             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
+             "should be int32, int64.");
+  }
+
+  void AddInputY() override {
+    AddInput("Y",
+             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
+             "should be int32, int64.");
+  }
+
+  std::string GetOpFuntionality() const override {
+    return "Floor divide two tensors element-wise";
+  }
 };
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/elementwise/elementwise_mod_op.cc

@@ -22,6 +22,22 @@ class ElementwiseModOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "Mod"; }
   std::string GetEquation() const override { return "Out = X \\\\% Y"; }
+
+  void AddInputX() override {
+    AddInput("X",
+             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
+             "should be int32, int64.");
+  }
+
+  void AddInputY() override {
+    AddInput("Y",
+             "(Variable), Tensor or LoDTensor of any dimensions. Its dtype "
+             "should be int32, int64.");
+  }
+
+  std::string GetOpFuntionality() const override {
+    return "Mod two tensors element-wise";
+  }
 };
 }  // namespace operators
 }  // namespace paddle

python/paddle/fluid/layers/nn.py

@@ -13826,10 +13826,60 @@ Examples:
 
 
 def elementwise_mod(x, y, axis=-1, act=None, name=None):
+    """
+Examples:
+
+    ..  code-block:: python
+
+        import paddle.fluid as fluid
+        import numpy as np
+
+        def gen_data():
+            return {
+                "x": np.array([10, 15, 8]).astype('int32'),
+                "y": np.array([3, 6, 5]).astype('int32')
+            }
+
+        x = fluid.data(name="x", shape=[3], dtype='int32')
+        y = fluid.data(name="y", shape=[3], dtype='int32')
+        z = fluid.layers.elementwise_mod(x, y)
+
+        place = fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        z_value = exe.run(feed=gen_data(),
+                            fetch_list=[z.name])
+
+        print(z_value) #[1, 3, 3]
+    """
     return _elementwise_op(LayerHelper('elementwise_mod', **locals()))
 
 
 def elementwise_floordiv(x, y, axis=-1, act=None, name=None):
+    """
+Examples:
+
+    ..  code-block:: python
+
+        import paddle.fluid as fluid
+        import numpy as np
+
+        def gen_data():
+            return {
+                "x": np.array([10, 15, 8]).astype('int32'),
+                "y": np.array([3, 7, 5]).astype('int32')
+            }
+
+        x = fluid.data(name="x", shape=[3], dtype='int32')
+        y = fluid.data(name="y", shape=[3], dtype='int32')
+        z = fluid.layers.elementwise_floordiv(x, y)
+
+        place = fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        z_value = exe.run(feed=gen_data(),
+                            fetch_list=[z.name])
+
+        print(z_value) #[3, 2, 1]
+    """
     return _elementwise_op(LayerHelper('elementwise_floordiv', **locals()))
 
 
@@ -13841,6 +13891,8 @@ for func in [
         elementwise_max,
         elementwise_pow,
         elementwise_min,
+        elementwise_mod,
+        elementwise_floordiv,
 ]:
     op_proto = OpProtoHolder.instance().get_op_proto(func.__name__)
     func.__doc__ = _generate_doc_string_(
@@ -13858,10 +13910,7 @@ for func in [
         skip_attrs_set={"x_data_format", "y_data_format", "axis"
                         }) + """\n""" + str(func.__doc__)
 
-for func in [
-        elementwise_mod,
-        elementwise_floordiv,
-]:
+for func in []:
     op_proto = OpProtoHolder.instance().get_op_proto(func.__name__)
     func.__doc__ = _generate_doc_string_(
         op_proto,