[CodeStyle] remove tabs in cpp files

paddle/fluid/operators/dequeue_op.cc

@@ -90,7 +90,7 @@ class DequeueOpMaker : public framework::OpProtoAndCheckerMaker {
     AddOutput("Out", "A list of `lod_tensor` to dequeue and assigned.")
         .AsDuplicable();
     AddComment(R"DOC(
-			Dequeue operator.
+      Dequeue operator.
       )DOC");
   }
 };

paddle/fluid/operators/enqueue_op.cc

@@ -78,7 +78,7 @@ class EnqueueOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<std::string>("queue_name",
                          "Name of the `LoDTensorBlockingQueueHolder` variable");
     AddComment(R"DOC(
-			Enqueue operator.
+      Enqueue operator.
       )DOC");
   }
 };

paddle/fluid/operators/pixel_shuffle_op.cc

@@ -52,19 +52,18 @@ class PixelShuffleOpMaker : public framework::OpProtoAndCheckerMaker {
         .SetDefault("NCHW");
 
     AddComment(R"DOC(
-		Pixel Shuffle operator
-		This operator rearranges elements in a tensor of shape :math:`(*, C \times r^2, H, W)`
-    		to a tensor of shape :math:`(C, H \times r, W \times r)`.
-
-		This is useful for implementing efficient sub-pixel convolution
-    		with a stride of :math:`1/r`.
-
-		Please refer to the paper:
-		 `Real-Time Single Image and Video Super-Resolution Using an Efficient
-		 Sub-Pixel Convolutional Neural Network <https://arxiv.org/abs/1609.05158v2>`_
-    		by Shi et. al (2016) for more details.
-
-        )DOC");
+    Pixel Shuffle operator
+    This operator rearranges elements in a tensor of shape :math:`(*, C \times r^2, H, W)`
+    to a tensor of shape :math:`(C, H \times r, W \times r)`.
+
+    This is useful for implementing efficient sub-pixel convolution
+    with a stride of :math:`1/r`.
+
+    Please refer to the paper:
+    `Real-Time Single Image and Video Super-Resolution Using an Efficient
+    Sub-Pixel Convolutional Neural Network <https://arxiv.org/abs/1609.05158v2>`_
+    by Shi et. al (2016) for more details.
+    )DOC");
   }
 };
 

paddle/fluid/operators/pixel_unshuffle_op.cc

@@ -48,18 +48,17 @@ class PixelUnshuffleOpMaker : public framework::OpProtoAndCheckerMaker {
         .SetDefault("NCHW");
 
     AddComment(R"DOC(
-		Pixel Unshuffle operator
-		This operator rearranges elements in a tensor of shape :math:`(*, C, H, W)`
-    		to a tensor of shape :math:`(*, C\times r^2, H / r, W / r)`.
+    Pixel Unshuffle operator
+    This operator rearranges elements in a tensor of shape :math:`(*, C, H, W)`
+    to a tensor of shape :math:`(*, C\times r^2, H / r, W / r)`.
 
-		This operation is the reversion of PixelShuffle operation.
+    This operation is the reversion of PixelShuffle operation.
 
-		Please refer to the paper:
-		 `Real-Time Single Image and Video Super-Resolution Using an Efficient
-		 Sub-Pixel Convolutional Neural Network <https://arxiv.org/abs/1609.05158v2>`_
-    		by Shi et. al (2016) for more details.
-
-        )DOC");
+    Please refer to the paper:
+    `Real-Time Single Image and Video Super-Resolution Using an Efficient
+    Sub-Pixel Convolutional Neural Network <https://arxiv.org/abs/1609.05158v2>`_
+    by Shi et. al (2016) for more details.
+    )DOC");
   }
 };
 

paddle/fluid/operators/reader/create_ctr_reader_op.cc

@@ -87,7 +87,7 @@ class CreateCTRReaderOpMaker : public FileReaderMakerBase {
                                       "format is svm");
 
     AddComment(R"DOC(
-			Create CTRReader to support read ctr data with cpp.
+      Create CTRReader to support read ctr data with cpp.
       )DOC");
   }
 };

paddle/fluid/operators/shuffle_channel_op.cc

@@ -70,16 +70,16 @@ class ShuffleChannelOpMaker : public framework::OpProtoAndCheckerMaker {
                                 "group should be larger than 0."));
         });
     AddComment(R"DOC(
-		Shuffle Channel operator
-		This opearator shuffles the channels of input x.
-		It  divide the input channels in each group into several subgroups,
-		and obtain a new order by selecting element from every subgroup one by one.
-
-		Shuffle channel operation makes it possible to build more powerful structures
-		with multiple group convolutional layers.
-		please get more information from the following paper:
-		https://arxiv.org/pdf/1707.01083.pdf
-        )DOC");
+    Shuffle Channel operator
+    This opearator shuffles the channels of input x.
+    It  divide the input channels in each group into several subgroups,
+    and obtain a new order by selecting element from every subgroup one by one.
+
+    Shuffle channel operation makes it possible to build more powerful structures
+    with multiple group convolutional layers.
+    please get more information from the following paper:
+    https://arxiv.org/pdf/1707.01083.pdf
+    )DOC");
   }
 };