提交 e95d9b5a authored 作者: Arnaud Bergeron's avatar Arnaud Bergeron

Add a mode to docgen to run the code samples in the documentation.

This alleviates copying them elsewhere to ensure they are not broken.
上级 7c672596
...@@ -16,46 +16,55 @@ Conditions ...@@ -16,46 +16,55 @@ Conditions
**IfElse Example: Comparison with Switch** **IfElse Example: Comparison with Switch**
.. code-block:: python .. testcode::
from theano import tensor as T from theano import tensor as T
from theano.ifelse import ifelse from theano.ifelse import ifelse
import theano, time, numpy import theano, time, numpy
a,b = T.scalars('a','b') a,b = T.scalars('a','b')
x,y = T.matrices('x','y') x,y = T.matrices('x','y')
z_switch = T.switch(T.lt(a,b), T.mean(x), T.mean(y)) z_switch = T.switch(T.lt(a,b), T.mean(x), T.mean(y))
z_lazy = ifelse(T.lt(a,b), T.mean(x), T.mean(y)) z_lazy = ifelse(T.lt(a,b), T.mean(x), T.mean(y))
f_switch = theano.function([a,b,x,y], z_switch,
mode=theano.Mode(linker='vm'))
f_lazyifelse = theano.function([a,b,x,y], z_lazy,
mode=theano.Mode(linker='vm'))
val1 = 0.
val2 = 1.
big_mat1 = numpy.ones((10000,1000))
big_mat2 = numpy.ones((10000,1000))
f_switch = theano.function([a,b,x,y], z_switch, n_times = 10
mode=theano.Mode(linker='vm'))
f_lazyifelse = theano.function([a,b,x,y], z_lazy,
mode=theano.Mode(linker='vm'))
val1 = 0. tic = time.clock()
val2 = 1. for i in xrange(n_times):
big_mat1 = numpy.ones((10000,1000)) f_switch(val1, val2, big_mat1, big_mat2)
big_mat2 = numpy.ones((10000,1000)) print 'time spent evaluating both values %f sec'%(time.clock()-tic)
n_times = 10 tic = time.clock()
for i in xrange(n_times):
f_lazyifelse(val1, val2, big_mat1, big_mat2)
print 'time spent evaluating one value %f sec'%(time.clock()-tic)
tic = time.clock() .. testoutput::
for i in xrange(n_times): :hide:
f_switch(val1, val2, big_mat1, big_mat2) :options: +ELLIPSIS
print 'time spent evaluating both values %f sec'%(time.clock()-tic)
tic = time.clock() time spent evaluating both values ... sec
for i in xrange(n_times): time spent evaluating one value ... sec
f_lazyifelse(val1, val2, big_mat1, big_mat2)
print 'time spent evaluating one value %f sec'%(time.clock()-tic)
IfElse Op spend less time (about an half) than Switch since it computes only IfElse Op spend less time (about an half) than Switch since it computes only
one variable instead of both. one variable instead of both.
>>> python ifelse_switch.py .. code-block:: none
time spent evaluating both values 0.6700 sec
time spent evaluating one value 0.3500 sec $ python ifelse_switch.py
time spent evaluating both values 0.6700 sec
time spent evaluating one value 0.3500 sec
Note that IfElse condition is a boolean while Switch condition is a tensor, so Note that IfElse condition is a boolean while Switch condition is a tensor, so
Switch is more general. Switch is more general.
