提交 6b02f8ca authored 作者: Frédéric Bastien's avatar Frédéric Bastien

Merge pull request #4030 from hantek/fixtesterr

solving doc test failures
...@@ -66,7 +66,7 @@ script: ...@@ -66,7 +66,7 @@ script:
- cd -; cd Theano - cd -; cd Theano
- theano-nose -v $PART - theano-nose -v $PART
- if [[ $DOC == "1" ]]; then python doc/scripts/docgen.py --nopdf --check; fi - if [[ $DOC == "1" ]]; then python doc/scripts/docgen.py --nopdf --check; fi
# - if [[ $DOC == "1" ]]; then python doc/scripts/docgen.py --test --check; fi - if [[ $DOC == "1" ]]; then python doc/scripts/docgen.py --test --check; fi
after_failure: after_failure:
- cat /home/travis/.pip/pip.log - cat /home/travis/.pip/pip.log
...@@ -41,14 +41,14 @@ Conditions ...@@ -41,14 +41,14 @@ Conditions
n_times = 10 n_times = 10
tic = time.clock() tic = time.clock()
for i in xrange(n_times): for i in range(n_times):
f_switch(val1, val2, big_mat1, big_mat2) f_switch(val1, val2, big_mat1, big_mat2)
print 'time spent evaluating both values %f sec'%(time.clock()-tic) print('time spent evaluating both values %f sec' % (time.clock()-tic))
tic = time.clock() tic = time.clock()
for i in xrange(n_times): for i in range(n_times):
f_lazyifelse(val1, val2, big_mat1, big_mat2) f_lazyifelse(val1, val2, big_mat1, big_mat2)
print 'time spent evaluating one value %f sec'%(time.clock()-tic) print('time spent evaluating one value %f sec' % (time.clock()-tic))
.. testoutput:: .. testoutput::
:hide: :hide:
...@@ -142,7 +142,7 @@ Loops ...@@ -142,7 +142,7 @@ Loops
outputs=polynomial) outputs=polynomial)
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))
.. testoutput:: .. testoutput::
......
...@@ -412,8 +412,9 @@ but it must not influence the semantics of the Op output. ...@@ -412,8 +412,9 @@ but it must not influence the semantics of the Op output.
You can try the new Op as follows: You can try the new Op as follows:
.. testcode:: example(Using make_node) .. testcode:: example
import theano
x = theano.tensor.matrix() x = theano.tensor.matrix()
f = theano.function([x], DoubleOp1()(x)) f = theano.function([x], DoubleOp1()(x))
import numpy import numpy
...@@ -425,10 +426,9 @@ You can try the new Op as follows: ...@@ -425,10 +426,9 @@ You can try the new Op as follows:
.. testoutput:: example .. testoutput:: example
:hide: :hide:
:options: +ELLIPSIS :options: +ELLIPSIS, +SKIP
... <BLANKLINE>
...
.. code-block:: none .. code-block:: none
...@@ -443,8 +443,9 @@ You can try the new Op as follows: ...@@ -443,8 +443,9 @@ You can try the new Op as follows:
[ 1.5465443 1.30803715 1.53125983 1.88291403] [ 1.5465443 1.30803715 1.53125983 1.88291403]
[ 1.6904152 0.61000201 1.76861002 1.9163731 ]] [ 1.6904152 0.61000201 1.76861002 1.9163731 ]]
.. testcode:: example (Using itypes and otypes) .. testcode:: example
import theano
x = theano.tensor.matrix() x = theano.tensor.matrix()
f = theano.function([x], DoubleOp2()(x)) f = theano.function([x], DoubleOp2()(x))
import numpy import numpy
...@@ -457,10 +458,9 @@ You can try the new Op as follows: ...@@ -457,10 +458,9 @@ You can try the new Op as follows:
.. testoutput:: example .. testoutput:: example
:hide: :hide:
:options: +ELLIPSIS :options: +ELLIPSIS, +SKIP
... <BLANKLINE>
...
.. code-block:: none .. code-block:: none
...@@ -503,8 +503,8 @@ and ``b`` are equal. ...@@ -503,8 +503,8 @@ and ``b`` are equal.
def make_node(self, x): def make_node(self, x):
# check that the theano version has support for __props__. # check that the theano version has support for __props__.
assert hasattr(self, '_props'), "Your version of theano is too old assert hasattr(self, '_props'), ("Your version of theano is too"
to support __props__." "old to support __props__.")
x = theano.tensor.as_tensor_variable(x) x = theano.tensor.as_tensor_variable(x)
return theano.Apply(self, [x], [x.type()]) return theano.Apply(self, [x], [x.type()])
......
