Default more args of the RNG.

doc/source/array.rst

@@ -443,7 +443,7 @@ Generating Arrays of Random Numbers
 
 .. module:: pyopencl.clrandom
 
-.. class:: RanluxGenerator(self, queue, num_work_items, max_work_items, luxury=2, seed=None)
+.. class:: RanluxGenerator(self, queue, num_work_items=None,  luxury=2, seed=None, max_work_items=None)
 
     :param queue: :class:`pyopencl.CommandQueue`, only used for initialization
     :param luxury: the "luxury value" of the generator, and should be 0-4, where 0 is fastest
@@ -451,16 +451,20 @@ Generating Arrays of Random Numbers
         sets the p-value of RANLUXCL.
     :param num_work_items: is the number of generators to initialize, usually corresponding
         to the number of work-items in the NDRange RANLUXCL will be used with.
+        May be `None`, in which case a default value is used.
     :param max_work_items: should reflect the maximum number of work-items that will be used
         on any parallel instance of RANLUXCL. So for instance if we are launching 5120
         work-items on GPU1 and 10240 work-items on GPU2, GPU1's RANLUXCLTab would be
         generated by calling ranluxcl_intialization with numWorkitems = 5120 while
         GPU2's RANLUXCLTab would use numWorkitems = 10240. However maxWorkitems must
         be at least 10240 for both GPU1 and GPU2, and it must be set to the same value
-        for both.
+        for both. (may be `None`)
 
     .. versionadded:: 2011.2
 
+    .. versionchanged:: 2012.2
+        Added default value for `num_work_items`.
+
     .. attribute:: state
 
         A :class:`pyopencl.array.Array` containing the state of the generator.
@@ -783,4 +787,3 @@ Fast Fourier Transforms
 
 Bogdan Opanchuk's `pyfft <http://pypi.python.org/pypi/pyfft>`_ package offers a
 variety of GPU-based FFT implementations.
-

pyopencl/clrandom.py

@@ -10,12 +10,18 @@ import numpy as np
 
 
 class RanluxGenerator(object):
-    def __init__(self, queue, num_work_items,
+    def __init__(self, queue, num_work_items=None,
             luxury=None, seed=None, no_warmup=False,
             use_legacy_init=False, max_work_items=None):
         if luxury is None:
             luxury = 4
 
+        if num_work_items is None:
+            if queue.device.type == cl.device_type.CPU:
+                num_work_items = 8 * queue.device.max_compute_units
+            else:
+                num_work_items = 64 * queue.device.max_compute_units
+
         if seed is None:
             from time import time
             seed = int(time()*1e6) % 2<<30
@@ -253,12 +259,7 @@ class RanluxGenerator(object):
 
 @first_arg_dependent_memoize
 def _get_generator(queue, luxury=None):
-    if queue.device.type == cl.device_type.CPU:
-        num_work_items = 8 * queue.device.max_compute_units
-    else:
-        num_work_items = 64 * queue.device.max_compute_units
-
-    gen = RanluxGenerator(queue, num_work_items, luxury=luxury)
+    gen = RanluxGenerator(queue, luxury=luxury)
     queue.finish()
     return gen