...@@ -112,7 +121,7 @@ Loops ...@@ -112,7 +121,7 @@ Loops
**Scan Example: Calculating a Polynomial** **Scan Example: Calculating a Polynomial**
.. code-block:: python .. testcode::
import theano import theano
import theano.tensor as T import theano.tensor as T
...@@ -133,7 +142,10 @@ Loops ...@@ -133,7 +142,10 @@ Loops
test_coeff = numpy.asarray([1, 0, 2], dtype=numpy.float32) test_coeff = numpy.asarray([1, 0, 2], dtype=numpy.float32)
print calculate_polynomial(test_coeff, 3) print calculate_polynomial(test_coeff, 3)
# 19.0
.. testoutput::
19.0
...@@ -267,7 +279,7 @@ Printing/Drawing Theano graphs ...@@ -267,7 +279,7 @@ Printing/Drawing Theano graphs
``theano.printing.pprint(variable)`` ``theano.printing.pprint(variable)``
>>> theano.printing.pprint(prediction) >>> theano.printing.pprint(prediction) # doctest: +SKIP
gt((TensorConstant{1} / (TensorConstant{1} + exp(((-(x \\dot w)) - b)))),TensorConstant{0.5}) gt((TensorConstant{1} / (TensorConstant{1} + exp(((-(x \\dot w)) - b)))),TensorConstant{0.5})
...@@ -275,7 +287,7 @@ gt((TensorConstant{1} / (TensorConstant{1} + exp(((-(x \\dot w)) - b)))),TensorC ...@@ -275,7 +287,7 @@ gt((TensorConstant{1} / (TensorConstant{1} + exp(((-(x \\dot w)) - b)))),TensorC
``theano.printing.debugprint({fct, variable, list of variables})`` ``theano.printing.debugprint({fct, variable, list of variables})``
>>> theano.printing.debugprint(prediction) >>> theano.printing.debugprint(prediction) # doctest: +SKIP
Elemwise{gt,no_inplace} [@181772236] '' Elemwise{gt,no_inplace} [@181772236] ''
|Elemwise{true_div,no_inplace} [@181746668] '' |Elemwise{true_div,no_inplace} [@181746668] ''
| |InplaceDimShuffle{x} [@181746412] '' | |InplaceDimShuffle{x} [@181746412] ''
...@@ -293,7 +305,7 @@ Elemwise{gt,no_inplace} [@181772236] '' ...@@ -293,7 +305,7 @@ Elemwise{gt,no_inplace} [@181772236] ''
| | | | | |b [@181730156] | | | | | |b [@181730156]
|InplaceDimShuffle{x} [@181771788] '' |InplaceDimShuffle{x} [@181771788] ''
| |TensorConstant{0.5} [@181771148] | |TensorConstant{0.5} [@181771148]
>>> theano.printing.debugprint(predict) >>> theano.printing.debugprint(predict) # doctest: +SKIP
Elemwise{Composite{neg,{sub,{{scalar_sigmoid,GT},neg}}}} [@183160204] '' 2 Elemwise{Composite{neg,{sub,{{scalar_sigmoid,GT},neg}}}} [@183160204] '' 2
|dot [@183018796] '' 1 |dot [@183018796] '' 1
| |x [@183000780] | |x [@183000780]
...@@ -304,19 +316,19 @@ Elemwise{Composite{neg,{sub,{{scalar_sigmoid,GT},neg}}}} [@183160204] '' 2 ...@@ -304,19 +316,19 @@ Elemwise{Composite{neg,{sub,{{scalar_sigmoid,GT},neg}}}} [@183160204] '' 2
- Picture Printing of Graphs - Picture Printing of Graphs
>>> theano.printing.pydotprint_variables(prediction) >>> theano.printing.pydotprint_variables(prediction) # doctest: +SKIP
.. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_prediction.png .. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_prediction.png
:width: 800 px :width: 800 px
All pydotprint* requires graphviz and pydot All pydotprint* requires graphviz and pydot
>>> theano.printing.pydotprint(predict) >>> theano.printing.pydotprint(predict) # doctest: +SKIP
.. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_predic.png .. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_predic.png
:width: 800 px :width: 800 px
>>> theano.printing.pydotprint(train) # This is a small train example! >>> theano.printing.pydotprint(train) # This is a small train example! # doctest: +SKIP
.. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_train.png .. image:: ../hpcs2011_tutorial/pics/logreg_pydotprint_train.png
:width: 1500 px :width: 1500 px
......
