support dp for class_center_sample, margin_cross_entropy

add unittest

fix unittest

fix unittest

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

@@ -243,7 +243,21 @@ def test_empty_label():
                         label, self.num_classes, self.num_samples)
                     print(remapped_label, sampled_class_index)
 
+        def test_group_value():
+            for place in self.places:
+                with paddle.fluid.dygraph.guard(place):
+                    label_np = np.random.randint(
+                        0,
+                        self.num_classes, (self.batch_size, ),
+                        dtype=self.dtype)
+                    label = paddle.to_tensor(label_np)
+
+                    remapped_label, sampled_class_index = paddle.nn.functional.class_center_sample(
+                        label, self.num_classes, self.num_samples)
+                    print(remapped_label, sampled_class_index)
+
         self.assertRaises(ValueError, test_empty_label)
+        self.assertRaises(ValueError, test_group_value)
 
 
 if __name__ == '__main__':

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

@@ -400,8 +400,31 @@ def test_label_type():
                         return_softmax=True,
                         reduction=None)
 
+        def test_group_value():
+            for place in self.places:
+                with paddle.fluid.dygraph.guard(place):
+                    labels_np = np.random.randint(
+                        0, self.num_class, (self.batch_dim, ), dtype="int64")
+                    logits_np = np.random.uniform(
+                        -0.99, 0.99,
+                        [self.batch_dim, self.num_class]).astype(self.dtype)
+                    labels = paddle.to_tensor(labels_np)
+                    logits = paddle.to_tensor(logits_np)
+
+                    loss, softmax = paddle.nn.functional.margin_cross_entropy(
+                        logits,
+                        labels,
+                        margin1=self.margin1,
+                        margin2=self.margin2,
+                        margin3=self.margin3,
+                        scale=self.scale,
+                        return_softmax=True,
+                        reduction=None,
+                        group=False)
+
         self.assertRaises(ValueError, test_dim)
         self.assertRaises(NotImplementedError, test_label_type)
+        self.assertRaises(ValueError, test_group_value)
 
 
 if __name__ == '__main__':

python/paddle/nn/functional/common.py

@@ -1731,18 +1731,22 @@ class centers and the shape of sampled_class_center will be [num_positive_class_
         #Tensor(shape=[7], dtype=int64, place=CUDAPlace(1), stop_gradient=True,
         #       [0, 1, 2, 3, 5, 7, 8])
     """
-    if group is not None and not group.is_member():
+    if group != False and group is not None and not group.is_member():
+        raise ValueError(
+            'Expected group is True, None or instance of paddle.distributed.collective.Group \
+             (got group: {})'.format(group))
         return
 
-    ring_id = 0 if group is None else group.id
+    ring_id = 0
     rank = 0
     nranks = 1
-    if core.is_compiled_with_dist():
-        parallel_env = paddle.distributed.ParallelEnv()
-        global_rank = parallel_env.rank
-        rank = global_rank if group is None else group.get_group_rank(
-            global_rank)
-        nranks = parallel_env.world_size if group is None else group.nranks
+    if group != False:
+        if core.is_compiled_with_dist():
+            parallel_env = paddle.distributed.ParallelEnv()
+            global_rank = parallel_env.rank
+            rank = global_rank if group is None else group.get_group_rank(
+                global_rank)
+            nranks = parallel_env.world_size if group is None else group.nranks
 
     if num_samples > num_classes:
         raise ValueError(

python/paddle/nn/functional/loss.py

@@ -1297,24 +1297,29 @@ def margin_cross_entropy(logits,
     """
 
     assert reduction in ['mean', 'sum', 'none', None]
-    if group is not None and not group.is_member():
+    if group != False and group is not None and not group.is_member():
+        raise ValueError(
+            'Expected group is False, None or instance of paddle.distributed.collective.Group \
+             (got group: {})'.format(group))
         return
 
-    ring_id = 0 if group is None else group.id
+    ring_id = 0
     rank = 0
     nranks = 1
-    if core.is_compiled_with_dist():
-        parallel_env = paddle.distributed.ParallelEnv()
-        global_rank = parallel_env.rank
-        rank = global_rank if group is None else group.get_group_rank(
-            global_rank)
-        nranks = parallel_env.world_size if group is None else group.nranks
+    if group != False:
+        ring_id = 0 if group is None else group.id
+        if core.is_compiled_with_dist():
+            parallel_env = paddle.distributed.ParallelEnv()
+            global_rank = parallel_env.rank
+            rank = global_rank if group is None else group.get_group_rank(
+                global_rank)
+            nranks = parallel_env.world_size if group is None else group.nranks
 
     input_dims = len(list(logits.shape))
     label_dims = len(list(label.shape))
     if input_dims - 1 != label_dims and input_dims != label_dims:
         raise ValueError(
-            'Expected nput_dims - 1 = label_dims or input_dims == label_dims\
+            'Expected input_dims - 1 = label_dims or input_dims == label_dims\
              (got nput_dims{}, label_dims{})'.format(input_dims, label_dims))
     if input_dims - 1 == label_dims:
         label = paddle.unsqueeze(label, axis=-1)