Polish from concat to conv shift operators (#5347)

* polish from concat to conv_shift op doc

* small fix

* small fix

paddle/operators/concat_op.cc

@@ -56,20 +56,24 @@ class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   ConcatOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("X", "the input tensors of concat operator.").AsDuplicable();
-    AddOutput("Out", "the output tensor of concat operator.");
+    AddInput("X", "Input tensors of concat operator.").AsDuplicable();
+    AddOutput("Out", "Output tensor of concat operator.");
+    AddAttr<int>("axis",
+                 "The axis along which the input tensors will be concatenated.")
+        .SetDefault(0);
     AddComment(R"DOC(
-            Join the input tensors along with the axis.
-            Examples:
+Concat Operator.
+
+Concatenate the input tensors along dimension axis.
+Examples:
   Input[0] = [[1,2],[3,4]]
   Input[1] = [[5,6]]
   axis = 0
   Output = [[1,2],
             [3,4],
             [5,6]]
-        )DOC");
-    AddAttr<int>("axis", "The axis which the inputs will be joined with.")
-        .SetDefault(0);
+
+)DOC");
   }
 };
 

paddle/operators/cond_op.cc

@@ -216,11 +216,12 @@ class CondOpProtoAndCheckerMaker : public framework::OpProtoAndCheckerMaker {
     AddOutput("IndexTensors", "Index Tensors contains indices for true/false");
 
     AddComment(R"DOC(
-Sample dependent Cond Operator:
-Given Cond[i] as a 1/0 vector to indicate true/false
-The equation is:
-Out[i] = subnet_t[i], if Cond[i] == true
-Out[i] = subnet_t[i], if Cond[i] == false
+Sample Dependent Conditional Operator.
+
+Given Cond[i] as a 1/0 vector to indicate true/false:
+Out[i] = subnet_true[i], if Cond[i] == true
+Out[i] = subnet_false[i], if Cond[i] == false
+
 )DOC");
   }
 };

paddle/operators/conv2d_op.cc

@@ -56,17 +56,18 @@ Conv2DOpMaker::Conv2DOpMaker(framework::OpProto* proto,
   AddInput(
       "Input",
       "The input tensor of convolution operator. "
-      "The format of input tensor is NCHW. Where N is batch size, C is the "
-      "number of channels, H and W is the height and width of image.");
+      "The format of input tensor is NCHW, where N is batch size, C is the "
+      "number of channels, H is the height of the image, "
+      "and W is the width of the image.");
   AddInput("Filter",
-           "The filter tensor of convolution operator."
+           "The filter tensor of convolution operator. "
            "The format of the filter tensor is MCHW, where M is the number of "
            "output image channels, C is the number of input image channels, "
-           "H and W is height and width of filter. "
-           "If the groups attribute is greater than 1, C equal the number of "
+           "H is the height of the filter, and W is the width of the filter. "
+           "If the groups attribute is greater than 1, C equals the number of "
            "input image channels divided by the groups.");
   AddOutput("Output",
-            "The output tensor of convolution operator."
+            "The output tensor of convolution operator. "
             "The format of output tensor is also NCHW.");
   AddAttr<std::vector<int>>("strides", "strides of convolution operator.")
       .SetDefault({1, 1});
@@ -74,16 +75,19 @@ Conv2DOpMaker::Conv2DOpMaker(framework::OpProto* proto,
       .SetDefault({0, 0});
   AddAttr<int>(
       "groups",
-      "group size of convolution operator. "
-      "Refer to grouped convolution in Alex Krizhevsky's paper: "
-      "when group=2, the first half of the filters are only connected to the "
-      "first half of the input channels, and the second half only connected "
-      "to the second half.")
+      "Group size of convolution operator. "
+      "According to grouped convolution in Alex Krizhevsky's Deep CNN paper: "
+      "when group=2, the first half of the filters is only connected to the "
+      "first half of the input channels, while the second half of the filters "
+      "is only connected to the second half of the input channels.")
       .SetDefault(1);
   AddComment(R"DOC(
-The convolution operation calculates the output based on the input, filter
-and strides, paddings, groups parameters. The size of each dimension of the
-parameters is checked in the infer-shape.
+Convolution Operator.
+
+The convolution operation calculates the output based on the input, filter, 
+strides, paddings, and groups parameters. The size of each dimension of the
+parameters is checked in the infer-shape method.
+
 )DOC");
 }
 

paddle/operators/conv2d_transpose_op.cc

@@ -54,15 +54,16 @@ Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(
   AddInput(
       "Input",
       "(Tensor) The input tensor of convolution transpose operator. "
-      "The format of input tensor is NCHW. Where N is batch size, C is the "
-      "number of input channels, H and W is the height and width of image.");
+      "The format of input tensor is NCHW, where N is batch size, C is the "
+      "number of input channels, H is the height of the image, and "
+      "W is the width of the image.");
   AddInput("Filter",
            "(Tensor) The filter tensor of convolution transpose operator."
            "The format of the filter tensor is CMHW, where C is the number of "
            "output image channels, M is the number of input image channels, "
-           "H and W is height and width of filter. "
+           "H is the height of the filter, and W is the width of the filter. "
            "We enforce groups number == 1 and padding == 0 in "
-           "convolution transpose Scenario.");
+           "the convolution transpose scenario.");
   AddOutput("Output",
             "(Tensor) The output tensor of convolution transpose operator."
             "The format of output tensor is also NCHW.");
@@ -73,9 +74,12 @@ Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(
                             "paddings of convolution transpose operator.")
       .SetDefault({0, 0});
   AddComment(R"DOC(
-The convolution transpose operation calculates the output based on the input, filter
-and strides, paddings, groups parameters. The size of each dimension of the
-parameters is checked in the infer-shape.
+Convolution Transpose Operator.
+
+The convolution transpose operation calculates the output based on the input, 
+filter, strides, paddings, and groups parameters. The size of each dimension 
+of the parameters is checked in the infer-shape method.
+
 )DOC");
 }
 

paddle/operators/conv_shift_op.cc

@@ -96,14 +96,13 @@ as used in the Neural Turing Machine: https://arxiv.org/abs/1410.5401
 
 The equation is:
 
-  \f[
-      Out[i] = \sum_{j=-(N-1)/2}^{(N-1)/2} X_{i+j} * Y_{j}
-  \f]
+$$Out[i] = \sum_{j=-(N-1)/2}^{(N-1)/2} X_{i+j} * Y_{j}$$
 
-where X's index is computed modulo M, and b's index is computed modulo N.
+where X's index is computed modulo M, and Y's index is computed modulo N.
+
+Both inputs X and Y can carry LoD (Level of Details) information.
+However, the output only shares the LoD information with input X.
 
-Both of the input `X` and `Y` can carry LoD (Level of Details) information.
-However, the output only shares the LoD information with input `X`.
 )DOC");
   }
 };