...@@ -80,7 +80,7 @@ Exercise 6 ...@@ -80,7 +80,7 @@ Exercise 6
Theano + PyCUDA Theano + PyCUDA
--------------- ---------------
.. code-block:: python .. testcode::
import numpy, theano import numpy, theano
import theano.misc.pycuda_init import theano.misc.pycuda_init
...@@ -118,15 +118,20 @@ Theano + PyCUDA ...@@ -118,15 +118,20 @@ Theano + PyCUDA
pycuda_fct(inputs[0][0], z[0], numpy.intc(inputs[0][0].size), pycuda_fct(inputs[0][0], z[0], numpy.intc(inputs[0][0].size),
block=(512,1,1), grid=grid) block=(512,1,1), grid=grid)
return thunk return thunk
.. testoutput::
:hide:
:options: +SKIP
This contains GPU code so skip it
Test it! Test it!
>>> x = theano.tensor.fmatrix() >>> x = theano.tensor.fmatrix() # doctest: +SKIP
>>> f = theano.function([x], PyCUDADoubleOp()(x)) >>> f = theano.function([x], PyCUDADoubleOp()(x)) # doctest: +SKIP
>>> xv=numpy.ones((4,5), dtype="float32") >>> xv=numpy.ones((4,5), dtype="float32") # doctest: +SKIP
>>> assert numpy.allclose(f(xv), xv*2) >>> assert numpy.allclose(f(xv), xv*2) # doctest: +SKIP
>>> print numpy.asarray(f(xv)) >>> print numpy.asarray(f(xv)) # doctest: +SKIP
Exercises 7 Exercises 7
----------- -----------
......
...@@ -23,7 +23,7 @@ ...@@ -23,7 +23,7 @@
# Add any Sphinx extension module names here, as strings. They can be # Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones. # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.autodoc', 'sphinx.ext.todo'] extensions = ['sphinx.ext.autodoc', 'sphinx.ext.todo', 'sphinx.ext.doctest']
todo_include_todos = True todo_include_todos = True
......
...@@ -3,6 +3,11 @@ ...@@ -3,6 +3,11 @@
Glossary Glossary
======== ========
..
# This is for the doctests in the file
>>> import theano
>>> from theano import tensor
.. glossary:: .. glossary::
Apply Apply
...@@ -25,8 +30,10 @@ Glossary ...@@ -25,8 +30,10 @@ Glossary
Constant Constant
A variable with an immutable value. A variable with an immutable value.
For example, when you type For example, when you type
>>> x = tensor.ivector() >>> x = tensor.ivector()
>>> y = x + 3 >>> y = x + 3
Then a `constant` is created to represent the ``3`` in the graph. Then a `constant` is created to represent the ``3`` in the graph.
See also: :class:`gof.Constant` See also: :class:`gof.Constant`
......
...@@ -318,7 +318,7 @@ a Python (or IPython) interpreter, ...@@ -318,7 +318,7 @@ a Python (or IPython) interpreter,
.. code-block:: python .. code-block:: python
>>> import theano >>> import theano
>>> theano.test() >>> theano.test() # doctest: +SKIP
You can also run them in-place from the Git checkout directory by typing You can also run them in-place from the Git checkout directory by typing
......
