merge

doc/generate_dtype_tensor_table.py

+
+letters = [
+    ('b', 'int8'),
+    ('w', 'int16'),
+    ('i', 'int32'),
+    ('l', 'int64'),
+    ('d', 'float64'),
+    ('f', 'float32'),
+    ('c', 'complex64'),
+    ('z', 'complex128') ]
+
+shapes = [
+        ('scalar', ()),
+        ('vector', (False,)),
+        ('row', (True, False)),
+        ('col', (False, True)),
+        ('matrix', (False,False)),
+        ('tensor3', (False,False,False)),
+        ('tensor4', (False,False,False,False)),]
+
+hdr = '============ =========== ==== =========== ================================='
+print hdr
+print 'Constructor  dtype       ndim shape       broadcastable'
+print hdr
+for letter in letters:
+    for shape in shapes:
+        suff = ',)' if len(shape[1])==1 else ')'
+        s = '(' + ','.join('1' if b else '?' for b in shape[1]) + suff
+        print '%s%-10s  %-10s  %-4s %-10s  %-20s' %(
+                letter[0], shape[0], letter[1], len(shape[1]), s, shape[1]
+                )
+print hdr

doc/library/tensor/index.txt

@@ -10,8 +10,8 @@
 .. moduleauthor:: LISA
 
 Theano's strength is in expressing symbolic calculations involving tensors.  
-There are many types of symbolic expressions for tensors.  For everyone's
-sanity, they are grouped into the following sections:
+There are many types of symbolic expressions for tensors. 
+They are grouped into the following sections:
 
 
 .. toctree::

doc/tutorial/adding.txt

@@ -65,7 +65,7 @@ is the type we assign to "0-dimensional arrays (`scalar`) of doubles
 
 ``dscalar`` is not a class. Therefore, neither ``x`` nor ``y``
 are actually instances of ``dscalar``. They are instances of
-:ref:`TensorVariable <libdoc_tensor_type>`. ``x`` and ``y``
+:class:`TensorVariable`. ``x`` and ``y``
 are, however, assigned the theano Type ``dscalar`` in their ``type``
 field, as you can see here:
 

doc/tutorial/symbolic_graphs.txt

@@ -38,11 +38,20 @@ details about these building blocks see :ref:`variable`, :ref:`op`,
 
 **Diagram**
 
+.. _tutorial-graphfigure: 
+
 .. figure:: apply.png 
     :align: center
 
+    Interaction between instances of Apply (blue), Variable (red), Op (green),
+    and Type (purple).
+
+.. # COMMENT
+    WARNING: hyper-links and ref's seem to break the PDF build when placed
+    into this figure caption.
 
-Arrows represent references to the Python objects pointed at. The blue
+Arrows in this :ref:`figure <tutorial-graphfigure>` represent references to the 
+Python objects pointed at. The blue
 box is an :ref:`apply` node. Red boxes are :ref:`variable` nodes. Green
 circles are :ref:`Ops <op>`. Purple boxes are :ref:`Types <type>`.
 

theano/tensor/basic.py

@@ -737,6 +737,11 @@ btensor3 = TensorType('int8', (False,)*3)
 wtensor3 = TensorType('int16', (False,)*3)
 itensor3 = TensorType('int32', (False,)*3)
 ltensor3 = TensorType('int64', (False,)*3)
+def tensor3(name=None, dtype='float64'):
+    type = TensorType(dtype, (False, False, False))
+    return type(name)
+tensor3s, ftensor3s, dtensor3s, itensor3s, ltensor3s = _multi(tensor3, ftensor3, dtensor3,
+        itensor3, ltensor3)
 
 ctensor4 = TensorType('complex64', (False,)*4)
 ztensor4 = TensorType('complex128', (False,)*4)
@@ -746,6 +751,11 @@ btensor4 = TensorType('int8', (False,)*4)
 wtensor4 = TensorType('int16', (False,)*4)
 itensor4 = TensorType('int32', (False,)*4)
 ltensor4 = TensorType('int64', (False,)*4)
+def tensor4(name=None, dtype='float64'):
+    type = TensorType(dtype, (False, False, False, False))
+    return type(name)
+tensor4s, ftensor4s, dtensor4s, itensor4s, ltensor4s = _multi(tensor4, ftensor4, dtensor4,
+        itensor4, ltensor4)
 
 class _tensor_py_operators:
     #UNARY