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pytensor
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0d29c1a9
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0d29c1a9
authored
3月 06, 2009
作者:
Olivier Breuleux
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go go part two
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cop.txt
doc/tutorials/advanced/ex1/cop.txt
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ctype.txt
doc/tutorials/advanced/ex1/ctype.txt
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doc/tutorials/advanced/ex1/cop.txt
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0d29c1a9
...
@@ -3,6 +3,163 @@
...
@@ -3,6 +3,163 @@
Implementing the arithmetic Ops in C
Implementing the arithmetic Ops in C
====================================
====================================
Now that we have set up our ``double`` type properly to allow C
implementations for operations that work on it, all we have to do now
is to actually define these operations in C.
How does it work?
=================
Before a C :ref:`op` is executed, the variables related to each of its
inputs will be declared and will be filled appropriately, either from
an input provided by the end user (using c_extract) or it might simply
have been calculated by another operation. For each of the outputs,
the variables associated to them will be declared and initialized.
The operation then simply has to compute what it needs to using the
input variables and place the results in the output variables.
What needs to be defined
========================
There are less methods to define for an Op than for a Type:
- **c_code(node, name, input_names, output_names, sub)**
- This must return C code that carries the computation we want to
do.
- **c_code_cleanup(node, name, input_names, output_names, sub)**
- This must return C code that cleans up whatever c_code allocated
and that we must free.
- *Default* The default behavior is to do nothing.
- **c_compile_args(), c_headers(), c_libraries(), c_support_code()**
- Allows you to specify headers, libraries, special g++ arguments or
helper functions/structs that the type needs. See :ref:`op`.
The ``name`` argument is currently given an invalid value, so steer
away from it. As was the case with Type, ``sub['fail']`` provides
failure code that you *must* use if you want to raise an exception,
after setting the exception message.
The ``node`` argument is an :ref:`apply` node representing an
application of the current Op on a list of inputs, producing a list of
outputs. ``input_names`` and ``output_names`` arguments contain as
many strings as there are inputs and outputs to the application of the
Op and they correspond to the ``name`` that is passed to the type of
each Result in these lists. For example, if ``node.inputs[0].type ==
double``, then ``input_names[0]`` is the ``name`` argument passed to
``double.c_declare`` etc. when the first input is processed by Theano.
In a nutshell, ``input_names`` and ``output_names`` parameterize the
names of the inputs your operation needs to use and the outputs it
needs to put results into. But this will be clear with the examples.
Defining the methods
====================
We will be defining C code for the multiplication Op on doubles.
**c_code**
.. code-block:: python
def c_code(node, name, input_names, output_names, sub):
x_name, y_name = input_names[0], input_names[1]
output_name = output_names[0]
return """
%(output_name)s = %(x_name)s * %(y_name)s;
""" % locals()
mul.c_code = c_code
And that's it. As we enter the scope of the C code we are defining in
the method above, many variables are defined for us. Namely, the
variables x_name, y_name and output_name are all of the primitive C
``double`` type and they were declared using the C code returned by
``double.c_declare``.
Implementing multiplication is as simple as multiplying the two input
doubles and setting the output double to what comes out of it. If you
had more than one output, you would simply set the variable(s) for
each output to what they should be.
.. warning::
Do *NOT* use C's ``return`` statement to return the result(s) of
the computations. Set the output variables directly as shown
above. Theano will pick them up for you.
**c_code_cleanup**
There is nothing to cleanup after multiplying two doubles. Typically,
you won't need to define this method unless you malloc() some
temporary storage (which you would free() here) or create temporary
Python objects (which you would Py_XDECREF() here).
Final version
=============
As before, I tried to organize the code in order to minimize
repetition. You can check that mul produces the same C code in this
version that it produces in the code I gave above.
.. code-block:: python
from theano import gof
class BinaryDoubleOp(gof.Op):
def __init__(self, name, fn, ccode):
self.name = name
self.fn = fn
self.ccode = ccode
def make_node(self, x, y):
if isinstance(x, (int, float)):
x = gof.Constant(double, x)
if isinstance(y, (int, float)):
y = gof.Constant(double, y)
if x.type != double or y.type != double:
raise TypeError('%s only works on doubles' % self.name)
return gof.Apply(self, [x, y], [double()])
def perform(self, node, (x, y), (z, )):
z[0] = self.fn(x, y)
def __str__(self):
return self.name
def c_code(self, node, name, (x, y), (z, ), sub):
return self.ccode % locals()
add = BinaryDoubleOp(name = 'add',
fn = lambda x, y: x + y,
ccode = "%(z)s = %(x)s + %(y)s;")
sub = BinaryDoubleOp(name = 'sub',
fn = lambda x, y: x - y,
ccode = "%(z)s = %(x)s - %(y)s;")
mul = BinaryDoubleOp(name = 'mul',
fn = lambda x, y: x * y,
ccode = "%(z)s = %(x)s * %(y)s;")
div = BinaryDoubleOp(name = 'div',
fn = lambda x, y: x / y,
ccode = "%(z)s = %(x)s / %(y)s;")
**Next:** `Example 2 - cons_cell`_
**Next:** `Example 2 - cons_cell`_
...
...
doc/tutorials/advanced/ex1/ctype.txt
浏览文件 @
0d29c1a9
...
@@ -152,6 +152,7 @@ it, it's best to publish it somewhere.
...
@@ -152,6 +152,7 @@ it, it's best to publish it somewhere.
return """
return """
%(name)s = 0.0;
%(name)s = 0.0;
""" % dict(name = name)
""" % dict(name = name)
double.c_init = c_init
Still straightforward. This function simply has to initialize the
Still straightforward. This function simply has to initialize the
double we declared previously to a suitable value. This is useful if
double we declared previously to a suitable value. This is useful if
...
@@ -181,6 +182,7 @@ called, without knowing for sure which of the two.
...
@@ -181,6 +182,7 @@ called, without knowing for sure which of the two.
}
}
%(name)s = PyFloat_AsDouble(py_%(name)s);
%(name)s = PyFloat_AsDouble(py_%(name)s);
""" % dict(name = name, fail = sub['fail'])
""" % dict(name = name, fail = sub['fail'])
double.c_extract = c_extract
This method is slightly more sophisticated. What happens here is that
This method is slightly more sophisticated. What happens here is that
we have a reference to a Python object which Theano has placed in
we have a reference to a Python object which Theano has placed in
...
@@ -218,6 +220,7 @@ API) and we put it in our double variable that we declared previously.
...
@@ -218,6 +220,7 @@ API) and we put it in our double variable that we declared previously.
py_%(name)s = Py_None;
py_%(name)s = Py_None;
}
}
""" % dict(name = name)
""" % dict(name = name)
double.c_sync = c_sync
This function is probably the trickiest. What happens here is that we
This function is probably the trickiest. What happens here is that we
have computed some operation on doubles and we have put the result
have computed some operation on doubles and we have put the result
...
@@ -267,6 +270,7 @@ unlikely to ever happen, but if it ever does, better safe than sorry.
...
@@ -267,6 +270,7 @@ unlikely to ever happen, but if it ever does, better safe than sorry.
def c_cleanup(self, name, sub):
def c_cleanup(self, name, sub):
return ""
return ""
double.c_cleanup = c_cleanup
We actually have nothing to do here. We declared a double on the stack
We actually have nothing to do here. We declared a double on the stack
so the C language will reclaim it for us when its scope ends. We
so the C language will reclaim it for us when its scope ends. We
...
...
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