removed raw_random from shared_randomstreams

doc/library/tensor/shared_randomstreams.txt

@@ -163,114 +163,3 @@ Reference
         Including this pair in the``updates`` list to function will cause the
         function to update the random number generator feeding this variable.
 
-.. _libdoc_tensor_raw_random:
-
-=============================================
-:mod:`raw_random` -- Low-level random numbers
-=============================================
-
-.. module:: raw_random
-   :platform: Unix, Windows
-   :synopsis: symbolic random variables
-.. moduleauthor:: LISA
-
-
-Raw random provides the random-number drawing functionality, that underlies
-the :class:`RandomStreams` interface.
-
-Reference
-=========
-
-.. class:: RandomStateType(gof.Type)
-
-    A `Type` for variables that will take ``numpy.random.RandomState`` values.
-
-.. class:: RandomFunction(gof.Op)
-
-    Op that draws random numbers from a numpy.RandomState object.  This Op is
-    parametrized to draw numbers from many distributions.
-
-
-.. function:: random_function(fn, dtype, *rfargs, **rfkwargs)
-
-    Returns a wrapper around RandomFunction which automatically infers the number
-    of dimensions of the output from the given shape. If the shape cannot be inferred,
-    the user can give an integer as first argument, which will be interpreted as the
-    number of dimensions.
-
-    If the distribution is not scalar (e.g., a multinomial), the output will have
-    more dimensions than what the shape argument suggests. The "ndim_added" keyword
-    arguments allows to specify how many dimensions to add (for a multinomial, 1).
-
-    The number of dimensions for the following shape arguments can be inferred:
-
-    * shape(x)
-    * make_lvector(x, y, z, ...)
-    * ndarrays,  constants
-
-.. function:: uniform(random_state, size, low=0.0, high=1.0)
-
-    Sample from a uniform distribution between low and high.
-
-    If the size argument is ambiguous on the number of
-    dimensions, the first argument may be a plain integer
-    to supplement the missing information.
-
-    :returns: :class:`RandomVariable`, NewRandomState
-
-.. function:: binomial(random_state, size, n=1, p=0.5)
-
-    Sample n times with probability of success prob for each trial,
-    return the number of successes.
-
-    If the size argument is ambiguous on the number of
-    dimensions, the first argument may be a plain integer
-    to supplement the missing information.
-    :returns: :class:`RandomVariable`, NewRandomState
-
-.. function:: normal(random_state, size, avg=0.0, std=1.0)
-
-    Sample from a normal distribution centered on avg with
-    the specified standard deviation (std)
-
-    If the size argument is ambiguous on the number of
-    dimensions, the first argument may be a plain integer
-    to supplement the missing information.
-
-    :returns: :class:`RandomVariable`, NewRandomState
-
-.. function:: random_integers(random_state, size, low=0, high=1)
-
-    Sample a random integer between low and high, both inclusive.
-
-    If the size argument is ambiguous on the number of
-    dimensions, the first argument may be a plain integer
-    to supplement the missing information.
-
-    :returns: :class:`RandomVariable`, NewRandomState
-
-.. function:: permutation(random_state, size, n=1)
-
-    Returns permutations of the integers between 0 and n-1, as many times
-    as required by size. For instance, if size=(p,q), p*q permutations
-    will be generated, and the output shape will be (p,q,n), because each
-    permutation is of size n.
-
-    If the size argument is ambiguous on the number of dimensions, the first
-    argument may be a plain integer i, which should correspond to len(size).
-    Note that the output will then be of dimension i+1.
-
-    :returns: :class:`RandomVariable`, NewRandomState
-
-.. function:: multinomial(random_state, size, p_vals=[0.5, 0.5])
-
-    Sample from a multinomial distribution defined by probabilities pvals,
-    as many times as required by size. For instance, if size=(p,q), p*q
-    samples will be drawn, and the output shape will be (p,q,len(pvals)).
-
-    If the size argument is ambiguous on the number of dimensions, the first
-    argument may be a plain integer i, which should correspond to len(size).
-    Note that the output will then be of dimension i+1.
-
-    :returns: :class:`RandomVariable`, NewRandomState
-