Merge pull request #5447 from ReyhaneAskari/fix_doc

doc/library/compile/shared.txt

@@ -19,11 +19,34 @@
 
     The user-friendly constructor is :func:`shared`
 
-    .. attribute:: value
+    .. method:: get_value(self, borrow=False, return_internal_type=False)
     
-        Read/write access to the [non-symbolic] value/data associated with this SharedVariable.
+       :param borrow: True to permit returning of an object aliased to internal memory.
+       :type borrow: bool
                
-        Changes to this value will be visible to all functions using this SharedVariable.  
+       :param return_internal_type: True to permit the returning of an arbitrary type object used
+               internally to store the shared variable.
+       :type return_internal_type: bool
+
+       By default, return a copy of the data. If ``borrow=True`` (and
+       ``return_internal_type=False``), maybe it will return a copy.
+       For tensor, it will always return a ndarray by default, so if
+       the data is on the GPU, it will return a copy, but if the data
+       is on the CPU, it will return the original data.  If you do
+       ``borrow=True`` and ``return_internal_type=True``, it will
+       always return the original data, not a copy, but this can be a
+       GPU object.
+    
+    .. method:: set_value(self, new_value, borrow=False)
+
+       :param new_value: The new value.
+       :type new_value: A compatible type for this shared variable.
+
+       :param borrow: True to use the new_value directly, potentially creating problems
+           related to aliased memory.
+       :type borrow: bool
+
+       The new value will be seen by all functions using this SharedVariable.
 
     .. method:: __init__(self, name, type, value, strict, container=None)
 

theano/compile/sharedvalue.py

@@ -120,6 +120,31 @@ class SharedVariable(Variable):
         Changes to this value will be visible to all functions using
         this SharedVariable.
 
+        Notes
+        -----
+        Set_value will work in-place on the GPU, if
+        the following conditions are met:
+
+            * The destination on the GPU must be c_contiguous.
+            * The source is on the CPU.
+            * The old value must have the same dtype as the new value
+              (which is a given for now, since only float32 is
+              supported).
+            * The old and new value must have the same shape.
+            * The old value is being completely replaced by the new
+              value (not partially modified, e.g. by replacing some
+              subtensor of it).
+            * You change the value of the shared variable via
+              set_value, not via the .value accessors. You should not
+              use the .value accessors anyway, since they will soon be
+              deprecated and removed.
+
+        It is also worth mentioning that, for efficient transfer to the GPU,
+        Theano will make the new data ``c_contiguous``. This can require an
+        extra copy of the data on the host.
+
+        The inplace on gpu memory work when borrow is either True or False.
+
         """
         if borrow:
             self.container.value = new_value

theano/sandbox/cuda/var.py

@@ -79,24 +79,6 @@ class CudaNdarraySharedVariable(_operators, SharedVariable):
         """
         Return the value of this SharedVariable's internal array.
 
-        Parameters
-        ----------
-        borrow
-            Permit the return of internal storage, when used in conjunction with
-            ``return_internal_type=True``.
-        return_internal_type
-            True to return the internal ``cuda_ndarray`` instance rather than a
-            ``numpy.ndarray`` (Default False).
-
-        By default ``get_value()`` copies from the GPU to a ``numpy.ndarray``
-        and returns that host-allocated array.
-
-        ``get_value(False,True)`` will return a GPU-allocated copy of the
-        original GPU array.
-
-        ``get_value(True,True)`` will return the original GPU-allocated array
-        without any copying.
-
         """
         if return_internal_type or not self.get_value_return_ndarray:
             # return a cuda_ndarray
@@ -111,42 +93,6 @@ class CudaNdarraySharedVariable(_operators, SharedVariable):
         """
         Assign `value` to the GPU-allocated array.
 
-        Parameters
-        ----------
-        borrow : bool
-            ``True`` permits reusing `value` itself, ``False`` requires that
-            this function copies `value` into internal storage.
-
-        Notes
-        -----
-        Prior to Theano 0.3.1, set_value did not work in-place on the GPU. This
-        meant that sometimes, GPU memory for the new value would be allocated
-        before the old memory was released. If you're running near the limits of
-        GPU memory, this could cause you to run out of GPU memory.
-
-        Beginning with Theano 0.3.1, set_value will work in-place on the GPU, if
-        the following conditions are met:
-
-            * The destination on the GPU must be c_contiguous.
-            * The source is on the CPU.
-            * The old value must have the same dtype as the new value
-              (which is a given for now, since only float32 is
-              supported).
-            * The old and new value must have the same shape.
-            * The old value is being completely replaced by the new
-              value (not partially modified, e.g. by replacing some
-              subtensor of it).
-            * You change the value of the shared variable via
-              set_value, not via the .value accessors. You should not
-              use the .value accessors anyway, since they will soon be
-              deprecated and removed.
-
-        It is also worth mentioning that, for efficient transfer to the GPU,
-        Theano will make the new data ``c_contiguous``. This can require an
-        extra copy of the data on the host.
-
-        The inplace on gpu memory work when borrow is either True or False.
-
         """
         if not borrow:
             # TODO: check for cuda_ndarray type