support the tuple for attribute of axis in min, max for api2.0

Update the code for the min,max, test=develop

paddle/fluid/operators/reduce_ops/reduce_op.h

@@ -15,6 +15,7 @@ limitations under the License. */
 #pragma once
 
 #include <algorithm>
+#include <set>
 #include <string>
 #include <vector>
 
@@ -98,6 +99,18 @@ class ReduceKernel : public framework::OpKernel<T> {
     int out_dtype = context.Attr<int>("out_dtype");
     framework::proto::VarType::Type cast_out_dtype;
 
+    // The dims has full dim, set the reduce_all is True
+    const auto& input_dim_size = context.Input<Tensor>("X")->dims().size();
+    std::set<int> dims_set(dims.begin(), dims.end());
+    bool full_dim = true;
+    for (auto i = 0; i < input_dim_size; i++) {
+      if (dims_set.find(i) == dims_set.end()) {
+        full_dim = false;
+        break;
+      }
+    }
+    reduce_all = (reduce_all || full_dim);
+
     if (out_dtype < 0) {
       auto* cast_input = context.Input<Tensor>("X");
       cast_out_dtype =
@@ -137,6 +150,18 @@ class BoolReduceKernel : public framework::OpKernel<OutT> {
     auto dims = context.Attr<std::vector<int>>("dim");
     bool keep_dim = context.Attr<bool>("keep_dim");
 
+    // The dims has full dim, set the reduce_all is True
+    const auto& input_dim_size = context.Input<Tensor>("X")->dims().size();
+    std::set<int> dims_set(dims.begin(), dims.end());
+    bool full_dim = true;
+    for (auto i = 0; i < input_dim_size; i++) {
+      if (dims_set.find(i) == dims_set.end()) {
+        full_dim = false;
+        break;
+      }
+    }
+    reduce_all = (reduce_all || full_dim);
+
     if (reduce_all) {
       // Flatten and reduce 1-D tensor
       auto x = EigenVector<OutT>::Flatten(*input);
@@ -183,6 +208,17 @@ class ReduceGradKernel : public framework::OpKernel<T> {
     auto* output = context.Output<Tensor>(framework::GradVarName("X"));
     output->mutable_data<T>(context.GetPlace());
 
+    // The dims has full dim, set the reduce_all is True
+    const auto& input_dim_size = context.Input<Tensor>("X")->dims().size();
+    std::set<int> dims_set(dims.begin(), dims.end());
+    bool full_dim = true;
+    for (auto i = 0; i < input_dim_size; i++) {
+      if (dims_set.find(i) == dims_set.end()) {
+        full_dim = false;
+        break;
+      }
+    }
+    reduce_all = (reduce_all || full_dim);
     // NOTE: EigenTensor::From() uses tensor->data()
     // if op has NoNeedBufferVarsInferer, the corresponding kNoNeedBufferX or
     // kNoNeedBufferY should set true

python/paddle/fluid/tests/unittests/test_max_op.py

@@ -48,6 +48,15 @@ class ApiMaxTest(unittest.TestCase):
             res, = exe.run(feed={"data": input_data}, fetch_list=[result_max])
         self.assertEqual((res == np.max(input_data, axis=0)).all(), True)
 
+        with paddle.static.program_guard(paddle.static.Program(),
+                                         paddle.static.Program()):
+            data = paddle.nn.data("data", shape=[10, 10], dtype="int64")
+            result_max = paddle.max(x=data, axis=(0, 1))
+            exe = paddle.static.Executor(self.place)
+            input_data = np.random.randint(10, size=(10, 10)).astype(np.int64)
+            res, = exe.run(feed={"data": input_data}, fetch_list=[result_max])
+        self.assertEqual((res == np.max(input_data, axis=(0, 1))).all(), True)
+
     def test_errors(self):
         paddle.enable_static()
 
@@ -59,6 +68,15 @@ class ApiMaxTest(unittest.TestCase):
 
         self.assertRaises(TypeError, test_input_type)
 
+        def test_axis_type():
+            with paddle.static.program_guard(paddle.static.Program(),
+                                             paddle.static.Program()):
+                data = paddle.nn.data("data", shape=[10, 10], dtype="int64")
+                axis = paddle.nn.data("axis", shape=[10, 10], dtype="int64")
+                result_min = paddle.min(data, axis)
+
+        self.assertRaises(TypeError, test_axis_type)
+
     def test_imperative_api(self):
         paddle.disable_static()
         np_x = np.array([10, 10]).astype('float64')

python/paddle/fluid/tests/unittests/test_min_op.py

@@ -48,6 +48,15 @@ class ApiMinTest(unittest.TestCase):
             res, = exe.run(feed={"data": input_data}, fetch_list=[result_min])
         self.assertEqual((res == np.min(input_data, axis=0)).all(), True)
 
