Merge pull request #494 from lamblin/fix_doc_syntax

doc/NEWS.txt

@@ -54,8 +54,7 @@ Interface Features Removed (most were deprecated):
       to return has been removed. Instead, apply a subtensor to the output
       returned by scan to select a certain slice.
     * The inner function (that scan receives) should return its outputs and
-      updates following this order:
-        [outputs], [updates], [condition].
+      updates following this order: [outputs], [updates], [condition].
       One can skip any of the three if not used, but the order has to stay unchanged.
 
 Interface bug fix:
@@ -74,8 +73,10 @@ Bug fixes (incorrect results):
    Dieleman)
  * Theoretical bug: in some case we could have GPUSum return bad value.
    We were not able to reproduce this problem
+
    * patterns affected ({0,1}*nb dim, 0 no reduction on this dim, 1 reduction on this dim):
      01, 011, 0111, 010, 10, 001, 0011, 0101 (Frederic)
+
  * div by zero in verify_grad. This hid a bug in the grad of Images2Neibs. (James)
  * theano.sandbox.neighbors.Images2Neibs grad was returning a wrong value.
    The grad is now disabled and returns an error. (Frederic)
@@ -98,9 +99,10 @@ Scan fixes:
    before : most of the time crash, but could be wrong value with bad number of dimensions (so a visible bug)
    now : do the right thing.
  * gradient with respect to outputs using multiple taps (reported by Timothy, fix by Razvan)
-   before : it used to return wrong values
-   now : do the right thing.
-   Note: The reported case of this bug was happening in conjunction with the
+
+   * before : it used to return wrong values
+   * now : do the right thing.
+   * Note: The reported case of this bug was happening in conjunction with the
      save optimization of scan that give run time errors. So if you didn't
      manually disable the same memory optimization (number in the list4),
      you are fine if you didn't manually request multiple taps.

doc/core_development_guide.txt

@@ -20,7 +20,7 @@ some of them might be outdated though:
 
 * :ref:`pipeline` -- Describes the steps of compiling a Theano Function.
 
-* :ref:`graphstructure` -- Describes the symbolic graphs generated by
+* :ref:`graphstructures` -- Describes the symbolic graphs generated by
   :mod:`theano.scan`.
 
 * :ref:`unittest` -- Tutorial on how to use unittest in testing Theano.

doc/developer/scan.txt

@@ -91,7 +91,7 @@ Naming conventions
 * ``input_state`` will stand for a state :math:`\mathbf{x}`, when it is
   provided as an input to the recurrent formula (the inner function) that 
   will generate the new value of the state
-* ``output_state`` will stand for a state :math:`\math{x}` when it refers 
+* ``output_state`` will stand for a state :math:`\mathbf{x}` when it refers 
   to the result of the recurrent formula (the output of the inner function)
 * ``output`` will stand for an output :math:`\mathbf{y}`
 * ``input`` will be an input :math:`\mathbf{u}`

doc/introduction.txt

@@ -174,23 +174,29 @@ Here is the state of that vision as of 24 October 2011 (after Theano release
 * We have many graph transformations that cover the 4 categories listed above.
 * We can improve the graph transformation with better storage optimization
   and instruction selection.
+
   * Similar to auto-tuning during the optimization phase, but this
     doesn't apply to only 1 op.
   * Example of use: Determine if we should move computation to the
     GPU or not depending on the input size.
   * Possible implementation note: allow Theano Variable in the env to
     have more then 1 owner.
+
 * We have a CUDA backend for tensors of type `float32` only.
 * Efforts have begun towards a generic GPU ndarray (GPU tensor) (started in the
   `compyte <https://github.com/inducer/compyte/wiki>`_ project)
+
   * Move GPU backend outside of Theano (on top of PyCUDA/PyOpenCL)
   * Will provide better support for GPU on Windows and use an OpenCL backend on CPU.
+
 * Loops work, but not all related optimizations are currently done.
 * The cvm linker allows lazy evaluation. It works, but some work is still
   needed before enabling it by default.
+
   * All tests pass with linker=cvm?
   * How to have `DEBUG_MODE` check it? Right now, DebugMode checks the computation non-lazily.
   * The profiler used by cvm is less complete than `PROFILE_MODE`.
+
 * SIMD parallelism on the CPU comes from the compiler.
 * Multi-core parallelism is only supported for gemv and gemm, and only
   if the external BLAS implementation supports it.

doc/sandbox/randomnumbers.txt

-.. sandbox_randnb:
+.. _sandbox_randnb:
 
 ==============
 Random Numbers

theano/sandbox/linalg/ops.py

@@ -480,8 +480,8 @@ class MatrixPinv(Op):
 
     The pseudo-inverse of a matrix A, denoted :math:`A^+`, is
     defined as: "the matrix that 'solves' [the least-squares problem]
-    :math:`Ax = b`," i.e., if :math:`\bar{x}` is said solution, then
-    :math:`A^+` is that matrix such that :math:`\bar{x} = A^+b`.
+    :math:`Ax = b`," i.e., if :math:`\\bar{x}` is said solution, then
+    :math:`A^+` is that matrix such that :math:`\\bar{x} = A^+b`.
 
     Note that :math:`Ax=AA^+b`, so :math:`AA^+` is close to the identity matrix.
     This method is not faster then `matrix_inverse`. Its strength comes from

theano/tensor/raw_random.py

@@ -563,7 +563,7 @@ def permutation(random_state, size=None, n=1, ndim=None, dtype='int64'):
     the size argument and the shape of n, but you may always specify it
     with the `ndim` parameter.
 
-    .. note::
+    :note:
         Note that the output will then be of dimension ndim+1.
     """
     ndim, size, bcast = _infer_ndim_bcast(ndim, size)