Release 2.0rc cherry pick api rename #28108 (#28184)

* rename count_include_pad-->exclusive  return_indices-->return_mask

* remove track_running_stats

* fix typo.

* rename xxxd-->xxxxD

* solve conflicts

Author: cnn

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

@@ -63,10 +63,7 @@ def __init__(self,
             bias_attr=False)
 
         self._sync_batch_norm2 = SyncBatchNorm(
-            num_filters,
-            weight_attr=False,
-            bias_attr=False,
-            track_running_stats=False)
+            num_filters, weight_attr=False, bias_attr=False)
 
     def forward(self, inputs):
         y = self._conv(inputs)

python/paddle/fluid/tests/unittests/test_adaptive_max_pool2d.py

@@ -150,7 +150,7 @@ def test_dynamic_graph(self):
             x = paddle.to_tensor(self.x_np)
 
             out_1 = paddle.nn.functional.adaptive_max_pool2d(
-                x=x, return_indices=False, output_size=[3, 3])
+                x=x, return_mask=False, output_size=[3, 3])
 
             out_2 = paddle.nn.functional.adaptive_max_pool2d(x=x, output_size=5)
 

python/paddle/fluid/tests/unittests/test_pool1d_api.py

@@ -148,19 +148,16 @@ def check_avg_dygraph_padding_results(self, place):
             input_np = np.random.random([2, 3, 32]).astype("float32")
             input = fluid.dygraph.to_variable(input_np)
             result = F.avg_pool1d(
-                input,
-                kernel_size=2,
-                stride=2,
-                padding=[1],
-                count_include_pad=True)
+                input, kernel_size=2, stride=2, padding=[1], exclusive=True)
 
             result_np = avg_pool1D_forward_naive(
                 input_np, ksize=[2], strides=[2], paddings=[1], exclusive=False)
 
             self.assertTrue(np.allclose(result.numpy(), result_np))
 
             avg_pool1d_dg = paddle.nn.AvgPool1D(
-                kernel_size=2, stride=None, padding=1, count_include_pad=True)
+                kernel_size=2, stride=None, padding=1, exclusive=True)
+
             result = avg_pool1d_dg(input)
             self.assertTrue(np.allclose(result.numpy(), result_np))
 
@@ -200,7 +197,7 @@ def check_max_dygraph_return_index_results(self, place):
             input_np = np.random.random([2, 3, 32]).astype("float32")
             input = fluid.dygraph.to_variable(input_np)
             result, index = F.max_pool1d(
-                input, kernel_size=2, stride=2, padding=0, return_indices=True)
+                input, kernel_size=2, stride=2, padding=0, return_mask=True)
 
             result_np = max_pool1D_forward_naive(
                 input_np, ksize=[2], strides=[2], paddings=[0])

python/paddle/fluid/tests/unittests/test_pool2d_api.py

@@ -134,7 +134,7 @@ def check_max_dygraph_results(self, place):
             input_np = np.random.random([2, 3, 32, 32]).astype("float32")
             input = fluid.dygraph.to_variable(input_np)
             result = max_pool2d(
-                input, kernel_size=2, stride=2, padding=0, return_indices=False)
+                input, kernel_size=2, stride=2, padding=0, return_mask=False)
 
             result_np = pool2D_forward_naive(
                 input_np,
@@ -159,7 +159,7 @@ def check_max_dygraph_nhwc_results(self, place):
                 kernel_size=2,
                 stride=2,
                 padding=0,
-                return_indices=False,
+                return_mask=False,
                 data_format="NHWC")
 
             result_np = pool2D_forward_naive(
@@ -222,7 +222,7 @@ def check_max_dygraph_stride_is_none(self, place):
                 kernel_size=2,
                 stride=None,
                 padding="SAME",
-                return_indices=True)
+                return_mask=True)
 
             result_np = pool2D_forward_naive(
                 input_np,
@@ -269,7 +269,7 @@ def check_max_dygraph_padding(self, place):
                 kernel_size=2,
                 stride=2,
                 padding=padding,
-                return_indices=False)
+                return_mask=False)
 
             result_np = pool2D_forward_naive(
                 input_np,
@@ -490,7 +490,7 @@ def run9():
                     padding=0,
                     ceil_mode=False,
                     data_format='NHWC',
-                    return_indices=True)
+                    return_mask=True)
 
         self.assertRaises(ValueError, run9)
 

python/paddle/fluid/tests/unittests/test_pool3d_api.py

@@ -83,7 +83,7 @@ def check_avg_dygraph_padding_results(self, place):
                 stride=2,
                 padding=1,
                 ceil_mode=False,
-                count_include_pad=True)
+                exclusive=True)
 
             result_np = avg_pool3D_forward_naive(
                 input_np,
@@ -100,7 +100,7 @@ def check_avg_dygraph_padding_results(self, place):
                 stride=None,
                 padding=1,
                 ceil_mode=False,
-                count_include_pad=True)
+                exclusive=True)
             result = avg_pool3d_dg(input)
             self.assertTrue(np.allclose(result.numpy(), result_np))
 
@@ -175,7 +175,7 @@ def check_max_dygraph_ndhwc_results(self, place):
                 stride=2,
                 padding=0,
                 data_format="NDHWC",
-                return_indices=False)
+                return_mask=False)
 
             result_np = pool3D_forward_naive(
                 input_np,
@@ -239,7 +239,7 @@ def check_max_dygraph_stride_is_none(self, place):
                 kernel_size=2,
                 stride=None,
                 padding="SAME",
-                return_indices=True)
+                return_mask=True)
 
             result_np = pool3D_forward_naive(
                 input_np,
@@ -467,7 +467,7 @@ def run10():
                     stride=2,
                     padding=0,
                     data_format='NDHWC',
-                    return_indices=True)
+                    return_mask=True)
 
         self.assertRaises(ValueError, run10)