+        with paddle.static.program_guard(paddle.static.Program(),
+                                         paddle.static.Program()):
+            data = paddle.nn.data("data", shape=[10, 10], dtype="int64")
+            result_min = paddle.min(x=data, axis=(0, 1))
+            exe = paddle.static.Executor(self.place)
+            input_data = np.random.randint(10, size=(10, 10)).astype(np.int64)
+            res, = exe.run(feed={"data": input_data}, fetch_list=[result_min])
+        self.assertEqual((res == np.min(input_data, axis=(0, 1))).all(), True)
+
     def test_errors(self):
         paddle.enable_static()
 
@@ -59,6 +68,15 @@ class ApiMinTest(unittest.TestCase):
 
         self.assertRaises(TypeError, test_input_type)
 
+        def test_axis_type():
+            with paddle.static.program_guard(paddle.static.Program(),
+                                             paddle.static.Program()):
+                data = paddle.nn.data("data", shape=[10, 10], dtype="int64")
+                axis = paddle.nn.data("axis", shape=[10, 10], dtype="int64")
+                result_min = paddle.min(data, axis)
+
+        self.assertRaises(TypeError, test_axis_type)
+
     def test_imperative_api(self):
         paddle.disable_static()
         np_x = np.array([10, 10]).astype('float64')

python/paddle/tensor/math.py

@@ -1177,19 +1177,19 @@ def max(x, axis=None, keepdim=False, name=None):
             float64, int32, int64.
         axis(list|int, optional): The axis along which the maximum is computed.
             If :attr:`None`, compute the maximum over all elements of
-            :attr:`input` and return a Tensor variable with a single element,
+             `x` and return a Tensor variable with a single element,
             otherwise must be in the range :math:`[-x.ndim(x), x.ndim(x))`.
             If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
         keepdim(bool, optional): Whether to reserve the reduced dimension in the
             output Tensor. The result tensor will have one fewer dimension
-            than the :attr:`input` unless :attr:`keepdim` is true, default
+            than the `x` unless :attr:`keepdim` is true, default
             value is False.
         name(str, optional): The default value is None.  Normally there is no need for
             user to set this property.  For more information, please refer to :ref:`api_guide_Name`
 
     Returns:
         Tensor, results of maximum on the specified axis of input tensor,
-        it's data type is the same as input's Tensor.
+        it's data type is the same as `x`.
 
     Examples:
         .. code-block:: python
@@ -1232,7 +1232,14 @@ def max(x, axis=None, keepdim=False, name=None):
     """
 
     if axis is not None and not isinstance(axis, list):
-        axis = [axis]
+        if isinstance(axis, tuple):
+            axis = list(axis)
+        elif isinstance(axis, int):
+            axis= [axis]
+        else:
+            raise TypeError(
+                "The type of axis must be int, list or tuple, but received {}".format(type(axis)))
+
     reduce_all = True if axis == None or axis == [] else False
     axis = axis if axis != None and axis != [] else [0]
     if in_dygraph_mode():
@@ -1265,12 +1272,12 @@ def min(x, axis=None, keepdim=False, name=None):
         x(Tensor): A tensor, the data type is float32, float64, int32, int64.
         axis(list|int, optional): The axis along which the minimum is computed.
             If :attr:`None`, compute the minimum over all elements of
-            :attr:`input` and return a Tensor variable with a single element,
+            `x` and return a Tensor variable with a single element,
             otherwise must be in the range :math:`[-x.ndim, x.ndim)`.
             If :math:`axis[i] < 0`, the axis to reduce is :math:`x.ndim + axis[i]`.
         keepdim(bool, optional): Whether to reserve the reduced dimension in the
             output Tensor. The result tensor will have one fewer dimension
-            than the :attr:`input` unless :attr:`keepdim` is true, default
+            than the `x` unless :attr:`keepdim` is true, default
             value is False.
         name(str, optional): The default value is None.  Normally there is no need for 
             user to set this property.  For more information, please refer to :ref:`api_guide_Name`
@@ -1320,7 +1327,13 @@ def min(x, axis=None, keepdim=False, name=None):
     """
 
     if axis is not None and not isinstance(axis, list):
-        axis= [axis]
+        if isinstance(axis, tuple):
+            axis = list(axis)
+        elif isinstance(axis, int):
+            axis= [axis]
+        else:
+            raise TypeError(
+                "The type of axis must be int, list or tuple, but received {}".format(type(axis)))
     reduce_all = True if axis == None or axis == [] else False
     axis = axis if axis != None and axis != [] else [0]
     if in_dygraph_mode():