...@@ -65,7 +65,7 @@ if __name__ == '__main__': ...@@ -65,7 +65,7 @@ if __name__ == '__main__':
options.update(dict([x, y or True] for x, y in options.update(dict([x, y or True] for x, y in
getopt.getopt(sys.argv[1:], getopt.getopt(sys.argv[1:],
'o:', 'o:',
['epydoc', 'rst', 'help', 'nopdf', 'cache'])[0])) ['epydoc', 'rst', 'help', 'nopdf', 'cache', 'test'])[0]))
if options['--help']: if options['--help']:
print 'Usage: %s [OPTIONS]' % sys.argv[0] print 'Usage: %s [OPTIONS]' % sys.argv[0]
print ' -o <dir>: output the html files in the specified dir' print ' -o <dir>: output the html files in the specified dir'
...@@ -74,10 +74,11 @@ if __name__ == '__main__': ...@@ -74,10 +74,11 @@ if __name__ == '__main__':
print ' --nopdf: do not produce a PDF file from the doc, only HTML' print ' --nopdf: do not produce a PDF file from the doc, only HTML'
print ' --epydoc: only compile the api documentation', print ' --epydoc: only compile the api documentation',
print '(requires epydoc)' print '(requires epydoc)'
print ' --test: run all the code samples in the documentaton'
print ' --help: this help' print ' --help: this help'
sys.exit(0) sys.exit(0)
if not (options['--epydoc'] or options['--rst']): if not (options['--epydoc'] or options['--rst'] or options['--test']):
# Default is now rst # Default is now rst
options['--rst'] = True options['--rst'] = True
...@@ -113,17 +114,18 @@ if __name__ == '__main__': ...@@ -113,17 +114,18 @@ if __name__ == '__main__':
# Generate PDF doc # Generate PDF doc
# TODO # TODO
def call_sphinx(builder, workdir, extraopts=None):
import sphinx
if extraopts is None:
extraopts = []
if not options['--cache']:
extraopts.append('-E')
sphinx.main(['', '-b', builder] + extraopts +
[os.path.join(throot, 'doc'), workdir])
if options['--all'] or options['--rst']: if options['--all'] or options['--rst']:
mkdir("doc") mkdir("doc")
sys.path[0:0] = [os.path.join(throot, 'doc')] sys.path[0:0] = [os.path.join(throot, 'doc')]
def call_sphinx(builder, workdir, extraopts=None):
import sphinx
if extraopts is None:
extraopts = []
if not options['--cache']:
extraopts.append('-E')
sphinx.main(['', '-b', builder] + extraopts +
[os.path.join(throot, 'doc'), workdir])
call_sphinx('html', '.') call_sphinx('html', '.')
if not options['--nopdf']: if not options['--nopdf']:
...@@ -142,3 +144,8 @@ if __name__ == '__main__': ...@@ -142,3 +144,8 @@ if __name__ == '__main__':
print 'OSError:', e print 'OSError:', e
except IOError, e: except IOError, e:
print 'IOError:', e print 'IOError:', e
if options['--test']:
mkdir("doc")
sys.path[0:0] = [os.path.join(throot, 'doc')]
call_sphinx('doctest', '.')
...@@ -967,6 +967,7 @@ def set_subtensor(x, y, inplace=False, ...@@ -967,6 +967,7 @@ def set_subtensor(x, y, inplace=False,
Example: To replicate the numpy expression "r[10:] = 5", type Example: To replicate the numpy expression "r[10:] = 5", type
>>> r = ivector()
>>> new_r = set_subtensor(r[10:], 5) >>> new_r = set_subtensor(r[10:], 5)
:param x: symbolic variable for the lvalue of = operation :param x: symbolic variable for the lvalue of = operation
...@@ -991,6 +992,7 @@ def inc_subtensor(x, y, inplace=False, set_instead_of_inc=False, ...@@ -991,6 +992,7 @@ def inc_subtensor(x, y, inplace=False, set_instead_of_inc=False,
Example: To replicate the numpy expression "r[10:] += 5", type Example: To replicate the numpy expression "r[10:] += 5", type
>>> r = ivector()
>>> new_r = inc_subtensor(r[10:], 5) >>> new_r = inc_subtensor(r[10:], 5)
""" """
# First of all, y cannot have a higher dimension than x, # First of all, y cannot have a higher dimension than x,
......
...@@ -892,7 +892,7 @@ class T_loading_and_saving(unittest.TestCase): ...@@ -892,7 +892,7 @@ class T_loading_and_saving(unittest.TestCase):
class T_modes(unittest.TestCase): class T_modes(unittest.TestCase):
# All tests here belog to # All tests here belong to
# http://deeplearning.net/software/theano/tutorial/modes.html # http://deeplearning.net/software/theano/tutorial/modes.html
# Theano/doc/tutorial/modes.txt # Theano/doc/tutorial/modes.txt
# Any change you do here also add it to the tutorial ! # Any change you do here also add it to the tutorial !
......
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