...@@ -156,9 +156,6 @@ the params type. ...@@ -156,9 +156,6 @@ the params type.
return ("%(z)s = %(x)s * PyFloat_AsDouble(%(p)s);" % return ("%(z)s = %(x)s * PyFloat_AsDouble(%(p)s);" %
dict(z=outputs[0], x=inputs[0], p=sub['params'])) dict(z=outputs[0], x=inputs[0], p=sub['params']))
.. testoutput::
:hide:
A more complex example A more complex example
---------------------- ----------------------
...@@ -225,5 +222,3 @@ weights. ...@@ -225,5 +222,3 @@ weights.
%(z)s = alpha_%(name)s * %(x)s + beta_%(name)s * %(y)s; %(z)s = alpha_%(name)s * %(x)s + beta_%(name)s * %(y)s;
""" % dict(name=name, z=outputs[0], x=inputs[0], y=inputs[1]) """ % dict(name=name, z=outputs[0], x=inputs[0], y=inputs[1])
.. testoutput::
:hide:
...@@ -420,9 +420,9 @@ Create a test file containing: ...@@ -420,9 +420,9 @@ Create a test file containing:
t_start = time.time() t_start = time.time()
tAB = mf(A,B) tAB = mf(A,B)
t_end = time.time() t_end = time.time()
print "NP time: %f[s], theano time: %f[s] (times should be close when run on CPU!)" %( print("NP time: %f[s], theano time: %f[s] (times should be close when run on CPU!)" %(
np_end-np_start, t_end-t_start) np_end-np_start, t_end-t_start))
print "Result difference: %f" % (np.abs(AB-tAB).max(), ) print("Result difference: %f" % (np.abs(AB-tAB).max(), ))
.. testoutput:: .. testoutput::
:hide: :hide:
......
...@@ -187,7 +187,7 @@ downcast** of the latter. ...@@ -187,7 +187,7 @@ downcast** of the latter.
# test # test
some_num = 15 some_num = 15
print(triangular_sequence(some_num)) print(triangular_sequence(some_num))
print([n * (n + 1) // 2 for n in xrange(some_num)]) print([n * (n + 1) // 2 for n in range(some_num)])
.. testoutput:: .. testoutput::
......
...@@ -336,7 +336,7 @@ shows how to print all inputs and outputs: ...@@ -336,7 +336,7 @@ shows how to print all inputs and outputs:
end='') end='')
def inspect_outputs(i, node, fn): def inspect_outputs(i, node, fn):
print("output(s) value(s):", [output[0] for output in fn.outputs]) print(" output(s) value(s):", [output[0] for output in fn.outputs])
x = theano.tensor.dscalar('x') x = theano.tensor.dscalar('x')
f = theano.function([x], [5 * x], f = theano.function([x], [5 * x],
......
...@@ -125,7 +125,7 @@ array(35.0) ...@@ -125,7 +125,7 @@ array(35.0)
This makes use of the :ref:`In <function_inputs>` class which allows This makes use of the :ref:`In <function_inputs>` class which allows
you to specify properties of your function's parameters with greater detail. Here we you to specify properties of your function's parameters with greater detail. Here we
give a default value of 1 for *y* by creating a ``In`` instance with give a default value of 1 for *y* by creating a ``In`` instance with
its ``default`` field set to 1. its ``value`` field set to 1.
Inputs with default values must follow inputs without default Inputs with default values must follow inputs without default
values (like Python's functions). There can be multiple inputs with default values. These parameters can values (like Python's functions). There can be multiple inputs with default values. These parameters can
...@@ -206,15 +206,15 @@ Let's try it out! ...@@ -206,15 +206,15 @@ Let's try it out!
.. If you modify this code, also change : .. If you modify this code, also change :
.. theano/tests/test_tutorial.py:T_examples.test_examples_8 .. theano/tests/test_tutorial.py:T_examples.test_examples_8
>>> state.get_value() >>> print(state.get_value())
0 0
>>> accumulator(1) >>> accumulator(1)
array(0) array(0)
>>> state.get_value() >>> print(state.get_value())
1 1
>>> accumulator(300) >>> accumulator(300)
array(1) array(1)
>>> state.get_value() >>> print(state.get_value())
301 301
It is possible to reset the state. Just use the ``.set_value()`` method: It is possible to reset the state. Just use the ``.set_value()`` method:
...@@ -222,7 +222,7 @@ It is possible to reset the state. Just use the ``.set_value()`` method: ...@@ -222,7 +222,7 @@ It is possible to reset the state. Just use the ``.set_value()`` method:
>>> state.set_value(-1) >>> state.set_value(-1)
>>> accumulator(3) >>> accumulator(3)
array(-1) array(-1)
>>> state.get_value() >>> print(state.get_value())
2 2
As we mentioned above, you can define more than one function to use the same As we mentioned above, you can define more than one function to use the same
...@@ -234,7 +234,7 @@ shared variable. These functions can all update the value. ...@@ -234,7 +234,7 @@ shared variable. These functions can all update the value.
