Add info in the doc of sparse dot ops.

doc/library/sparse/index.txt

@@ -197,18 +197,21 @@ List of Implemented Operations
     - :class:`Dot <theano.sparse.basic.Dot>` and
       :func:`dot <theano.sparse.basic.dot>`.
 
+        - One of the inputs must be sparse, the other sparse or dense.
         - The grad implemented is regular.
         - No C code for perform and no C code for grad.
         - Return a dense for perform and a dense for grad.
     - :class:`StructuredDot <theano.sparse.basic.StructuredDot>`
       and :func:`structured_dot <theano.sparse.basic.structured_dot>`.
 
+        - The first input is sparse, the second can be sparse or dense.
         - The grad implemented is structured.
         - C code for perform and grad.
         - Return a dense for perforn and a sparse for grad.
     - :class:`TrueDot <theano.sparse.basic.TrueDot>` and
       :func:`true_dot <theano.sparse.basic.true_dot>`.
 
+        - The first input is sparse, the second can be sparse or dense.
         - The grad implemented is regular.
         - No C code for perform and no C code for grad.
         - Return a Sparse for perform and a Sparse for grad.
@@ -217,17 +220,22 @@ List of Implemented Operations
     - :class:`SamplingDot <theano.sparse.basic.SamplingDot>` and
       ``sampling_dot``.
 
+        - Both input must be dense.
         - The grad implemented is structured for `p`.
         - Sample of the dot and sample of the gradient.
         - C code for perform but not for grad.
         - Return sparse for perform and grad.
     - :class:`Usmm <theano.sparse.basic.Usmm>` and ``usmm``.
 
+        - You *shouldn't* insert this op yourself!
+           - There is optimization that transform a
+             :class:`Dot <theano.sparse.basic.Dot>` to ``Usmm`` when possible.
+
         - This op is the equivalent of gemm for sparse dot.
-        - There is no grad implemented for this op.
-        - There is optimization that transform a
-          :class:`Dot <theano.sparse.basic.Dot>` to ``Usmm`` when possible.
-          You shouldn't need to insert it yourself.
+        - There is no grad implemented for this op and this is not needed as
+          you don't insert it yourself.
+        - One of the inputs must be sparse, the other sparse or dense.
+        - Return a dense for perform
 
 - Slice Operations
     - sparse_variable[N, N], return a tensor scalar.