提交 12ee12f4 authored 作者: Frederic's avatar Frederic

Doc Variable and Apply node correctly (for Variable.eval)

上级 ce2ceb7b
.. _libdoc_gof_graph:
==============================================
:mod:`graph` -- Interface for the Theano graph
==============================================
.. module:: graph
:platform: Unix, Windows
:synopsis: Interface for types of symbolic variables
.. moduleauthor:: LISA
---------
Reference
---------
.. automodule:: theano.gof.graph
:members:
...@@ -13,6 +13,7 @@ ...@@ -13,6 +13,7 @@
.. toctree:: .. toctree::
:maxdepth: 1 :maxdepth: 1
graph
fgraph fgraph
toolbox toolbox
type type
......
...@@ -4,7 +4,7 @@ ...@@ -4,7 +4,7 @@
:mod:`type` -- Interface for types of variables :mod:`type` -- Interface for types of variables
================================================ ================================================
.. module:: fgraph .. module:: type
:platform: Unix, Windows :platform: Unix, Windows
:synopsis: Interface for types of symbolic variables :synopsis: Interface for types of symbolic variables
.. moduleauthor:: LISA .. moduleauthor:: LISA
......
...@@ -117,7 +117,8 @@ then be used like a normal Python function. ...@@ -117,7 +117,8 @@ then be used like a normal Python function.
.. note:: .. note::
As a shortcut, you can skip step 3, and just use a variable's As a shortcut, you can skip step 3, and just use a variable's
:func:`eval` method. The :func:`eval` method is not as flexible :func:`eval <theano.gof.graph.Variable.eval>` method.
The :func:`eval` method is not as flexible
as :func:`function` but it can do everything we've covered in as :func:`function` but it can do everything we've covered in
the tutorial so far. It has the added benefit of not requiring the tutorial so far. It has the added benefit of not requiring
you to import :func:`function` . Here is how :func:`eval` works: you to import :func:`function` . Here is how :func:`eval` works:
......
...@@ -451,6 +451,31 @@ class Variable(Node): ...@@ -451,6 +451,31 @@ class Variable(Node):
inputs_to_values inputs_to_values
A dictionary mapping theano Variables to values. A dictionary mapping theano Variables to values.
Examples
--------
>>> import theano.tensor as T
>>> x = T.dscalar('x')
>>> y = T.dscalar('y')
>>> z = x + y
>>> z.eval({x : 16.3, y : 12.1})
array(28.4)
We passed :func:`eval` a dictionary mapping symbolic theano
variables to the values to substitute for them, and it returned
the numerical value of the expression.
Notes
-----
`eval` will be slow the first time you call it on a variable --
it needs to call :func:`function` to compile the expression behind
the scenes. Subsequent calls to :func:`eval` on that same variable
will be fast, because the variable caches the compiled function.
This way of computing have more overhead then a normal Theano
function, so don't use it too much in real script. But is
useful for interactive session and quick experiments.
""" """
if inputs_to_values is None: if inputs_to_values is None:
......
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