>>> decrementor = function([inc], state, updates=[(state, state-inc)]) >>> decrementor = function([inc], state, updates=[(state, state-inc)])
>>> decrementor(2) >>> decrementor(2)
array(2) array(2)
>>> state.get_value() >>> print(state.get_value())
0 0
You might be wondering why the updates mechanism exists. You can always You might be wondering why the updates mechanism exists. You can always
...@@ -261,7 +261,7 @@ for the purpose of one particular function. ...@@ -261,7 +261,7 @@ for the purpose of one particular function.
>>> skip_shared = function([inc, foo], fn_of_state, givens=[(state, foo)]) >>> skip_shared = function([inc, foo], fn_of_state, givens=[(state, foo)])
>>> skip_shared(1, 3) # we're using 3 for the state, not state.value >>> skip_shared(1, 3) # we're using 3 for the state, not state.value
array(7) array(7)
>>> state.get_value() # old state still there, but we didn't use it >>> print(state.get_value()) # old state still there, but we didn't use it
0 0
The ``givens`` parameter can be used to replace any symbolic variable, not just a The ``givens`` parameter can be used to replace any symbolic variable, not just a
......
...@@ -30,10 +30,7 @@ The Basics of Pickling ...@@ -30,10 +30,7 @@ The Basics of Pickling
The two modules ``pickle`` and ``cPickle`` have the same functionalities, but The two modules ``pickle`` and ``cPickle`` have the same functionalities, but
``cPickle``, coded in C, is much faster. ``cPickle``, coded in C, is much faster.
.. If you modify this code, also change : >>> from six.moves import cPickle
.. theano/tests/test_tutorial.py:T_loading_and_saving.test_loading_and_saving_3
>>> import cPickle
You can serialize (or *save*, or *pickle*) objects to a file with You can serialize (or *save*, or *pickle*) objects to a file with
``cPickle.dump``: ``cPickle.dump``:
...@@ -42,7 +39,7 @@ You can serialize (or *save*, or *pickle*) objects to a file with ...@@ -42,7 +39,7 @@ You can serialize (or *save*, or *pickle*) objects to a file with
my_obj = object() my_obj = object()
>>> f = file('obj.save', 'wb') >>> f = open('obj.save', 'wb')
>>> cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL) >>> cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
>>> f.close() >>> f.close()
...@@ -60,7 +57,7 @@ You can serialize (or *save*, or *pickle*) objects to a file with ...@@ -60,7 +57,7 @@ You can serialize (or *save*, or *pickle*) objects to a file with
To de-serialize (or *load*, or *unpickle*) a pickled file, use To de-serialize (or *load*, or *unpickle*) a pickled file, use
``cPickle.load``: ``cPickle.load``:
>>> f = file('obj.save', 'rb') >>> f = open('obj.save', 'rb')
>>> loaded_obj = cPickle.load(f) >>> loaded_obj = cPickle.load(f)
>>> f.close() >>> f.close()
...@@ -74,14 +71,14 @@ same order): ...@@ -74,14 +71,14 @@ same order):
obj2 = object() obj2 = object()
obj3 = object() obj3 = object()
>>> f = file('objects.save', 'wb') >>> f = open('objects.save', 'wb')
>>> for obj in [obj1, obj2, obj3]: >>> for obj in [obj1, obj2, obj3]:
... cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL) ... cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
>>> f.close() >>> f.close()
Then: Then:
>>> f = file('objects.save', 'rb') >>> f = open('objects.save', 'rb')
>>> loaded_objects = [] >>> loaded_objects = []
>>> for i in range(3): >>> for i in range(3):
... loaded_objects.append(cPickle.load(f)) ... loaded_objects.append(cPickle.load(f))
...@@ -121,7 +118,7 @@ For instance, you can define functions along the lines of: ...@@ -121,7 +118,7 @@ For instance, you can define functions along the lines of:
def __setstate__(self, d): def __setstate__(self, d):
self.__dict__.update(d) self.__dict__.update(d)
self.training_set = cPickle.load(file(self.training_set_file, 'rb')) self.training_set = cPickle.load(open(self.training_set_file, 'rb'))
Robust Serialization Robust Serialization
......
