Add resize_bilinear

Author: reyoung

paddle/fluid/operators/bilinear_interp_op.cc

@@ -56,17 +56,16 @@ class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   void Make() override {
     AddInput("X",
-             "(Tensor) The input tensor of bilinear interpolation, "
+             "The input tensor of bilinear interpolation, "
              "This is a 4-D tensor with shape of (N x C x h x w)");
     AddInput("OutSize",
-             "(Tensor) This is a 1-D tensor with two number. "
+             "This is a 1-D tensor with two number. "
              "The first number is height and the second number is width.")
         .AsDispensable();
-    AddOutput("Out",
-              "(Tensor) The dimension of output is (N x C x out_h x out_w]");
+    AddOutput("Out", "The dimension of output is (N x C x out_h x out_w)");
 
-    AddAttr<int>("out_h", "(int) output height of bilinear interpolation op.");
-    AddAttr<int>("out_w", "(int) output width of bilinear interpolation op.");
+    AddAttr<int>("out_h", "output height of bilinear interpolation op.");
+    AddAttr<int>("out_w", "output width of bilinear interpolation op.");
     AddComment(R"DOC(
           Bilinear interpolation is an extension of linear interpolation for 
           interpolating functions of two variables (e.g. H-direction and 

python/paddle/fluid/layers/layer_function_generator.py

@@ -224,7 +224,7 @@ def __impl__(func):
     return __impl__
 
 
-def templatedoc():
+def templatedoc(op_type=None):
     """
     Decorator of layer function. It will use the docstring from the layer
     function as the template. The template arguments are:
@@ -242,15 +242,20 @@ def trim_ending_dot(msg):
         return msg.rstrip('.')
 
     def __impl__(func):
-        op_proto = OpProtoHolder.instance().get_op_proto(func.__name__)
+        if op_type is None:
+            op_type_name = func.__name__
+        else:
+            op_type_name = op_type
+        op_proto = OpProtoHolder.instance().get_op_proto(op_type_name)
         tmpl = string.Template(func.__doc__)
 
         comment_lines = op_proto.comment.split("\n")
         comment = ""
         for line in comment_lines:
-            line = line.lstrip()
-            comment += line
-            comment += "\n"
+            line = line.strip()
+            if len(line) != 0:
+                comment += line
+                comment += " "
 
         args = {"comment": trim_ending_dot(comment)}
         for each_input in op_proto.inputs:

python/paddle/fluid/layers/nn.py

@@ -4037,18 +4037,25 @@ def _is_list_or_turple_(data):
     return out
 
 
+@templatedoc(op_type="bilinear_interp")
 def resize_bilinear(input, out_shape=None, scale=None, name=None):
     """
-    This is an alias of layer 'image_resize' with bilinear interpolation.
+    ${comment}
+
+    Args:
+        input(${x_type}): ${x_comment}.
+
+        out_shape(${out_size_type}): ${out_size_comment}.
 
-    The mathematical meaning of resize bilinear layer is
-    Bilinear interpolation.
-    Bilinear interpolation is an extension of linear interpolation for
-    interpolating functions of two variables (e.g. H-direction and
-    W-direction in this layer) on a rectilinear 2D grid.
+        scale(float|None): The multiplier for the input height or width. At
+             least one of out_shape or scale must be set. And out_shape has
+             a higher priority than scale. Default: None.
+
+        name(str|None): The output variable name.
+
+    Returns:
 
-    For details, please refer to Wikipedia:
-    https://en.wikipedia.org/wiki/Bilinear_interpolation
+        ${out_comment}.
     """
 
     return image_resize(input, out_shape, scale, name, 'BILINEAR')