Add docstrings for make_node functions of GpuDnnTransformerSampler and GpuDnnTransformerGrid

theano/gpuarray/dnn.py

@@ -2806,6 +2806,19 @@ class GpuDnnTransformerGrid(DnnBase):
         DnnBase.__init__(self, ["c_code/dnn_sptf_grid.c"], "APPLY_SPECIFIC(dnn_sptf_grid)")
 
     def make_node(self, theta, desc):
+        """
+        Create a grid generator node for a cuDNN Spatial Transformer
+
+        Parameters
+        ----------
+        theta : tensor
+            Affine transformation tensor containing one affine transformation
+            matrix per image. ``theta`` is usually generated by the localization
+            network.
+
+        desc : GpuDnnTransformerDesc
+            Spatial transformer descriptor
+        """
         context_name = infer_context_name(desc)
 
         if (not isinstance(desc.type, CDataType) or
@@ -2856,6 +2869,24 @@ class GpuDnnTransformerSampler(DnnBase):
         DnnBase.__init__(self, ["c_code/dnn_sptf_sampler.c"], "APPLY_SPECIFIC(dnn_sptf_sampler)")
 
     def make_node(self, img, grid, desc):
+        """
+        Create a grid sampler node for a cuDNN Spatial Transformer
+
+        Parameters
+        ----------
+        img : tensor
+            Images from which the pixels will be sampled. The implementation
+            assumes the tensor is in NCHW format, where N is the number of images,
+            C is the number of color channels, H is the height of the inputs, and
+            W is width of the inputs.
+
+        grid : GpuDnnTransformerGrid
+            Grid that contains the coordinates of the pixels to be sampled from
+            the inputs images.
+
+        desc : GpuDnnTransformerDesc
+            Spatial transformer descriptor
+        """
         context_name = infer_context_name(desc)
 
         if (not isinstance(desc.type, CDataType) or
@@ -3012,7 +3043,7 @@ def dnn_spatialtf(img, theta, scale_width=1, scale_height=1, precision=theano.co
     Currently, cuDNN only supports 2D transformations with 2x3 affine
     transformation matrices.
 
-    Also, the only grid sampler method available is the bilinear interpolation.
+    Bilinear interpolation is the only grid sampler method available.
     """
     out_dims = (img.shape[0], img.shape[1],
                 theano.tensor.ceil(img.shape[2] * scale_height),