...@@ -66,7 +66,7 @@ Debug Print ...@@ -66,7 +66,7 @@ Debug Print
The pre-compilation graph: The pre-compilation graph:
>>> theano.printing.debugprint(prediction) # doctest: +NORMALIZE_WHITESPACE >>> theano.printing.debugprint(prediction) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
Elemwise{gt,no_inplace} [id A] '' Elemwise{gt,no_inplace} [id A] ''
|Elemwise{true_div,no_inplace} [id B] '' |Elemwise{true_div,no_inplace} [id B] ''
| |DimShuffle{x} [id C] '' | |DimShuffle{x} [id C] ''
...@@ -87,9 +87,9 @@ Elemwise{gt,no_inplace} [id A] '' ...@@ -87,9 +87,9 @@ Elemwise{gt,no_inplace} [id A] ''
The post-compilation graph: The post-compilation graph:
>>> theano.printing.debugprint(predict) # doctest: +NORMALIZE_WHITESPACE >>> theano.printing.debugprint(predict) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
Elemwise{Composite{GT(scalar_sigmoid((-((-i0) - i1))), i2)}} [id A] '' 4 Elemwise{Composite{GT(scalar_sigmoid((-((-i0) - i1))), i2)}} [id A] '' 4
|CGemv{inplace} [id B] '' 3 |...Gemv{inplace} [id B] '' 3
| |AllocEmpty{dtype='float64'} [id C] '' 2 | |AllocEmpty{dtype='float64'} [id C] '' 2
| | |Shape_i{0} [id D] '' 1 | | |Shape_i{0} [id D] '' 1
| | |x [id E] | | |x [id E]
......
...@@ -32,12 +32,13 @@ functions using either of the following two options: ...@@ -32,12 +32,13 @@ functions using either of the following two options:
functions but one or more specific function(s). functions but one or more specific function(s).
- You can also combine the profile of many functions: - You can also combine the profile of many functions:
.. testcode:: .. doctest::
:hide:
profile = theano.compile.ProfileStats() profile = theano.compile.ProfileStats()
f = theano.function(..., profile=profile) f = theano.function(..., profile=profile) # doctest: +SKIP
g = theano.function(..., profile=profile) g = theano.function(..., profile=profile) # doctest: +SKIP
... ... # doctest: +SKIP
profile.print_summary() profile.print_summary()
......
...@@ -45,7 +45,8 @@ def function_dump(filename, inputs, outputs=None, mode=None, updates=None, ...@@ -45,7 +45,8 @@ def function_dump(filename, inputs, outputs=None, mode=None, updates=None,
To load such a dump and do the compilation: To load such a dump and do the compilation:
>>> import cPickle, theano >>> from six.moves import cPickle
>>> import theano
>>> d = cPickle.load(open("func_dump.bin", "rb")) # doctest: +SKIP >>> d = cPickle.load(open("func_dump.bin", "rb")) # doctest: +SKIP
>>> f = theano.function(**d) # doctest: +SKIP >>> f = theano.function(**d) # doctest: +SKIP
......
...@@ -327,13 +327,13 @@ def dump(obj, file_handler, protocol=DEFAULT_PROTOCOL, ...@@ -327,13 +327,13 @@ def dump(obj, file_handler, protocol=DEFAULT_PROTOCOL,
>>> import theano >>> import theano
>>> foo_1 = theano.shared(0, name='foo') >>> foo_1 = theano.shared(0, name='foo')
>>> foo_2 = theano.shared(1, name='foo') >>> foo_2 = theano.shared(1, name='foo')
>>> with open('model.zip', 'w') as f: >>> with open('model.zip', 'wb') as f:
... dump((foo_1, foo_2, numpy.array(2)), f) ... dump((foo_1, foo_2, numpy.array(2)), f)
>>> numpy.load('model.zip').keys() >>> numpy.load('model.zip').keys()
['foo', 'foo_2', 'array_0', 'pkl'] ['foo', 'foo_2', 'array_0', 'pkl']
>>> numpy.load('model.zip')['foo'] >>> numpy.load('model.zip')['foo']
array(0) array(0)
>>> with open('model.zip') as f: >>> with open('model.zip', 'rb') as f:
... foo_1, foo_2, array = load(f) ... foo_1, foo_2, array = load(f)
>>> array >>> array
array(2) array(2)
......
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